SMATIKA: STIKI Informatika Jurnal is a journal published by Lembaga Penelitian & Pengabdian kepada Masyarakat (LPPM) of Sekolah Tinggi Informatika & Komputer Indonesia (STIKI) Malang. The scope of this journal in the field of Computer Science, Information Systems, and Information Management. SMATIKA journal published four times a year, in March, Juny, September and December with an ISSN (printed): 2087-0256 and ISSN (online): 2580-6939. SMATIKA has accredited Sinta in S4 and has had DOI 10.32664.
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Home Page SMATIKA Journal Volume 15 Number 02, Desember 2025
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A Comparative Analysis Of Javascript-Based Web Stacks in Software Construction Phase: MEAN, MERN and MEVN
The construction phase of a web application development generally involves a number of personnel with specific perspectives and expertise, including: backend developers, frontend developers, and mobile developers. Based on these different perspectives, the combination of technology architecture and programming languages (stack) used will vary. Javascript is one type of programming language that is compatible with various platforms and can be used to harmonize the programming architecture of the three different perspectives. There are three types of JavaScript-based tech stacks that have a large user base: Angular-based MEAN, React-based MERN, and Vue-based MEVN. Based on this situation, it is necessary to empirically analyze tech stack comparisons in the context of web application development activities. The indicators used in this comparative study include: LOC (lines of code), execution performance, function structure analysis (call stack), and memory usage efficiency. The comparative results show that the MERN stack, which is based on React, has a more efficient LOC than the other two stacks. Though the difference is not very noticeable, MERN stack also displays the most efficient level of memory use. The comparative results also demonstrate that, in comparison to the other stacks, the MEVN tech stack has the most effective function call structure.
Indoor Human Presence Detection System Using Histogram of Oriented Gradients Algorithm
This study aims to develop a web-based monitoring system utilizing computer vision and the Histogram of Oriented Gradients (HOG) algorithm to detect and count the number of people in a room. The research was motivated by the need for automated systems to replace manual methods, particularly during the COVID-19 pandemic, where contactless attendance tracking is critical. The HOG algorithm extracts visual features as image gradients representing human shapes, which are then classified using a machine learning model. The research methodology involved testing various camera configurations and angles, such as above door placement and room corners, with 80 and 60-degree camera angles. The system was built using Python, OpenCV for image processing, and Flask for web interface development. Data was collected through 200 trials, capturing live images with a camera. The results showed that the camera positioned above the door at an 80-degree angle achieved the highest detection accuracy at 66%, while other configurations showed reduced accuracy, averaging around 52%. The system also logs data, including time, detected human count, and captured images for further analysis. The findings highlight the importance of camera placement and angle in ensuring effective human detection. These results support the development of computer vision-based systems for practical applications such as crowd management, attendance counting, and public space monitoring. Future research is proposed to improve detection accuracy by integrating facial recognition technology and developing a more intuitive user interface. This study contributes substantially to improving the efficiency of automated systems for counting individuals in enclosed spaces, addressing various industrial and social needs.
Copyright (c) 2025 SMATIKA JURNAL : STIKI Informatika Jurnal
Improving User Experience and Information Delivery through Motion UI in a Single-Page Campus Website
This research aims to develop a campus introduction website interface for STIKI Malang by implementing Motion UI to enhance information delivery effectiveness and user experience. Currently, the STIKI website uses a multi-page structure that requires visitors to open sub-menus separately to access information, resulting in significant resource consumption and long loading times. By transforming the website structure into a single-page application (SPA) and integrating dynamic animation elements through Motion UI, it is expected to increase engagement and conversion rates. Qualitative analysis results show significant improvements in user engagement and information comprehension, with page loading times drastically reduced to an average of 2.6 seconds. Evaluation using the User Experience Questionnaire (UEQ) also demonstrates significant improvements in attractiveness, clarity, efficiency, and stimulation aspects. This research concludes that implementing Motion UI on STIKI's single-page website successfully enhances user experience, access speed, and information delivery effectiveness. The results of this research can serve as a reference for developing interface design strategies for other educational institution websites
Evaluation of User Experience of Yamaha R15 AR Tutorial Application Using User Experience Questionnaire (UEQ)
This study aims to evaluate the user experience (UX) of an Augmented Reality (AR) application designed as a tutorial medium for introducing components of the Yamaha R15 VVA motorcycle. The evaluation was conducted using the User Experience Questionnaire (UEQ) method, covering six aspects: attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty. The research sample consisted of 30 students who have taken or are currently taking the Human-Computer Interaction course at Universitas Bhineka Nusantara. The analysis results showed that the pragmatic quality had an average value of -0.092 and the hedonic quality 0.108, with an overall score of 0.008, categorized as neutral. The average standard deviation of 0.666 indicates a high level of agreement among respondents. Although the application met some visual and interactive aspects, weaknesses were found in navigation features, usage guidance, and audiovisual support. Reliability testing showed that the UEQ instrument is appropriate for use, with a Cronbach’s alpha value of 0.88 (pragmatic) and 0.77 (hedonic). These results recommend further development in usability aspects and supporting features to enhance the effectiveness of the AR-based technical learning application.
