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INDONESIA
JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Published by Politeknik Negeri Batam
ISSN : -     EISSN : 25486861     DOI : 10.3087
Core Subject : Science,
Computer Science & IT
Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan reviewer.
Arjuna Subject : -
Articles 57 Documents
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Search results for , issue "Vol. 9 No. 3 (2025): June 2025" : 57 Documents clear
Sentiment Analysis on BRImo Application Reviews Using IndoBERT Simarmata, Asyer Aprinando Pratama; Sasongko, Theopilus Bayu
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.8162

Abstract

The advancement of information technology has significantly impacted various sectors, including digital banking. BRImo, a mobile banking application from Bank Rakyat Indonesia (BRI), has been widely used, generating numerous user reviews that reflect their experiences. This study applies IndoBERT, a transformer-based model specifically designed for the Indonesian language, to analyze sentiment in BRImo user reviews. IndoBERT excels in handling the unique characteristics of the Indonesian language, such as informal and mixed-language usage. The dataset was collected from Kaggle and processed through labeling, data balancing, and splitting into 80% training, 10% validation, and 10% testing data. The IndoBERT model was evaluated using a confusion matrix and achieved 90% accuracy, with F1-scores of 0.89 for negative, 0.91 for neutral, and 0.90 for positive sentiments. Sentiment analysis results indicate that a significant portion of negative reviews highlight issues related to login difficulties, transaction failures, and slow customer service response times. These insights can help BRI enhance application reliability and customer support efficiency. This study demonstrates that IndoBERT is effective in sentiment analysis for Indonesian text and can be utilized to enhance BRImo services by providing deeper insights into user feedback.
IoT-Based Smoking Violation Detection System Equipped with Object Detection Using YOLOv5s Algorithm Putri, Audina Amalia; Hermawan, Indra
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.8459

Abstract

Smoking is a common habit in Indonesia. The Indonesian government has implemented regulations on smoke-free areas, but violations of the smoke-free policy still often occur. Previous studies have developed smoking violation detection system based on the MQ sensor. However, the smoking violation detection system based only on the MQ sensor is less reliable because the detected gas could come from other sources. Therefore, this study discusses a smoking violation detection system that can automatically verify smoking violation activities using the MQ-7 sensor, MQ-135 sensor, and the YOLOv5s algorithm. The MQ-7 sensor that has been calibrated to detect CO in ppm units achieved an accuracy level of 89.84%. The MQ-135 sensor also has successfully detected ammonia and toluene in cigarette smoke in ppm units. The trained YOLOv5s algorithm achieved an average Precision of 91.9%, Recall 83.7%, F1-Score 87.6%, and mAP50 88.3%. The system is equipped with a speaker that will sound automatically after a verified smoking violation occurs and Telegram notifications in the form of text messages and images.
Utilization of EfficientNet-B0 to Identify Oncomelania Hupensis Lindoensis as a Schistosomiasis Host Lamadjido, Moh. Raihan Dirga Putra; Laila, Rahmah; Pusadan, Mohammad Yazdi; Yudhaswana, Yuri; Lapatta, Nouval Trezandy; Ngemba, Hajra Rasmita
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9058

Abstract

Schistosomiasis caused by the Schistosoma japonicum worm is a significant health problem in Indonesia, especially in endemic areas such as the Napu Plateau and Bada Plateau. The main problem in controlling this disease is the difficulty in rapid and accurate identification of Oncomelania hupensis lindoensis snails as intermediate hosts of the parasite. This research aims to develop an artificial intelligence-based system that can efficiently identify the snail species. The stages of this research include collecting snail image data from the Central Sulawesi Provincial Health Office, consisting of 2100 images covering seven snail species, then processed through preprocessing and augmentation stages. The model applied was EfficientNet-B0. The results showed that the EfficientNet-B0 model achieved 98.80% training accuracy and 98.33% validation accuracy. Confusion matrix testing showed good performance, with an accuracy of 98% and for the species Oncomelania hupensis lindoensis had a recall of 93%, precision of 100%, F1-score of 97%, and the resulting AUC value of 99.7%. This research successfully developed an efficient identification system, which is expected to help health surveillance personnel in accelerating the identification process of schistosomiasis intermediate hosts.
Intelligent Web-Based Application for Personalized Obesity Management Wijayakusuma, I Gusti Ngurah Lanang; Sudarma, Made; I Ketut Gede Darma Putra; Oka Sudana; Minho Jo
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9151

