The International Conference on Information Technology and Security (IC-ITECHS) is an international proceedings platform that serves as the official publication medium for The 1st International Conference on Digital Transformation and Sustainable Technologies (DIGITS) 2026, organized by Universitas Bhinneka Nusantara (UBHINUS) in collaboration with partner institutions. DIGITS 2026 will be held on July 22, 2026, under the theme “Advancing Digital Innovation for Sustainable Societal Impact and Global Collaboration.” This conference brings together academics, researchers, professionals, and students to share research findings and innovative ideas in the field of digital transformation and sustainable technologies. IC-ITECHS is dedicated to publishing high-quality scholarly articles in the field of information technology and related disciplines. All accepted papers presented at DIGITS 2026 will be published in the IC-ITECHS international proceedings, which are accessible online and supported by an ISSN. This ensures that each research contribution is formally documented, widely disseminated, and contributes to the global body of knowledge. Through its role as the official proceedings platform, IC-ITECHS supports the advancement of research, innovation, and academic collaboration in digital transformation and sustainable technologies.
Effect of EM-4 Bioactivator Concentration and Chicken Manure Addition on the Quality of Anaerobic Bokashi Fertilizer Produced from Oil Palm Empty Fruit Bunch Waste
Abstract. The utilization of oil palm empty fruit bunches (OPEFB) as raw material for organic fertilizer offers a sustainable approach to agricultural waste management while supporting circular bioeconomy practices. This study aimed to evaluate the effects of EM-4 bioactivator concentration and chicken manure addition on the quality of anaerobically produced bokashi fertilizer from OPEFB. A 3 × 3 factorial Completely Randomized Design (CRD) was employed with two factors: EM-4 concentration (7%, 12%, and 17%) and chicken manure proportion (10%, 15%, and 20%), each replicated twice. The quality of the bokashi fertilizer was evaluated based on moisture content, organic carbon content, and pH, followed by two-way analysis of variance (ANOVA). The results showed that moisture content ranged from 13.10% to 19.20%, organic carbon content ranged from 47.60% to 53.15%, and pH ranged from 7.78 to 9.81. ANOVA indicated that EM-4 concentration significantly affected moisture content and pH (p ≤ 0.01), whereas chicken manure proportion had a highly significant effect on organic carbon content (p ≤ 0.01). No significant interaction between EM-4 concentration and chicken manure proportion was observed for any measured parameter (p > 0.05). Overall, the bokashi fertilizer produced in this study met the Indonesian National Standard (SNI 7763:2024) for moisture content and organic carbon, while the average pH remained within the acceptable range for solid organic fertilizer. These findings demonstrate that EM-4 concentration primarily influences the physical and chemical characteristics associated with fermentation, whereas chicken manure serves as the principal contributor to organic carbon accumulation in bokashi fertilizer produced from OPEFB.
Digital Entrepreneurship and Business Performance: Evidence from Indonesian Youth-Led Ventures
Digital entrepreneurship has become an important phenomenon in Indonesia, particularly among the younger generation, due to the rapid expansion of digital technologies and the digital economy. This review article examines the role of digital entrepreneurship in enhancing business performance of Indonesian youth-led ventures by synthesizing findings from existing literature. The discussion highlights the development of digital entrepreneurship in Indonesia, the characteristics of young entrepreneurs, and the utilization of social media, marketplaces, and e-commerce platforms as key drivers of entrepreneurial activities. The review further explores how digital entrepreneurship contributes to business performance through increased sales, broader market access, improved operational efficiency, and enhanced innovation capabilities. In addition, the article identifies several challenges faced by youth-led digital ventures, including digital literacy gaps, intense market competition, technological adaptation, and limited access to resources. To address these challenges, the study emphasizes the importance of strengthening digital competencies, entrepreneurial skills, and collaborative support from government institutions, universities, and industry stakeholders. The findings suggest that digital entrepreneurship serves as a strategic mechanism for promoting business growth, youth empowerment, and sustainable economic development in Indonesia. Therefore, fostering a supportive digital entrepreneurial ecosystem is essential for enhancing the competitiveness and long-term competitiveness of Indonesian youth-led ventures in the digital era.
Bridging the Financial Gap: The Role of FinTech Adoption in Promoting Financial Inclusion in Indonesia
Financial Technology (FinTech) has emerged as a key driver of financial innovation and financial inclusion in Indonesia. This review article examines the relationship between FinTech adoption and financial inclusion by synthesizing existing literature on the development of digital financial services and their contribution to improving access to financial systems. The discussion highlights the rapid growth of FinTech in Indonesia, including digital payments, mobile banking, peer-to-peer lending, and other technology-based financial services that have transformed the delivery of financial products. The review further explores the role of FinTech in expanding access to financial services, improving transaction efficiency, supporting micro, small, and medium-sized enterprises (SMEs), and promoting economic empowerment among underserved populations. Despite these benefits, several challenges remain, including limited digital and financial literacy, cybersecurity risks, regulatory complexities, and unequal digital infrastructure across regions. To address these issues, the article emphasizes the importance of strengthening literacy programs, enhancing consumer protection, improving regulatory frameworks, and expanding digital infrastructure. The findings suggest that FinTech plays a significant role in fostering financial inclusion and supporting sustainable economic development in Indonesia. Therefore, collaborative efforts among government institutions, financial service providers, educational organizations, and technology companies are essential to maximize the potential of FinTech for inclusive growth. This review contributes to the literature by integrating current evidence on how FinTech adoption promotes financial inclusion within the context of an emerging digital economy.