Virtual Reality Game of Sorghum for Food Resilience
Sorghum is a vital staple food crop widely consumed in Asia and Africa, ranking among the top five food crops globally after wheat, corn, rice, and barley. It is rich in carbohydrates and low in sugar, making it a suitable dietary option for individuals with diabetes. Sorghum can be cultivated on marginal or unproductive land; however, improper cultivation techniques may lead to sub-optimal yields or even crop failure. Survey findings indicate that public awareness and knowledge about sorghum cultivation in Indonesia remain limited, contributing to difficulties in effective planting and crop management. To address this issue, a simulation game utilizing virtual reality (VR) technology was developed to provide an interactive and immersive learning experience for sorghum cultivation. The Unity game engine was employed in the development process, incorporating freely available assets from various sources. The application was validated through expert interviews and user testing within the community. Post-testing results demonstrated a 31% increase in user knowledge regarding sorghum cultivation. These findings suggest that the VR-based game effectively enhances public understanding of the procedures involved in planting and maintaining sorghum crops.
Analysis of Build Time in Continuous Integration on Multi-Node Jenkins Using Caching Methods
In the era of modern software development, the speed and efficiency of application build processes have become critical factors in enhancing the productivity of development teams. Jenkins, as a popular CI/CD tool, can be utilized to perform distributed builds across multiple servers. However, long build times remain a significant challenge, especially for container-based applications that require numerous dependencies and compilation stages. This study proposes a method to optimize build time by leveraging caching mechanisms. The proposed method utilizes cache storage to save frequently used build artifacts, thereby reducing the time required for recompilation in subsequent builds. In this research, experiments were conducted to compare the build time of container-based applications before and after implementing the caching method. The results of this study indicate that applying caching techniques to container-based applications can improve build speed by approximately 43% to 76%. This finding demonstrates that caching is highly effective in enhancing build time efficiency within Jenkins’ multi-node architecture. Consequently, this optimization not only accelerates the build process but also reduces computational resource consumption, thereby supporting more efficient and cost-effective CI/CD practices.
Building RT/RW Net With Pointing Points Between Regions
The digital divide between urban and rural areas in Indonesia remains a significant challenge in the current digital era, with limited internet access in remote regions hindering economic, educational, and social progress. This research aims to develop a wireless LAN-based RT/RW Net system as a solution to enhance efficient and affordable internet access. The system utilizes point-to-point access between regions using specialized routers to overcome geographical and physical barriers, thereby enabling internet access in hard-to-reach areas. By leveraging WiFi 5 technology as a solution for better range and performance, along with ease of operation and affordable construction costs, the system is designed for efficiency. Device configuration is carried out using the built-in application of the TP-Link EAP 110 router, facilitating easier and more efficient management. The PPDIOO (Prepare, Plan, Design, Implement, Operate, Optimize) research methodology is chosen as the approach for developing the RT/RW Net network. The advantages of this method include structured and systematic design capabilities, greater flexibility in meeting design needs, and the ability to optimize the quality of the network once it is operational. This method can also analyze and build networks according to local geographical conditions. Expected outcomes include improved quality and reliability of the RT/RW Net network, provision of cheaper and more convenient internet access for communities, and contributions to a more equitable dissemination of information and communication technology across Indonesia, enabling communities to enjoy better access to information, broader educational opportunities, and enhanced economic prospects.