Abstract

Obesity is a serious global problem due to its association with various chronic diseases. This study explores the utilization of machine learning in particular deep learning technology to predict Body Mass Index (BMI) from individual photos to create an efficient solution for assessing obesity. Using the ResNet152 model and K-Fold Cross Validation, this application integrates filters on individual photos to improve prediction accuracy. The application was developed using React JS for the front end, PHP and MySQL for the backend and database management, and Python as the core of the machine learning system. The application that tested using blackbox method, to see all features is functioning and the web application prototipe is passed all the test scenario.
Augmented Reality Development for Creating Interactive Experiences in Tourism Places Pranata, Caraka Aji; Filza, Muhammad Fairul; Tanudidjaja, Miquel Jan
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9183

Abstract

Technology, hardware and software are developing rapidly as time goes by. One of the results of this rapid technological development is Augmented Reality (AR) technology. Current tools in augmented reality (AR) were offered by Vuforia Software Development Kit (SDK). However, with the rapid development of Unity Engine, now we can integrated OpenCV in Unity Engine. This integration presents ideas for the development of AR technology. This study uses an approach that uses research and development (R&D) methodology. The model that will be used is the utilization of the ADDIE development framework. We encountered three main problems, problems faced are "How many stages of implementing AR with mediapipe in Unity Engine?", “How people satisfaction while using this product?” and " What is the maximum distance and time required to conduct the interaction process?". From the research conducted, we found that there are four important AR development stages that must be carried using Unity Engine and OpenCV. Next for RQ2 we got a level of approval from users of 86.53% or strongly agree with what we are doing. Then for the last RQ, we got the results for optimal hand detection distance is 3 meters, and the speed with the fastest value is 0.098s.
Implementation of YOLO v11 for Image-Based Litter Detection and Classification in Environmental Management Efforts Ramadhani, Lingga Kurnia; Widyaningrum, Bajeng Nurul
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9213

Abstract

This research implements YOLO v11 for image-based waste detection and classification to improve waste management efficiency. The model recognizes four categories of waste: inorganic, organic, hazardous and residual. The training results showa mAP@0.5 of 0.989 and a maximum F1 of 0.98 at an optimal confidence level of 0.669. The model had high precision on the Organic (0.995) and B3 (0.991) classes, but faced difficulties in classifying the Residue category. The confusion matrix revealed most of the predictions were accurate, despite some misclassification. The model also showed stable performance under various lighting and background conditions. With this reliability, YOLO v11 can be applied in automated sorting systems to improve recycling efficiency and support sustainable environmental management, although further improvements to data augmentation and class weight adjustment are still needed.
Quality Analysis of the Registration Information System Website using ISO/IEC 9126 Standard Swari, Dw Ayu Agung Indra; Agustino, Dedy Panji; Wulandari, Ni Luh Komang Irma; Zalogo, Yohanna Vony Sora; Lau, Jessica
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9236

Abstract

The performance of registration information systems is a crucial factor in ensuring the efficiency and effectiveness of academic administrative services. This study evaluates the quality of a registration information system based on the ISO 9126 standard, focusing on key aspects such as functionality, reliability, usability, efficiency, maintainability, and portability. The data collection methods used in this study vary based on each quality aspect. For the usability and maintainability aspects, data was collected through a questionnaire distributed to 100 respondents, consisting of students, prospective students, and academic staff. For the efficiency aspect, the GTMetrix tool was used to evaluate website performance. The reliability aspect was tested using the WAPT application. The functionality aspect was assessed using black-box testing with a total of 10 participants consisting of 2 prospective students, 5 students, and 3 administrative staff members, while portability was evaluated by accessing the website on five different mobile devices with varying screen sizes, operating systems, and types. The evaluation results indicate that the system performs well in functionality, usability, portability, reliability and maintainability but requires significant improvements in efficiency, particularly in LCP optimization. Based on these findings, optimization strategies such as image compression, CSS and JavaScript minification, and server-side caching implementation are recommended.
Enhancing Web Security and Performance with Hybrid Stateless Authentication Mario, Benedictus; Wiradinata, Trianggoro; Christian, Christian
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9251

