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Nurul Khairina
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INDONESIA
Journal of Computer Networks, Architecture and High Performance Computing
Published by Yayasan Cita Cendekiawan Al Khwarizmi
ISSN : 26559102     EISSN : 26559102     DOI : 10.47709
Core Subject : Science, Education,
Computer Science & IT Education
Journal of Computer Networks, Architecture and Performance Computing is a scientific journal that contains all the results of research by lecturers, researchers, especially in the fields of computer networks, computer architecture, computing. this journal is published by Information Technology and Science (ITScience) Research Institute, which is a joint research and lecturer organization and issued 2 (two) times a year in January and July. E-ISSN LIPI : 2655-9102 Aims and Scopes: Indonesia Cyber Defense Framework Next-Generation Networking Wireless Sensor Network Odor Source Localization, Swarm Robot Traffic Signal Control System Autonomous Telecommunication Networks Smart Cardio Device Smart Ultrasonography for Telehealth Monitoring System Swarm Quadcopter based on Semantic Ontology for Forest Surveillance Smart Home System based on Context Awareness Grid/High-Performance Computing to Support drug design processes involving Indonesian medical plants Cloud Computing for Distance Learning Internet of Thing (IoT) Cluster, Grid, peer-to-peer, GPU, multi/many-core, and cloud computing Quantum computing technologies and applications Large-scale workflow and virtualization technologies Blockchain Cybersecurity and cryptography Machine learning, deep learning, and artificial intelligence Autonomic computing; data management/distributed data systems Energy-efficient computing infrastructure Big data infrastructure, storage and computation management Advanced next-generation networking technologies Parallel and distributed computing, language, and algorithms Programming environments and tools, scheduling and load balancing Operation system support, I/O, memory issues Problem-solving, performance modeling/evaluation
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 795 Documents
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Design of an Arduino Based Automatic Sealing Machine with DS18B20 Sensor for Smart Temperature Control Dewi, Marysca Shintya; Marlinda, Linda; Komarudin, Komarudin
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6277

Abstract

Sealing quality is a critical concern for Micro, Small, and Medium Enterprises (MSMEs) that rely on conventional machines lacking temperature control mechanisms. These systems often result in overheating or poor bonding, especially when applied to thin plastic materials such as polyethylene (PE), polypropylene (PP), and oriented polypropylene (OPP), each with varying melting points. This research aims to design an Arduino Uno-based automatic horizontal sealing machine integrated with a DS18B20 temperature sensor to provide smart temperature control during the sealing process. The proposed system employs a threshold-based ON-OFF control algorithm with a hysteresis margin of ±2.5°C, and displays real-time thermal feedback on a 16x2 LCD. The experimental methodology includes temperature deviation analysis and quality scoring of sealing results across PE, PP, and OPP films. Results show that the manual system deviated up to 15.4°C from the target temperature, leading to inconsistent outcomes. In contrast, the Arduino-based system maintained thermal stability within ±5°C and achieved a significant increase in sealing quality score from 60 to 92. These improvements indicate enhanced operational reliability, safety, and sealing consistency. The system provides a low-cost, scalable solution for MSMEs and can be upgraded to include PID control, IoT integration, or adaptive thermal profiling. This work demonstrates that embedded microcontroller-based automation is feasible and effective for small-scale packaging applications
Design of Smart Parking System Using Ultrasonic Sensor to Optimize Parking Lots On Campus Lubis, Faisal; Sundawa, Bakti Viyata; Cholish, Cholish; Abdullah, Abdullah
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 2 (2025): Research Article, Volume 7 Issue 2 April, 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i2.6099

Abstract

Monitoring the availability of parking lots in the campus area is very important. This is related to the solution of the problem of limited parking spaces for four-wheeled vehicles. Existing parking spaces can be optimized by adding a vehicle detection device. This vehicle detection device uses ultrasonic sensors and its programming is based on the ESP32 Microcontroller. Sensitivity parameters measured are object detection distance, influence of other frequencies, influence of passing objects and range areas horizontally and vertically. In the research, the measurement results obtained are object detection distance up to 350 cm, the influence of other frequencies does not exist, passing objects can be detected by vehicle detection devices, range areas vertically up to 250 cm and horizontally up to 150 cm. Based on the test results, the distance reading by the ultrasonic sensor on the vehicle detection device is accurate. This measurement is in accordance with the specifications of the GH-311 type ultrasonic sensor used in the device.
Usability Evaluation of the Online Marriage Registration Feature in SIMKAH Dzatama, Krisna Fahrizal; Erna Daniati; Anita Sari Wardani
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6295