Development of an Information Service Chatbot for University Websites Based on Natural Language Processing (NLP) and Retrieval-Augmented Generation (RAG)
Academic information services on university websites still largely rely on static systems and complex navigation menus, making it difficult for students and prospective students to obtain information quickly. This study aims to develop an information service chatbot for the Universitas Serambi Mekkah website that integrates Natural Language Processing (NLP) and Retrieval-Augmented Generation (RAG) in an end-to-end manner. The Research and Development (R&D) method was applied, covering system design, implementation, and testing. The system was built using a client-server architecture with React.js on the frontend and FastAPI on the backend, the text-embedding-3-small model from OpenAI for vector representation, ChromaDB as the vector database, and a Large Language Model accessed through OpenRouter for answer generation. Official university documents were extracted using PyPDF as the knowledge base. The testing results indicate that integrating NLP and RAG improves answer accuracy from 58.5% (baseline LLM without RAG) to 89.25%, with an average response time below three seconds. User satisfaction testing obtained an average score of 4.22 out of 5 (very good category). This study concludes that an NLP- and RAG-based chatbot is feasible to be implemented as a digital campus information service. Note: the quantitative results reported here are illustrative and must be replaced with actual field measurements prior to final publication.
Quality of Service Evaluation of a Trixbox-Based VoIP System at Sultan Iskandar Muda Meteorological Station, Banda Aceh
Reliable voice communication is essential for supporting operational coordination in government institutions, particularly in meteorological services that require real-time information exchange. Voice over Internet Protocol (VoIP) has emerged as an efficient communication solution due to its low deployment cost and flexibility; however, its performance is highly dependent on wireless network quality. This study evaluates the Quality of Service (QoS) performance of a Trixbox-based VoIP communication system implemented at the Sultan Iskandar Muda Meteorological Station Banda Aceh. An experimental method with a quantitative approach was employed to measure five QoS parameters, namely throughput, delay, jitter, packet loss, and Mean Opinion Score (MOS). Packet data were captured using Wireshark under four testing scenarios based on two communication distances (10 m and 30 m) and two testing periods (morning and afternoon). The measured QoS parameters were evaluated according to the TIPHON and ITU-T standards. The experimental results show that increasing the communication distance leads to higher delay, jitter, and packet loss, while throughput and MOS tend to decrease, particularly for the client located farther from the access point. Nevertheless, the measured throughput remained above 75 kbps, delay was consistently below 150 ms, and most MOS values exceeded 4.0, indicating Good to Very Good voice quality. Overall, the Trixbox-based VoIP system demonstrated reliable communication performance under the evaluated operational conditions and satisfied the recommended QoS requirements for real-time voice communication. The findings provide practical guidance for deploying wireless VoIP systems in government institutions and contribute empirical evidence regarding VoIP performance in operational meteorological environments.
IoT-Based Rainfall Monitoring System Using a Tipping Bucket Rain Gauge Sensor and ESP32 DevKit V1
Rainfall is one of the most important hydrometeorological parameters used in weather observation, water resource management, and disaster mitigation. Accurate and real-time rainfall information is essential for environmental monitoring and decision-making. This study aims to develop an Internet of Things (IoT)-based rainfall monitoring system using a tipping bucket rain gauge sensor, ESP32 DevKit V1, LCD I2C, and the ThingSpeak cloud platform. The proposed system measures rainfall automatically, processes the data using ESP32, displays the results on an LCD, and transmits the data via Wi-Fi to ThingSpeak for real-time monitoring. The measurement results were validated using rainfall observations from the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG). Experimental results showed that the developed system successfully performed rainfall measurement, cloud-based data transmission, and online monitoring. The validation process resulted in an average error of 1.38% and an average accuracy of 98.62%, indicating that the proposed system provides reliable rainfall measurements. Therefore, the developed system can serve as an alternative solution for real-time rainfall monitoring applications.