Abstract

Ensuring operational integrity across industries and protecting sensitive data require strong authentication systems. This paper presents a novel hybrid stateless authentication method that integrates binary payloads, token specifications, and database solutions. By employing a distinctive expiration policy, our proposed approach overcomes limitations inherent in traditional token revocation strategies while achieving token verification speeds that are up to 86 times faster than conventional statefull session-based methods. Overall, through uniformed benchmarking experiments and a comprehensive review of the literature substantiate the performance and security advantages of our method. Ultimately, this hybrid technique offers a more scalable and secure framework for authentication management, enabling efficient and flexible deployment in high-demand distributed environments.
Evaluation of the Effectiveness of Lightweight Encryption Algorithms on Data Performance and Security on IoT Devices Indrajati, Damar; Ashari, Wahid Miftahul
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9256

Abstract

Data security remains a major concern in the Internet of Things (IoT) landscape due to the inherent limitations in computational power, memory capacity, and energy availability of IoT devices. To address these challenges, lightweight encryption algorithms have emerged as alternatives to conventional cryptographic methods, aiming to balance performance and security. This study evaluates the effectiveness of five encryption algorithms—SIMON64/128, SPECK64/128, XTEA64/128, PRESENT64/128, and AES128—on IoT devices through experimental analysis of their security strength, execution time, CPU utilization, memory usage, and power efficiency. The experiments were conducted on a Raspberry Pi 3B+ using C-based implementations to emulate realistic IoT scenarios. The findings reveal that AES128 offers the strongest security characteristics, including the highest Avalanche Effect (39.29%) and Differential Resistance Score (6.76/10), but at the expense of significant resource consumption. In contrast, SIMON64/128 and SPECK64/128 deliver superior performance in terms of speed and resource efficiency, making them ideal for low-power environments, albeit with concerns about potential cryptographic backdoors. XTEA64/128 emerges as a practical compromise, delivering moderate security and low power consumption without known vulnerabilities. Based on these results, AES128 is suitable for high-capacity IoT platforms prioritizing strong encryption, while SIMON and SPECK are preferable for resource-constrained devices, with XTEA serving as a balanced alternative. This research contributes a comparative framework to guide the selection of encryption algorithms for IoT systems, ensuring an optimal trade-off between security and operational efficiency.
Evaluation of Scalability and Resilience of Hyperledger Fabric in Blockchain Implementation for Diploma Management Pebriyanti, Cahyani; Suranegara, Galura Muhammad
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9262

Abstract

This research aims to evaluate the performance of a Hyperledger Fabric-based blockchain system implemented for digital diploma management. The system is tested using the Caliper benchmark tool in various network and scalability scenarios, including normal conditions (baseline), network delay of 50ms, 100ms, 200ms, and 500ms; packet loss of 1%, 5%, 10%, and 15%; bandwidth limitation of 5 Mbps; high transaction load (scalability standard and scalability optimized); and extreme conditions in the form of Byzantine attacks with malicious nodes of 10%, 30%, and 50%. The evaluation was conducted using four key metrics: transaction success rate, failure rate, average transaction latency, and throughput (TPS). The system recorded high performance under normal network conditions with a success rate of 99.8%, latency of 0.89 seconds, and throughput of 9.7 TPS. Network disruptions such as delay, packet loss, and bandwidth limitation had only a minor impact, with the success rate remaining above 99% and latency gradually increasing. High load in the scalability scenario caused latency to increase to 27.21 seconds and failure rate to rise, but improved significantly after chaincode optimization. Meanwhile, the Byzantine scenario showed a drastic drop in performance with the success rate decreasing to 12.83% and the failure rate increasing to 87.17%. These results show that the Hyperledger Fabric-based digital diploma management system is resilient to common network disruptions and reliable at medium scale, but still requires strengthening the consensus mechanism to deal with extreme conditions and maintain reliability in environments that are not fully trusted.

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