Design and Implementation of a Coin-Based WiFi System for Coffee Shops or Cafés
The need for fast, stable, and affordable internet access is increasing along with the increasing dependence of society on information technology, especially in small business environments such as coffee shops and cafes. However, the operational costs of internet services are still a major challenge for micro-business owners. This study aims to design and implement a coin-based WiFi system that is independent, cost-effective, and easy to operate. This system integrates a coin sensor, microcontroller, and Raspberry Pi to detect coin denominations (Rp500 and Rp1000), automatically converts them into WiFi access duration, and records transactions in a local SQLite-based database. The web-based interface is built using Flask for ease of system administration and management. The research methods include literature studies, field observations, user interviews, and technical testing of sensor accuracy and network performance. Evaluations are carried out on download/upload speeds, latency, jitter, and packet loss to assess connection quality. The test results show that the system is able to detect coins with high accuracy and provide stable internet services according to the payment duration. The advantages of this system lie in its independence that does not depend on third-party applications, as well as its ability to be implemented in environments with technological and budget constraints. This system has the potential to be a viable alternative solution to expand internet access in the informal sector and drive digital transformation at the grassroots level.
Implementation of the New Student Admission System at Bina Insani University
New student admission is a very important process in higher education that requires fast, accurate, and organized information. At Bina Insani University, this process was previously done manually and using WhatsApp messaging services directly by the admin, which caused delays in response, repeated questions, and difficulties in managing registration documents. The purpose of this research is to build a new student admission information system that can speed up the registration process, reduce admin workload, and centralize registration documents digitally. This research uses the Extreme Programming (XP) method with data collection techniques through observation, interviews, and literature studies. This system is implemented using CodeIgniter with MySQL database and integrates real-time notifications via WhatsApp and Email using RabbitMQ architecture as a message broker. The results of the system implementation show that automatic notifications can improve the efficiency of information services, reduce repetitive questions, and speed up the response and document distribution process. The system also facilitates the search for registration documents with Google Drive integration. In conclusion, this system makes a significant contribution in improving the quality of new student admission services at Bina Insani University.
Classification of Fake and Real using Vision Transformer and EfficientNet-B0 on Real and AI-generated Images
Advances in artificial intelligence (AI) technology have enabled the creation of synthetic images that resemble real images, posing challenges in detecting and classifying such images. This study aims to develop an EfficientNet-B0 and Vision Transformer (ViT) based classification model to distinguish between real images and images generated by generative AI. The data used consists of 30,401 original images from the MSCOCO 2017 dataset and 30,401 generative AI-generated images from the SyntheticEye AI-Generated Images Dataset on Kaggle. The results showed that the ViT model achieved 98% accuracy and EfficientNet-B0 achieved 96% accuracy in classifying the images. The conclusion of this research is that both models have great potential in detecting digital media manipulation, with ViT showing superior performance. The practical implication of this research is the development of more advanced technologies for detecting generative images, which can be used in various real applications such as digital security and media verification.
Transfer Learning Based CNN Model Optimization for Pneumonia Classification in Chest X-Ray Images
Pneumonia is a leading cause of child mortality worldwide, and its diagnosis often relies on chest X-ray interpretation, which is prone to human error. This study aims to optimize a Convolutional Neural Network (CNN) model based on transfer learning using the DenseNet-121 architecture for pneumonia classification in chest X-ray images. The model was trained on a Kaggle dataset consisting of two classes: Normal and Pneumonia. Preprocessing included class balancing and data augmentation. Five fine-tuning strategies were tested, ranging from training only the classifier to unfreezing the entire pretrained layers. Evaluation metrics included accuracy, precision, recall, F1-score, and ROC-AUC. Results showed that the strategy of unfreezing Block 3–4 yielded the best performance with 94.39% accuracy, 95.61% F1-score, and 98.04% ROC-AUC. This study demonstrates that selective fine-tuning strategies significantly improve classification performance compared to training only the classifier or the entire network.
Web-Based Cattle Feed Monitoring and Management System at PT XYZ Central Lampung
This research discusses the design and implementation of a web-based cattle feed monitoring and management system at PT XYZ Lampung Tengah. The main problem faced is the manual recording in cattle feed management, which causes inaccuracies in feed consumption data, incorrect cost calculations, and the risk of inventory shortages or excesses. The research uses the Rapid Application Development (RAD) method in system development, which consists of four phases: Requirements Planning, RAD Design Workshop, Implementation, and Maintenance and Evaluation. The developed system has features for managing user data, feed type data, feed weight recaps, as well as generating recap and stock reports. The implementation results show that the system successfully automated the feed inventory recording process with access rights distribution between admin and user, data visualization through stock and feed expenditure graphs, and the ability to generate organized reports. In making the final report on animal feed, the admin takes up to 7 days because it adjusts warehouse data with feed expenditure records. But with this Web-based monitoring and animal feed system, the admin can present the final report on the use of feed in real-time. This system helps improve operational efficiency and the accuracy of feed usage recording at PT XYZ Lampung Tengah.