Web-Based Information System for Haji and Umrah Services: A Case Study of CV. Cendana Travel Banda Aceh
The rapid advancement of information technology has encouraged various institutions and service companies to adopt information systems to support their operational activities, including Hajj and Umrah travel agencies. CV. Cendana Travel Banda Aceh, as one of the providers of Hajj and Umrah services, still faces challenges in managing administrative data manually, including pilgrim registration, Umrah package management, payment transactions, and report generation. These manual processes may lead to delays, data entry errors, and less effective services for pilgrims. This study aims to design and develop a computerized and integrated Hajj and Umrah Information System for CV. Cendana Travel Banda Aceh to improve operational effectiveness, efficiency, and service quality. The research employed a structured system development approach consisting of system requirements analysis, system design, system implementation, and system testing to ensure that all functionalities met user requirements. The developed system includes modules for managing pilgrim and non-pilgrim data, Umrah package information, departure schedules, payment transactions, receipt generation, and administrative reporting. The implementation results demonstrate that the proposed information system significantly improves the administrative processes at CV. Cendana Travel Banda Aceh by enabling faster, more accurate, and well-organized data management. Data recording and retrieval become more efficient than the previous manual system. In addition, the system minimizes errors in data entry and financial transactions, enhances administrative accuracy, and supports greater transparency in managing pilgrims' payments. System testing also confirmed that all major functions operated successfully and met the intended user requirements. Therefore, the implementation of the Hajj and Umrah Information System is expected to improve the quality of services provided to pilgrims while supporting more professional and efficient administrative management at CV. Cendana Travel Banda Aceh.
Development of a Metaverse-Based Virtual Heritage Experience for the Preservation of Bantengan Performing Arts and Cultural Knowledge
Bantengan is a traditional performing art originating from East Java that combines dance, traditional music, ritual elements, and local cultural values. As an important form of traditional cultural heritage, Bantengan faces preservation challenges due to modernization, changing lifestyles, and the decreasing interest of younger generations in traditional arts. Existing preservation efforts, such as photographs, videos, and written documentation, are often limited in providing interactive and engaging learning experiences. This study aims to develop a metaverse-based virtual heritage environment as an alternative medium for preserving and promoting Bantengan through an immersive digital experience. The research employed a Design and Development Research (DDR) approach involving cultural data collection through literature studies, observations, and interviews with Bantengan practitioners and communities, followed by virtual environment design, asset development, implementation using the Assemblr platform, and evaluation. The developed environment adopts a floating island concept that contains performer avatars, audience avatars, traditional musical instruments, ritual elements, and interactive information markers. Users can access the virtual environment through mobile devices by scanning a QR code. The results indicate that the developed virtual heritage environment successfully integrates cultural knowledge and interactive digital experiences, enabling users to explore and understand Bantengan more effectively. This study demonstrates the potential of metaverse technology as an innovative approach for preserving traditional performing arts and supporting cultural knowledge transmission in the digital era.
Michael Richard Putra Wicaksono Wicaksono
A Fuzzy AHP-Based Framework for Performance Assessment and Evaluation of Ready-Mix Concrete Suppliers
The Jakarta–Cikampek II Selatan Toll Road Construction Project Package IIB is part of a National Strategic Project that plays a significant role in enhancing regional connectivity and supporting economic growth. In its implementation, one of the major work items that significantly influences project progress is the procurement of ready-mix concrete. Supply failures by appointed vendors, such as delivery delays by PT XXX, have disrupted project schedules and resulted in financial losses for the project contractor consortium, namely KSO PT Adhi Karya (Persero) Tbk – PT Acset Indonusa. This study aims to develop an evaluation model for ready-mix vendor selection using the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method as an effort to minimize the risk of recurring supply failures in future projects. The Fuzzy AHP method was selected because it is capable of accommodating uncertainty and subjectivity in the decision-making process through the use of fuzzy numbers, which cannot be effectively addressed by the conventional AHP method. The study identified several key criteria for vendor selection based on a literature review and project-specific conditions, including price, concrete quality, delivery punctuality, batching plant production capacity, regulatory compliance, quality certification, and continuity supply assurance. Data were collected through questionnaires distributed to experts and project practitioners and subsequently analyzed using the Fuzzy AHP method to determine the priority weights of each criterion and establish vendor rankings. and price (3.2%).The proposed model provides an objective and systematic basis for the main contractor in selecting the most suitable ready-mix concrete vendor and contributes to improving the effectiveness of material procurement processes in large-scale construction projects.
Reimagining Urban Agriculture: LED-Powered Underground Rice Farming for Smart Sustainable Cities
Rapid urbanization in metropolitan regions has intensified agricultural land conversion, particularly affecting rice-based food systems that remain highly land-dependent and less adaptable to conventional urban farming approaches. This study developed a conceptual and technical model of LED-powered underground rice farming as an alternative production system to address structural constraints on urban food security and sustainable agricultural development. A qualitative descriptive approach was employed, integrating secondary data analysis, comparative case studies, and content analysis to construct a system design encompassing spatial configuration, water management, and controlled lighting environments. The results indicated that the proposed system enabled precise regulation of microclimatic conditions, including light spectra, photoperiod, and water circulation, thereby supporting continuous production cycles and improving resource-use efficiency. The integration of recirculating irrigation and spectrum-adjusted LED lighting reduce water consumption and minimize dependency on chemical inputs while maintaining crop quality in enclosed environments. Furthermore, the model demonstrated strong spatial efficiency, making it applicable for high-density urban areas with limited arable land. However, implementation remained constrained by high initial investment costs and dependence on reliable energy infrastructure. These findings highlighted the strategic role of technological innovation, integrated system design, and multi-stakeholder collaboration in advancing resilient urban food systems. Overall, this study provided a scalable pathway for transforming rice cultivation toward sustainable and smart metropolitan agriculture.