Abstract

The development of digital technology has encouraged government agencies to adopt online-based public services. One such system is SIMKAH (Marriage Management Information System), a web-based platform initiated by the Indonesian Ministry of Religious Affairs to simplify marriage registration processes at Kantor Urusan Agama (KUA). However, several usability challenges remain, particularly in its online registration feature. This study aims to evaluate the usability of SIMKAH using the Think Aloud method based on ISO 9241-11, focusing on effectiveness, efficiency, and satisfaction aspects. The study involved 10 participants, all prospective brides and grooms who had never used SIMKAH before. They were asked to complete 10 scenario-based tasks while verbalizing their thoughts. The results show a high effectiveness rate of 87%, indicating that users were generally able to complete tasks successfully. However, efficiency was affected by lengthy form fields and confusing file upload sections. Satisfaction received a score of 4.1 out of 5, reflecting a positive experience overall, although users noted a lack of clear guidance, feedback notifications, and mobile optimization. User feedback highlighted the need for interface improvements, such as simplifying form structures, adding real-time validation, implementing autosave features, and enhancing visual guidance. These findings suggest that while SIMKAH is functionally adequate, improvements in usability are crucial to ensure a more seamless and satisfying user experience in digital public services
Real-Time Data Integration and Weather Reporting Automation with Cloud Computing-based Interactive Spatial Dashboard for Extreme Weather Risk Analytics in Indonesia Arifani, Kahpi Baiquni; Pintarko, Dody; Sari, Anggraini Puspita; Agussalim, Agussalim
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6298

Abstract

Global climate change has increased the risk of extreme weather events in Indonesia, necessitating an accurate and real-time weather information system. This study develops a cloud computing-based system capable of integrating national weather data in real-time, automating the generation of actual and forecast weather reports, and presenting this information through an interactive spatial dashboard. The system is built on a client-server architecture deployed on Google Cloud Platform, utilizing the OpenWeatherMap API, a Flask backend, and a JavaScript-based frontend (Leaflet.js and Chart.js). Evaluation results indicate that the system can provide integrated national weather data with latency under one second, generate automated multi-province weather reports, and deliver interactive heatmap visualizations of extreme weather risks. This system is effective in improving the speed, accuracy, and efficiency of weather information distribution to support decision-making in the maritime, transportation, and disaster management sectors.
Integrated Cnn Based Facial Emotion Detection And Camera Based PPG Heart Rate Monitoring Panggabean, Erwin; Simanjorang, R. Mahdelena; Apriani , Wira; Nuraisana , Nuraisana; Sipahutar, Hartati Palentina; Siagian, Tesalonika Pesta
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6299

Abstract

Human emotion detection and heart rate estimation are two important aspects in developing a more responsive and adaptive human-computer interaction system. This study proposes a real-time video-based system that is able to detect facial emotions and estimate the user's heart rate simultaneously. The Convolutional Neural Network (CNN) method is used to classify facial expressions into several emotion categories such as happy, sad, angry, afraid, and neutral. Meanwhile, heart rate estimation is carried out using a non-contact Photoplethysmography (PPG) approach, which utilizes variations in color intensity in the user's facial area from video recordings to calculate the pulse rate. This system is developed using a standard webcam camera without additional medical devices, allowing for practical and economical implementation. The test results show that the system is able to recognize facial expressions with good accuracy, and estimate heart rate with an average error rate that is still within the tolerance limit of non-medical applications. By integrating computer vision technology and biometric signals, this study contributes to the development of a passive, real-time, and easily accessible emotion and health monitoring system.
Usability Evaluation of the SiCanTiK Website at SMKN 3 Kota Kediri Using the System Usability Scale and USE Questionnaire Lukman, Muhammad Abi; Daniati, Erna; Wardani, Anita Sari
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6315

Abstract

The rapid advancement of information technology has driven the transformation of learning systems, especially in vocational education. SMKN 3 Kota Kediri has developed an e-learning platform called SiCantik (Sistem Informasi Canggih Terintegrasi dan Kolaboratif) to support the online learning process. However, despite its potential, the platform faces several usability issues such as difficulties in navigating features and accessing learning content, which may hinder learning outcomes. This study aims to analyze the usability level of the SiCantik website using the System Usability Scale (SUS) and the USE Questionnaire. A descriptive quantitative method was employed, and data were collected from 100 respondents through online questionnaires. Validity and reliability testing were conducted to ensure the accuracy of the instruments. The SUS results showed an average score of 61.8, which falls into the “Poor” category, indicating that the platform's usability is marginally acceptable. Meanwhile, the USE Questionnaire results produced an average usability percentage of 65.5%, which is categorized as “Feasible.” Among the four evaluated dimensions, Ease of Use had the highest score (68.5%), while Ease of Learning had the lowest (63.2%). These results imply that while users generally find the system usable, improvements are still needed, particularly in user guidance and system intuitiveness. This research provides valuable input for system developers and stakeholders to improve the user experience of educational platforms. Further research is recommended to evaluate the technical performance and long-term user engagement of the system.
APPLICATION OF TRANSFORMER MODEL AND WORD EMBEDDING IN SENTIMENT ANALISYS OF INDONESIAN E-COMMERCE APPLICATION REVIEW Kadarsih, Kadarsih; Pujianto, Defi
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6354