Security Gap Analysis of the Sorong Ministry of Health Polytechnic Website Using the Penetration Testing Method
Currently, information technology is very necessary, in the digital era cybersecurity is one of the main factors for an institution to survive and be recognized for its credibility, including educational institutions, the Poltekkes Sorong Website is used as the main portal or media to disseminate academic information, interaction between students and the public, However, the existence of security gaps is something that allows cyber attacks to be carried out which can endanger data confidentiality. This study aims to analyze the security gaps in the Poltekkes Kemenkes Sorong website, the testing carried out using the penetration testing method which has several stages including collecting scanning information, vulnerability analysis. So that this study can provide guidance and practice for information system managers at Poltekkes Kemenkes Sorong to reduce the risk of cyber attacks and protect sensitive data held by the institution.
Classification of Pneumonia in X-Ray Images Using CNN ResNet50V2 with Transfer Learning
The utilization of technology to build models that can classify pneumonia medical images automatically is needed for early diagnosis. This study aims to implement a Convolutional Neural Network (CNN) model with ResNet50V2 architecture that has been proven to have high accuracy in medical image classification. The model adopts a deep and efficient residual architecture, which facilitates deeper training of the model without suffering from vanishing gradient problem. This study went through four main stages: pneumonia and normal X-ray image data collection, data pre-processing (including set division, transformation, and augmentation), modeling using CNN with hyperparameter tuning, and model evaluation. Evaluation was performed using accuracy, F1-score, and Confusion Matrix metrics. The CNN model with ResNet50V2 as the backbone achieved 97% accuracy, showing excellent performance in differentiating between pneumonia and normal despite a small amount of misclassification. Although this model showed impressive results, challenges such as potential misclassification in cases with unclear or ambiguous images remain. Compared to previous approaches, this model offers advantages in accuracy and processing efficiency thanks to the use of a deeper and more sophisticated ResNet50V2. These advantages are expected to improve the precision of automated diagnosis in future medical applications.
Sentiment Analysis of Indonesian Audio Transcription Results Using T5 (Text-to-Text Transfer Transformer)
In the digital era, sentiment analysis has become a vital tool for understanding public opinion, particularly from data derived from digital media such as videos. However, voice-based sentiment analysis in the Indonesian language remains uncommon. This research aims to develop the T5 model for sentiment analysis of Indonesian generated from speech using speech-to-text technology. The primary advantages of the T5 model lie in its ability to process lengthy texts, comprehend natural language context, and adapt training for specific tasks such as sentiment analysis. The research dataset was obtained from 20 YouTube videos, segmented into clips of a maximum duration of 15 seconds, resulting in a total of 300 sentences consisting of 150 positive sentiments and 150 negative sentiments. The generated text data was processed using the T5 model, which was specifically trained to detect positive and negative sentiments through the optimization of specific hyperparameters. The results demonstrated that the T5 model achieved an accuracy of 83%, with a precision of 0.85, a recall of 0.83, and an F-measure of 0.83 when tested on datasets different from the training data. This research indicates that the T5 model can be adapted for voice-based sentiment analysis in the Indonesian language with satisfactory results. These findings contribute to the development of voice-based sentiment analysis technology, which can be applied to opinion analysis or product reviews. In the future, improving the pre-processing stage and using more diverse datasets are expected to improve the overall performance of the model.