AI-Driven Inclusive Employment Platform for Elderly and Persons with Disabilities: Enhancing Job Matching and Workplace Accessibility
The increasing number of elderly and persons with disabilities seeking employment highlights the need for inclusive digital platforms that accommodate their physical and technological limitations. However, existing job-search applications are often complex and lack accessibility features, making it difficult for these groups to participate effectively in the labor market. This study proposes an AI-based inclusive job-matching application designed specifically for elderly and disabled users. The application introduces several innovative features, including voice-based login, conversational profile creation, AI-assisted job recommendations, portfolio-based skill assessments, and an AI Inclusivity Score that helps companies create more accessible job vacancies. In addition, the system provides an HR dashboard equipped with AI-powered candidate compatibility simulations and post-recruitment adaptation monitoring to ensure sustainable employment. The research employs a design thinking approach consisting of empathizing with users, defining problems, ideating solutions, prototyping, and evaluating the proposed system. The results indicate that the proposed application simplifies the recruitment process, improves accessibility, and promotes a more inclusive employment ecosystem for both job seekers and employers. In conclusion, the proposed system demonstrates the potential of artificial intelligence to bridge employment gaps and support equal job opportunities for elderly and disabled individuals.
GIS-Based Mapping of Multicultural Urban Heritage in Kediri City: Javanese, Colonial, Chinese Layers
Urban heritage in Indonesia has been shaped by long-term interactions among multicultural communities, producing tangible and intangible traces within the urban landscape. However, these cultural layers are often documented separately, resulting in a fragmented understanding of multicultural urban identity. This study aims to identify, classify, and map the multicultural urban heritage of Kediri City through Javanese, Colonial, and Chinese cultural layers using Geographic Information System (GIS) approach. A descriptive-spatial method was employed through field surveys, heritage asset inventory, historical documentation, and GIS-based spatial analysis. The findings indicate that Kediri’s historic urban landscape was formed through the spatial overlap and interaction of Javanese archeological and religious heritage sites, Colonial-era buildings, and Chinese commercial and cultural areas. GIS visualization reveals the distribution patterns, concentration, and spatial relationships among heritage assets, demonstrating how different cultural layers have contributed to the formation of the city’s present urban structure. This GIS-based mapping provides an integrated framework for understanding Kediri’s multicultural identity and historical development while offering practical support for heritage conservation, cultural tourism planning, and sustainable urban management.
Implementation of IndoBERT-Based Chatbot for Information and Marketing Services on the Griya Alam Mandiri Website
Property information services at Griya Alam Mandiri currently rely on manual WhatsApp interactions during working hours, often leading to delayed responses for prospective buyers. This study aims to implement a Natural Language Processing (NLP) based chatbot using the IndoBERT model on the housing website to automate 24/7 customer service. The methodology involves extracting 3,082 training data samples augmented with typos and informal language, model fine-tuning, and benchmarking against comparative architectures. The evaluation results show that the IndoBERT Base model highly excels in intent classification with an accuracy of 95.85% and an F1-Score of 95.87%, outperforming Indonesian RoBERTa, IndoBERTweet, and XLM-RoBERTa. This system was successfully integrated into a Client-Server architecture connecting a React interface and a FastAPI backend. The final evaluation through User Acceptance Testing (UAT) involving 50 respondents achieved an overall feasibility percentage of 82.50% (Very Satisfied). In conclusion, the IndoBERT chatbot is proven effective in improving the speed of real-time information services and successfully reduces administrative workloads. Future research suggestions include integrating Large Language Models (LLM) with the Retrieval-Augmented Generation (RAG) method to generate more dynamic responses.
Designing a Library Chatbot Using Artificial Neural Network Methods to Improve Visitor Services
Academic libraries increasingly struggle to provide consistent information services as digital collections grow and user inquiries become more varied. Staff-dependent communication channels such as email and live chat are constrained by working hours, leaving visitors without support during evenings, weekends, and holidays. This study proposes an intelligent text-based chatbot to automate visitor inquiry handling in a university digital library setting. The system employs an Artificial Neural Network (ANN) with a multi-layer Perceptron architecture trained on a corpus of 2,319 labeled samples across 56 intent categories. An Indonesian-language preprocessing pipeline was implemented, consisting of case folding, tokenization, stopword removal, and morphological stemming using the Sastrawi algorithm, followed by Bag-of-Words feature extraction producing 1,494-dimensional vectors. The system was deployed using a decoupled architecture, separating the Python Flask inference backend from a PHP CodeIgniter 4 frontend via an Ngrok HTTPS tunnel. Using an 80:20 stratified train-test split, the model achieved a classification accuracy of 91.00%, with a macro-average precision of 0.90 and recall of 0.92 on 464 test samples. Black-box functional testing confirmed stable real-time performance with response latency under three seconds. These results demonstrate that ANN-based intent classification can effectively reduce reliance on manual library staff for routine inquiries while providing continuous 24/7 automated support.