Abstract

The rapid growth of e-commerce applications in Indonesia has resulted in a large volume of user reviews. The review contains important information that can be used to understand user satisfaction, complaints, and needs. Therefore, sentiment analysis of e-commerce app reviews is important to support future decision-making. This study aims to explore and compare the performance of the Transformer model and various word embedding methods in analyzing the sentiment of reviews of Indonesian e-commerce applications. The methods used involve extracting review data from the Google Play Store, text preprocessing, and text representation using Word2Vec, FastText, and IndoBERT. Next, this combination of embedding was tested using the Gradient Boosting Classifier as a prediction model. The evaluation was carried out by comparing the accuracy, precision, recall, F1-score, as well as the visualization of the confusion matrix and word cloud for each model. The results of the tests that have been carried out show that all three models have a fairly good ability to recognize positive reviews, with the highest accuracy score of 88% achieved by Word2Vec and FastText. While IndoBERT produces a lower accuracy value of 86%, IndoBERT shows a better balance in recall values and f1-scores for minority classes compared to Word2Vec and FastText. In conclusion, the application of the IndoBERT-based Transformer model is more effective in capturing the context and meaning of sentiment in Indonesian-language e-commerce reviews. These findings are expected to be a reference for the development of a more accurate sentiment analysis system for e-commerce applications in Indonesia.
Systematic Literature Review: Predicted Color Output in UI/UX Design Using Machine Learning Nurfadillah, Agita; Andarsyah, Roni
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6357

Abstract

An attractive user interface (UI) design is greatly influenced by the selection of appropriate colors, but the selection process tends to be subjective. To address this challenge, this study was conducted to identify commonly used machine learning techniques and evaluate their effectiveness in recommending colors based on RGB and HSL features. The method used was a Systematic Literature Review (SLR) of 39 articles published between 2020 and 2025. The study was conducted through three main stages, namely planning, implementation, and reporting. The review results show that approaches such as K-Means are widely used in the dominant color extraction stage, while classification algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), and Random Forest are applied for color prediction and recommendation. Random Forest is one of the models that shows superior performance, especially in terms of prediction stability and the ability to handle large numbers of variables. The model development process usually begins with color quantization, followed by data labeling and model training. Based on these findings, it can be concluded that Random Forest is a reliable model in color recommendation systems, especially when supported by good data preprocessing stages and proper parameter tuning.
Sentiment Analysis on Teacher Salary Policy in Indonesia 2025 Using Support Vector Machine: A Case Study on Instagram Data Zabni, Nur Hera; Furqan, Mhd.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6487

Abstract

The government's policy regarding salary increases for both civil servant (ASN) and non-civil servant (honorary) teachers in 2025 has generated various responses from the public, especially on social media. This issue has sparked public debate, with the emergence of both positive and negative comments, particularly on the Instagram platform. This study employs the Support Vector Machine (SVM) approach to classify public sentiment based on Instagram comments. A total of 1,500 comments were collected from the @folkative account during December 2024. The data were analyzed through several preprocessing stages (cleaning, case folding, tokenization, filtering, stopword removal, and stemming), followed by TF-IDF word weighting, normalization, and SVM model training and testing with an 80% training and 20% testing data split. The developed model demonstrated excellent performance, achieving an accuracy of 86%, precision of 87%, recall of 99%, and F1-score of 93%. These results indicate that the SVM algorithm is effective in classifying public opinion on government policies. This research also contributes to the advancement of machine learning applications in policy analysis based on public opinion, which can serve as valuable input for formulating more responsive policies.
RAD-Based Public Opinion Monitoring Information System for BSN Arianty, Kiki Puspo
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6497

Abstract

The growing influence of online media in shaping public opinion has driven government institutions to modernize their monitoring and communication systems. This study aims to develop a web-based information system for monitoring public opinion, tailored to the needs of the National Standardization Agency of Indonesia (BSN). Using the Rapid Application Development (RAD) approach, the system was built through a phased prototyping and user involvement to ensure functional relevance. The final system enables sentiment classification of news articles, centralized data storage, trend visualization, and automated news clipping. Evaluation results indicate improvements in monitoring speed, accuracy, and usability compared to previous manual methods. This study confirms the effectiveness of RAD in building practical digital tools for public sector communication and reputation management.

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