WordPress Application Satisfaction Level Sentiment Analysis Using K-Nearest Neighbor and Naive Bayes Methods
User satisfaction reflects emotions when comparing services received with expectations, so understanding user satisfaction is important for app development. This research aims to evaluate user satisfaction with WordPress apps on the Google Play Store and identify areas for improvement. Sentiment analysis with KNN and Naïve bayes algorithms as the method used to extract information from 5,000 user reviews downloaded from Google Play Store,. The results showed the majority of reviews had positive sentiments, with Naïve Bayes providing better results than KNN, achieving 88% accuracy, 89.45% precision, 88% recall, and 83% F1-Score on a 90:10 data split. The word cloud of positive reviews featured words such as “greatâ€, “goodâ€, “helpfulâ€, “appâ€, and “goodâ€, reflecting user satisfaction with the ease and benefits of the app, while negative reviews featured words such as “difficultâ€, “tryâ€, and “failâ€ indicating technical difficulties and user dissatisfaction. This study concludes that WordPress apps have provided a satisfactory experience for most users, but some technical areas need improvement. The results of this study will provide valuable information for app developers in efforts to improve service quality and the app's reputation
Aplikasi Augmented Reality Untuk Pengenalan Panca Indera Manusia
This study aims to design a maekerless Augmented Reality based application as a interactive learning media for the introduction of the five human senses for elementary school students. This application uses the Multimedia Development Life Cycle (MDLC) method because it is in accordance with the manufacturing stage. Features in This application displays 3D visualization of the organs of the five senses that can be manipulated by the user, complete with additional information in the form of text and audio. Feasibility testing conducted on elementary school students and teacher showed that the app had an excellent succes rate, with an average score of 98,1% based on a Likert Scale. This result shows that the application succesfully increasses student interest and effectively improves students understanding of the aterial of the five senses.
Application Types Of Drugs For Young Generation Based On Augmented Reality
Drugs are a serious threat to public health, especially the younger generation. Drug education has been carried out by the national narcotics agency but the reduction is not optimal, so a technology known as Augmented Reality (AR) is needed. The aim of research on educational applications on types of drugs for the young generation based on Augmented Reality is to make it easier for the young generation to understand about drugs and make users more interactive and interesting. This research was developed using the Multimedia Development Life Cycle research method. This method has six stages starting from the concept to the distribution results of the applications that have been created. From the research stages that have been carried out, the results of the Augmented Reality Education application on the types and side effects of drugs were obtained. This application still has limitations on Samsung Android devices. It doesn't support the Easy AR plugin. This application was created using the Markless Bassed Tracking method and uses black box testing with a very good category. This application can be used for education for the younger generation and the wider community.
Implementation of Internet of Thing to Automatically Monitor Water Filling and Usage
This research aims to address efficiency issues in household water management through the implementation of the Internet of Things (IoT) on an automated water reservoir system. The problem identified is the lack of efficient control and monitoring of water replenishment and usage, which often leads to wastage and mismatch with homeowners' needs. This research design adopts an IoT-based approach that enables real-time monitoring and remote control via a web application. The system is also equipped with sensors to detect pipe leaks and monitor water pressure. Analysis of the developed system shows that the device is able to provide accurate and responsive data regarding the condition of the water reservoir, and allows users to control water replenishment as needed. This finding shows a significant improvement in water usage efficiency, as well as reducing potential waste due to leaks and inaccuracies in filling the reservoir. The conclusion of this research is that the designed IoT system can be an effective solution for household water management, providing convenience and better control for users, and has the potential to be widely applied in water management at the home scale.
Mapping Literature and Research Trends on AI Applications in Journalism: A Bibliometric Review
An emerging field of interdisciplinary research that needs more focus is the application of AI in journalism. The bibliometric analysis of the most recent research on implementation in digital journalism is presented in this paper. From Scopus, publications from 2014 to 2023 were examined to determine subjects, performance, impact, and collaborations. The findings indicate a rise in yearly production, with over 88 publications released in 2023 attesting to heightened research activity. Additionally, more recent publications had a more significant citation effect, demonstrating their relevance today. The majority of the prolific writers are from America, China, and Spain. International collaborations are centered around the West, between the United States and China, and the United States and Korea. This offers a standard that will guide future research in this enormously promising field. For AI to be implemented in digital journalism in a responsible manner, under-represented groups must be more involved.
Simple Additive Weighting Method for Selection of Social Media in Digital Marketing for Culinary MSMEs in Banjarmasin City
Digital marketing has become very important because the world of marketing has changed through advances in information technology. Interactive and integrated marketing that allows market intermediaries, potential consumers and producers to interact with each other. Instagram, WhatsApp, Twitter, Facebook, Telegram, TikTok, YouTube, and Shopee are social media that are often used in digital marketing. In this research, the data used is Banjarmasin City Culinary UMKM data obtained through a questionnaire totaling 174 respondent data which was distributed to the Banjarmasin City Culinary UMKM group. Data obtained from decision support system calculations using the Simple Additive Weighting method shows that many social media that are popular in society may not be suitable for use as digital media for culinary marketing. The results of the Simple Additive Weighting research show that it can be used to help culinary MSMEs in Banjarmasin City in making decisions about the use of social media through social media ranking results. This decision is reviewed based on several criteria such as length of business, length of use of social media, income and age. The length of business is because the longer the business lasts, the more people will know it. The length of use of social media is because the longer people use social media, the more they understand how to use the features and benefits of the features on social media. The greater the income in the business, the faster the business will develop. If you are at a more ideal age for running a business, your business will develop quickly because you have creative ideas and broad insight into business. The results of the Simple Additive Weighting method research show that WhatsApp has an accuracy value of 0.92, while Telegram has an accuracy value of 0.715. The concrete impact of the results of this research is that social media can help increase sales and the Simple Additive Weighting method can be used as a decision maker in selecting social media as a marketing medium so that Culinary MSMEs do not make the wrong choice in using social media.