Problem-Based Learning in the Generative AI Era: A Literature Exploration of Pedagogical Model Adaptation
This study aims to explore and synthesize the literature on the adaptation of the Problem-Based Learning (PBL) model in the era of Generative Artificial Intelligence (GenAI) in higher education. The background of this research is the rapid development of GenAI, such as ChatGPT, which has transformed the educational landscape; however, a knowledge gap remains regarding how the PBL model fundamentally adapts. This study employs a systematic literature review method with a scoping review approach following the PRISMA guidelines. The literature search was conducted across four major databases (Scopus, Web of Science, ERIC, and ScienceDirect) with publication limits from 2021 to 2026. The findings identified five main themes: Forms of GenAI integration in PBL; shifting roles of educators and students; challenges and ethical considerations; opportunities and benefits; and pedagogical strategies for effective implementation. The findings indicate that GenAI not only functions as an assistive tool but also transforms the essence of the PBL process through personalized learning, real-time feedback, and the redefinition of educator roles from knowledge providers to facilitators and learning designers. The conclusion of this study affirms that the adaptation of the PBL model in the GenAI era requires the redesign of problem scenarios, the development of critical AI literacy, the formulation of ethical guidelines, and faculty training to utilize AI responsibly.
Digital-Based Work Environment to Improve the Performance of MSMES Employees in the City of Malang
Rapid changes in technology have led businesses to embrace digitalization, one example of which is the use of digitalization in the workplace. A digital-based work environment is a trend used by MSMEs today. The purpose of this study is to analyze the extent to which a digital-based work environment can provide employee performance improvements in MSMEs in Malang City. The method used is descriptive analysis and SLR. The results show that a digital-based work environment is more effective in MSMEs in Malang City, especially food and beverage MSMEs. With a completely digital environment ranging from attendance, performance measurement to salaries, it can encourage better employee performance. Key words: Work environment, employees, MSMEs, digitalization.
Attendance Information System for Interns at The Surakarta City Transportation Department
The attendance process for interns at the Surakarta City Transportation Department is still conducted manually, making it less effective, prone to recording errors, and difficult in terms of attendance data management. This study aims to design and develop a web-based internship attendance information system to improve the efficiency and accuracy of attendance recording. The research method employed is the Waterfall method, which consists of requirements analysis, system design, implementation, testing, and maintenance stages. The results indicate that the system was successfully developed according to user requirements, featuring multi-user login access for administrators, interns, and supervisors. The system is capable of automatically recording check-in and check-out attendance using facial recognition and location verification, while storing data in a structured database. Furthermore, the system facilitates internship participant management and enables the generation of attendance reports quickly and accurately. Based on Black Box Testing, all system functions operated as expected. Therefore, the system can enhance the effectiveness and efficiency of internship attendance management at the Surakarta City Transportation Department.
Comparison of TF-IDF and Sentence-Transformer NLP Methods for a Perfume Recommendation System Based on User Descriptions with Streamlit Visualization
The global perfume industry has grown considerably in recent years, yet helping consumers identify products that genuinely align with their personal taste remains a non-trivial problem, especially when preferences are communicated through unstructured, free-form natural language rather than standardized scent terminology. This study addresses that gap by evaluating and comparing two Natural Language Processing (NLP) text-representation methods, Term Frequency-Inverse Document Frequency (TF-IDF) and Sentence-Transformer, within a cross-lingual content-based filtering perfume recommendation system. The novelty lies in the cross-lingual setup, where unstructured Indonesian-language queries are matched directly against an English fragrance dataset of 42,115 records without any external translation module. A Streamlit web interface was deployed to collect data from 30 respondents, who submitted 180 graded relevance judgments for Top-3 recommendations evaluated through Precision@3 and Normalized Discounted Cumulative Gain (nDCG@3). System stability was assessed by partitioning the corpus into a training set of 33,692 records and a test set of 8,423 records. Sentence-Transformer, using the pre-trained paraphrase-multilingual-MiniLM-L12-v2 model, outperformed TF-IDF on all metrics, achieving a mean Precision@3 of 0.867 against 0.833 and a mean nDCG@3 of 0.912 against 0.850, with substantially lower score degradation across data partitions. These findings confirm that semantic embedding methods provide superior ranking quality and cross-lingual robustness, offering a scalable and translation-free solution applicable to multilingual product recommendation systems in commercial settings.
Enhancing SME Competitiveness through E-Commerce Adoption: A Framework for Malang City
Small and Medium-Sized Enterprises (SMEs) play a crucial role in economic development; however, enhancing their competitiveness in the digital era remains challenging, particularly in effectively leveraging e-commerce as a digital transformation strategy. Although prior studies have explored determinants and outcomes of e-commerce adoption, the findings remain fragmented and insufficient in explaining how e-commerce contributes to sustainable SME competitiveness. This study aims to identify internal and external factors influencing e-commerce adoption, examine its impact on SME competitiveness, and develop an integrated conceptual framework relevant to SMEs in Malang City. A Systematic Literature Review (SLR) was conducted following PRISMA guidelines, analyzing 33 empirical studies published between 2015 and 2025 from Scopus, ScienceDirect, Emerald, SpringerLink, Wiley, Taylor & Francis, and Google Scholar. The data were analyzed using thematic and content analysis to identify patterns and relationships across studies. The findings reveal that e-commerce adoption is driven by internal factors such as managerial capability, digital capability, innovation capability, and entrepreneurial orientation, as well as external factors including competitive pressure, customer demand, government support, and the digital ecosystem. Furthermore, e-commerce adoption enhances SME competitiveness through sales growth, profitability improvement, market expansion, operational efficiency, and sustainable competitive advantage. The study’s novelty lies in integrating the Resource-Based View (RBV), Dynamic Capability Theory (DCT), and Technology–Organization–Environment (TOE) framework into a unified model explaining how e-commerce translates into competitive advantage. The study provides both theoretical contributions to digital transformation literature and practical implications for strengthening SME competitiveness in Malang City through strategic e-commerce adoption.
Performance Evaluation of Embedding-Based and Keyword-Based Retrieval in Text Description-Based Hotel Recommendation
The massive volume of textual descriptions on hotel booking platforms makes it difficult for recommendation systems to accurately match user preferences. Traditional keyword-based retrieval methods, such as TF-IDF, often struggle to capture semantic relationships when relevant terms do not explicitly overlap. This study evaluates the performance of keyword-based (TF-IDF) and embedding-based (paraphrase-multilingual-MiniLM-L12-v2) retrieval approaches in a content-based hotel recommendation system using a small-scale dataset. The dataset consists of 30 unique Traveloka hotels in Yogyakarta collected from Kaggle, representing a resource-constrained experimental setting. Evaluation was conducted using a black-box approach with 10 dynamic synthetic queries and assessed through Precision@3 (P@3) and Mean Average Precision (MAP). The results indicate that MiniLM achieved higher retrieval effectiveness than TF-IDF, with a mean P@3 of 0.3667 and a mean MAP of 0.1378, compared with 0.3000 and 0.1333, respectively. These findings suggest that embedding-based retrieval is more effective in capturing semantic information, including synonym usage and implicit contextual relationships, within the evaluated dataset. Therefore, compact embedding models such as MiniLM may provide an alternative approach to traditional keyword-based retrieval methods for small-scale recommendation systems.
Thermal Performance of Living Walls for Passive Cooling in Contemporary Buildings
A passive cooling strategy such as living wall can be applied to reduce the microclimate’s temperature. Rumah Turi Surakarta is one of the contemporary hotels that applies living wall in its corridors, to create a cooler microclimate as a response of air temperature increment in Surakarta. This study aims to determine how the performance of the living wall as a passive cooling, by comparing air temperature reduction by living wall elements and sun shading elements. Observations were carried out to retrieve visual and measurement data, then the data were processed using quantitative descriptive methods and comparative analysis. The result showed that several factors that affect living wall’s performance as a passive cooling are orientation, the distance of the living walls to the corridor, the distance between plants, and the types of plants. Krokot Merah and Sirih Gading which are leafier and have a darker leaf color, are capable to reduce the temperature by 0.9°C, while Lili Paris which are have a fewer leaf and lighter leaf color are able to reduce by 0.2°C.
Augmented Reality Indoor Navigation Using Immersal SDK: Implementation in Ma Chung University
Spatial orientation within university buildings presents significant challenges for new students and visitors, particularly in campus environments with high architectural complexity. This study aims to develop and evaluate an Augmented Reality (AR)-based indoor navigation application to facilitate wayfinding in the Bhakti Persada Building, Ma Chung University. The application development utilized the Immersal Software Development Kit (SDK), which integrates Visual-Inertial Odometry (VIO) technology for spatial mapping and real-time position tracking. The application was designed with nine strategic destination points on the first floor of Bhakti Persada Building. Performance evaluation was conducted through two approaches: black box testing for system functionality validation and the System Usability Scale (SUS) to measure user acceptability. Test results demonstrated a functional accuracy rate of 93.33% based on established testing criteria. Usability evaluation yielded a SUS score of 77.75, indicating good acceptability levels and classifying the application as an acceptable system. This research successfully validated the effectiveness of AR technology implementation in addressing indoor navigation problems within university environments. These findings contribute to the development of technological solutions for enhancing user navigation experiences in complex interior spaces.