Employee Performance Assessment in the Field of Public Infrastructure and Facilities Handling Using the C4.5 Decision Tree Algorithm
One way that should be finished to decide representative execution is to decide the worth that has been gotten equitably founded on the discipline measures of participation, obligation regarding finishing work, and consistence with commitments and denials, utilizing the C4.5 choice tree calculation. The data studied was the Worker Performance Evaluation Form with a total of 108 workers, in 2023-2024 based on certain criteria with the data selected being 96 active workers. This data has several criteria, namely attendance discipline, responsibility for completing work, and compliance with obligations and prohibitions. The main aim of this writing is to determine employee performance from each criterion. The C4.5 decision tree algorithm can assist in the decision-making process regarding improving the performance and training of workers in the field of handling public infrastructure and facilities. You can see the results of the research that has been carried out as training data, the gain and entrophy values have been calculated. In the first partition, the highest gain value was obtained for Compliance with Obligations and Prohibitions with a value of 0.489943 and the smallest was Responsibility for Completion of Work with a value of 0.172824. This algorithm can be used to determine employee performance as a candidate for employee performance which will be determined by the relevant agency.
Design and Construction of an Environmental Monitoring System in a Cow Shed Based on the Internet of Things
Cows are livestock that are generally kept by the community, especially in rural areas. According to data from the Central Statistics Agency (BPS), in 2021 the beef cattle population reached 17,977,214, an increase compared to the previous year which was recorded at 17,440,393. Environmental factors in cow sheds can directly affect livestock, causing stress due to extreme temperatures, both hot and cold, resulting in decreased feed consumption and discomfort. High levels of ammonia gas from cow dung waste can affect cow resistance to disease and reduce cow productivity and can cause health problems for the surrounding community. This study aims to design an Internet of Things (IoT)-based cow shed environmental monitoring system. The method in this study uses several stages, namely data collection, needs analysis, design, planning and testing. The system created can monitor temperature, humidity and ammonia gas in the cow shed environment and display this information on a mobile application. In the mobile application, information from sensor values can be displayed in high, medium, and low categories during monitoring. The tool testing technique was carried out with 10 samples, the results showed that the temperature detector had an accuracy level of 91.13%, the humidity detector showed a value of 94.52% and the ammonia gas detector showed the highest value of 34.8 ppm at a distance of 10 cm and the smallest of 6.6 ppm at a distance of 100 cm. The results of this study indicate that the developed IoT system is effective in monitoring important parameters such as temperature, humidity, and ammonia gas in real-time. This can increase efficiency for farmers in monitoring environmental conditions in the cage, which was previously done manually.
Prototype of Weather Monitoring System and Early Rain Warning Based on Internet of Things
The condition of the air at a certain time and at a certain location over a short period of time is called weather. The term "time" refers to a mixture of meteorological factors that change over time. For example, the weather in the morning may be different from the afternoon and late hours. It is very important for humans to monitor, understand, and prepare for weather events. Weather information can be seen from weather information providers such as BMKG, but weather information on BMKG covers a wide area, so local areas such as villages have different weather even though they are in the same district. In addition, each weather information is presented in three-hour intervals and only covers a wide area, and there are no notifications in each area. Therefore, the purpose of this study is to create a prototype of a real-time weather monitoring system as well as an early warning of rain based on the internet of things (IOT) that can be accessed anywhere and anytime and the results are accurate and in accordance with environmental conditions, where the coverage is local areas such as villages so that there is no difference in weather information and early warning notifications. This research method uses the waterfall method with research stages carried out from data collection, needs analysis, design, creation of tools and program codes, and testing. This research produces weather information such as temperature, humidity, air pressure, wind speed, light conditions, and rain conditions, this research also produces weather notifications that can be used as early warnings of rain. The results of the study were also compared with data from BMKG, namely there was a significant difference between sensor values and notifications. This system can also be an alternative as a tool that can be used for weather monitoring and providing early warning notifications.