Automated Cyberattack Response System: A Combination of AI and Human Control with Recommendations for Measurable Actions
The growing frequency and complexity of cyberattacks have placed significant pressure on the security of digital infrastructure, particularly because manual incident handling tends to be slow and prone to delayed responses. This study aims to design and build an automated security incident response system that combines artificial intelligence with human oversight to improve both the speed and quality of response. The system was developed using the Waterfall method, integrating Wazuh as the network security monitoring platform, n8n as the workflow orchestration engine, and the Llama 3.1 8B language model accessed through the Groq API to generate mitigation recommendations in plain, easy-to-understand language. A human-in-the-loop approval mechanism was implemented through a Telegram bot, requiring analyst confirmation before any mitigation action is executed. The system was evaluated across three attack scenarios, SSH brute force, multiple failed login attempts, and suspicious file modification, each tested 15 times in a controlled virtual environment. The results show an average response time of 21.2, 34.1, and 36.3 seconds for each scenario respectively, far outperforming manual handling, which typically requires between 600 and 1,800 seconds. This translates into a response speed improvement of up to 98%, while the AI-generated recommendations remained fully consistent with the rule-based engine across all 45 trials conducted. These findings suggest that combining open-source SIEM, workflow automation, and LLM-based reasoning with human supervision offers a practical, low-cost, and reliable approach for strengthening incident response capability in resource-constrained environments.
Designing and Implementing COPRAS Decision Support System for Employee Performance Assessment
Employee performance evaluation remains a critical yet challenging process in organizations, particularly due to the persistence of subjectivity and inconsistent judgment across evaluators. In software house environments, where performance is influenced by both technical output and behavioral factors such as collaboration, communication, and initiative, the need for a structured and data-driven approach becomes increasingly important. This research aims to address these challenges by applying a multi-criteria decision-making approach to support employee performance assessment in a more systematic and transparent manner. The research adopts the Rapid Application Development (RAD) method to design and implement a decision support system, enabling iterative development and active user involvement. A case study was conducted in a software house company with approximately 80 employees across Sales, HRD, and IT departments. Performance evaluation was structured using five criteria, and the COPRAS method was applied to process the data, including normalization, weighting, and ranking of employees. Sensitivity to criteria weights was also considered to understand the robustness of the decision outcomes. The results show that the system successfully generates consistent and interpretable rankings, with clear differentiation between employees based on weighted performance indicators. The selected criteria were found to align well with the characteristics of software development work, supporting both technical and collaborative aspects of performance. Moreover, although the input data contains subjective elements, the use of a structured model allows the results to be objectively justified and transparently explained. Overall, the research demonstrates that integrating COPRAS into an information system can enhance fairness, consistency, and decision quality in employee performance evaluation, while bridging the gap between theoretical models and practical organizational needs
Design and Development of an Inventory Management System at Toko Rizky Grosir Using the SDLC Method
Toko Rizky Grosir is a daily essential goods retail store whose inventory management is still carried out manually by an owner who also holds other occupational responsibilities outside the store. This situation gives rise to several operational issues, including data recording errors, difficulty in remotely monitoring stock levels, delays in report generation, and the risk of stock shortages or overstocking. This study aims to design and develop a web-based inventory management system for Toko Rizky Grosir using the Software Development Life Cycle (SDLC) method with the Waterfall model. The development stages consist of requirements analysis, system design, implementation, testing, deployment, and maintenance. The system was built using PHP with the Laravel framework and a MySQL database, incorporating two levels of user access: Super Admin and Staff. The novelty of this research lies in the integration of ABC classification for stock categorization, FIFO-based item dispatch prioritized by expiration date, and automated notifications for low stock and items approaching expiry all within a single system specifically designed for a grocery store managed remotely. System testing was conducted using the Black Box Testing method in collaboration with the store owner and employees to verify all system functionalities. The test results indicate that all system features performed in accordance with the defined requirements, demonstrating the system's capability to improve operational efficiency, facilitate real-time stock monitoring, and reduce the risk of recording errors and financial losses due to expired goods.
Development of an AI-Based Digital Report Card Information System for Automated Student Progress Description Generation Using the Waterfall Method
The preparation of early childhood student report cards is still predominantly performed manually, resulting in time-consuming administrative processes, inconsistent narrative assessments, and increased teacher workload. Despite the growing adoption of educational information systems, limited studies have integrated Generative Artificial Intelligence (AI) to automate developmental narrative generation in early childhood education. This study aims to develop a web-based Digital Report Card Information System that integrates the Gemini API to automatically generate individualized developmental narratives based on teachers' assessment data. The system was developed using the Waterfall software development methodology, encompassing requirements analysis, system design, implementation, and testing. PHP and MySQL were used to develop the application, while the Gemini API generated narrative evaluations according to predefined developmental assessment indicators. The resulting system provides comprehensive functionalities, including student, teacher, and class management, developmental assessment, anecdotal records, principal approval, parent access, and automated digital report card generation. System implementation demonstrates that the proposed solution streamlines report preparation, facilitates assessment data management, and produces more consistent developmental narratives, thereby supporting academic administrative services at PAUD Terpadu Restu 2. These findings demonstrate the potential of integrating Generative AI into educational information systems to support digital transformation and improve assessment practices in early childhood education.