International Program Registration Application Development Using User Centered Design Method
This study focuses on designing and developing an international program registration application using the User-Centered Design (UCD) approach. The UCD method is implemented to create an optimized user interface and experience, prioritizing the needs of both local and international students. The application replaces the previously used Google Form-based system, which had limitations in data security, database management, and selection process integration. The development process follows UCD principles, including context of use identification, user and organizational needs analysis, high-fidelity prototype design, and evaluation using the System Usability Scale (SUS). The initial evaluation resulted in an SUS score of 65 (Marginal High), which improved to 72 (Acceptable) after a redesign. The application is developed using Dart for the frontend and Firebase for the backend, ensuring flexibility in feature expansion. This solution enhances registration efficiency, improves the user experience, and supports multilingual and cross-device accessibility. Ultimately, this research contributes to technological innovation in international program management while strengthening the institution’s competitiveness in global higher education.
Implementation of Wireguard as a Connection Using Mikrotik Routing
The integration of WireGuard and RouterOs mikrotik allows mikrotik users to easily create a secure and fast virtual private network using Virtual Private Network (VPN) for international networks that can provide many benefits, including security, privacy, unlimited access, and more efficient network management. The government has the right to monitor and take action if there is an indication of VPN misuse for illegal activities. WireGuard uses a combination of modern cryptography and network techniques to achieve high performance and strong security. In this study, researchers used the SDLC (Software / System Development life cycle) method where the method is quite detailed covering six stages, namely: planning (Planning), analysis (analysis), design (design), implementation (implementation), testing (testing), maintenance (maintenance). At the testing stage, there needs to be control and monitoring of the local network and packet los that will see changes in the IP address of the user, the aim is to maintain stability when using a Virtual Private Network (VPN).
Classification of Fiber Optic Cable Attenuation Quality Based on Termination Using K-Means Algorithm
This study aims to classify attenuation quality in fiber optic networks using the K-Means algorithm. The classification model is designed to group data based on the characteristics of network parameters collected from field measurements. This research also compares the performance of models built with all features and those using selected features. The evaluation uses two main metrics, Sum of Squared Errors (SSE) and Silhouette Coefficient, to assess the quality of the clustering results. Testing shows that the use of selected features produces better clusters, with an SSE of 91.75 and a Silhouette Coefficient of 0.5923, compared to using all features, which results in an SSE of 101.98 and a Silhouette Coefficient of 0.4977. These results indicate that selecting the right features can positively impact cluster quality, although it is not the sole determining factor. Overall, K-Means has been proven effective in grouping attenuation quality, making it useful for supporting efficient fiber optic network maintenance and monitoring.
Prediction of Employment Status of Vocational High School Graduates Using the Random Forest Algorithm: A Multifactor Analysis of Academic, Social, and Family Factors
This study aims to develop a prediction model for the employment status of senior high school (SMK) graduates in Indonesia using multifactor analysis involving academic performance, social environment, and society. This study uses a quantitative approach with the Random Forest algorithm to collect large amounts of data and provide specific predictions. The model predicts the employment status of SMK graduates by 76%, indicating good work performance. This study also found that significant community factors significantly affect the employment status of SMK graduates (36.5%), followed by social factors (35.2%) and academic factors (25.9%). This study encourages schools, parents, and the government to focus on holistic SMK education, such as collaboration between schools and industry, to improve the employment status of SMK graduates.
Development of Financial Management Information System Based IoT Integrated Using Waterfall Model
Financial management is a core subject of the study program that must be mastered by students of the Sharia Financial Management study program. This course presents material about financial management in theory. Based on the results of initial observations that have been made, Sharia Financial Management students have not even tried to directly practice financial management using an information system in managing finances. This happens because several existing financial management information systems are closed systems so students cannot access the system. Therefore, this study proposes a financial management information system with the support of IoT technology as a simulation or practice medium for Sharia Financial Management study program students. The proposed method in this study uses Waterfall model. Based on the average value of TAM analysis, it is 81.72%, where this value is included in the Very Good for use to strengthen the Financial Literacy of Sharia Financial Management students.