Implementation of Web-Based Financial Management System at Nizam Aluminium and Glass
Micro, Small, and Medium Enterprises (MSMEs) in the manufacturing sector often face efficiency constraints in financial management due to manual recording processes. Nizam Aluminium and Glass, a project-based manufacturing workshop, faces problems such as disorganized transaction records, a high risk of losing physical receipts, difficulties in monitoring outstanding customer receivables, and inaccurate project profit-loss analysis. This study aims to implement a web-based financial management system that integrates the Job Order Costing method with multi-role access separation (Owner and Admin) to digitize the workshop's operational workflow comprehensively. To construct the application, this research adopted the Waterfall methodology, progressing sequentially through needs identification, architectural design, coding via the Laravel framework, and functional evaluation. The results show that the system successfully separates the managerial role of the Owner in controlling the price database (Master HPP) and monitoring gross profit analysis, from the operational role of the Admin in recording orders, detailing material requirements, and managing customer receivables in real-time. This implementation is proven to centralize financial data, eliminate manual calculation errors, and present accurate profit margin visualizations for business owners.
Employee Performance Monitoring System Based on Assigment Data at PT. Tribintang Emas Mulia
Employee performance monitoring is an important process in improving work effectiveness and evaluating employee productivity within a company. However, conventional monitoring methods are often ineffective because task recording and reporting are still carried out manually, causing difficulties in supervision, evaluation, and performance reporting. This study aims to design and implement a web-based Employee Performance Monitoring System to assist companies in managing employee assignments and monitoring performance more efficiently. The research method used is the Waterfall method, which consists of requirement analysis, system design, implementation, testing, and maintenance stages. The system was developed using Laravel Framework, Filament, PHP, and MySQL database. The system provides features such as employee data management, division management, task assignment, task evidence upload, performance monitoring dashboards, and graphical reports of employee performance. System testing was conducted using Black Box Testing, and the results showed that all system functions operated properly according to user requirements. The implementation results indicate that the system can help companies monitor the number of assigned tasks, completed tasks, and task completion punctuality effectively. In addition, the system also provides performance visualization through charts and statistics, making it easier for management to evaluate employee performance and support decision-making processes within the company.
Web-Based Smartphone Recommendation System Using TF-IDF and Cosine Similarity Methods
The advancement of the digital era urges the use of smartphones as an essential instrument for society. However, the large variety of types and features actually triggers a dilemma for ordinary buyers who want to find a gadget according to their personal preferences. The average conventional search engine still relies on static filters that are less responsive to human language queries. Therefore, this study initiated a website-based gadget recommendation platform that adopts the Term Frequency-Inverse Document Frequency (TF-IDF) method combined with Cosine Similarity. This approach is executed so that the system can extract meaning from user-free text and calculate its proximity to the phone's specification database. With the development method (prototype), the system architecture is built using PHP, Laravel framework, and MySQL. The processed data is sourced from trusted sites in the 2024-2026 period. The output of this research is in the form of an intelligent application that is able to sort the most relevant products along with direct comparison facilities. The results of the Cosine Similarity calculation show that the system is able to provide recommendations precisely, as evidenced by testing 20 smartphone product data with the query "hp 6 million gaming" where the highest similarity value was calculated to reach a score of 0.381 on the Poco F7 product, which makes it the most accurate recommendation to support the final decision of consumers.
Design and Construction of a Website-Based Garment Production Information System
Garment is a specialist production in producing various types of clothing such as ready-to-wear clothing, sportswear, clothing accessories, etc. by utilizing information technology. As time goes by, there are now more and more companies operating in the garment sector and as technology advances, garment companies are now starting to intensively use a system in their production flow. The Garment Industry is a company that operates in the garment manufacturing sector. However, in its operation there are still many problems such as slow operation, less effective data management, manual reporting, missing range data and many more. Administrative activities in garments such as processing order data, order allocation and preparing reports still do not meet operational achievements. Because of this, an information system is needed which is expected to help garment companies solve the problems they face. The role of this information system is the right solution to deal with the problems faced by the company so that everything runs effectively and efficiently. The method that the author used in writing this final assignment was by observing the company premises, conducting interviews with people related to the company, and studying literature from several journals and guidelines for writing this final assignment. Thus, this system is expected to increase the productivity and service quality of garment companies, as well as make a positive contribution to their business growth. The system proposed by the author is web-based, built with a sequence of steps, namely problem identification, needs analysis, coding, design and testing.