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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 805 Documents
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Performance of Load Balancing Algorithms on Homogeneous and Heterogeneous Servers in On-Premise Environments Avia Aulia Faridah, Tsabitah; Suranegara, Galura Muhammad
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11614

Abstract

This research evaluates the performance of Round Robin, IP Hash, and Random Allocation algorithms in a homogeneous server environment, as well as Least Response Time, Least Connection, and Weighted Least Connection algorithms in a heterogeneous server environment implemented on on-premise servers. This study was motivated by the need to improve traffic management efficiency in local server infrastructure, where system performance is greatly influenced by resource diversity and distribution strategies. The experimental method was applied using NGINX and NGINX Plus as load balancing platforms, with Apache JMeter as a testing tool with low, medium, and high load test scenarios, while Netdata monitored the load distribution in real-time. Performance evaluation was based on six key metrics: throughput, latency, error rate, load distribution, CPU usage, and memory consumption. The results show that in a homogeneous environment, static algorithms such as Round Robin, IP Hash, and Random Allocation maintain stable performance with consistent throughput and minimal latency. Conversely, in a heterogeneous environment, dynamic algorithms, such as Weighted Least Connection, achieve lower latency and more balanced resource utilization. These findings highlight that algorithm selection must match system characteristics: static algorithms are more suitable for small-scale, uniform deployments, while dynamic approaches are recommended for heterogeneous or large-scale systems that require adaptive load management. Overall, weight-based dynamic approaches demonstrate superior scalability and resilience under high workloads.
Assessing Academic Website Quality Using the WebQual 4.0 Framework Pakpahan, Jonathan; Meiriza, Allsela; Novianti, Hardini
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11661

Abstract

The rapid growth of digital technologies in higher education has encouraged universities to improve academic service delivery through integrated online platforms. This study aims to measure the quality of the E-PPT (Pusat Pelayanan Terpadu Berbasis Elektronik) website of the Faculty of Computer Science, Universitas Sriwijaya, using the WebQual 4.0 model. A quantitative descriptive method was adopted, involving 354 valid respondents drawn from a total faculty population of 3,058 students across four academic levels (Diploma, Undergraduate, Master’s, and Doctoral). Data were collected via an online survey and analyzed using Microsoft Excel and SPSS. The website achieved an overall mean score of 3.60, indicating a good level of quality. Information Quality showed the highest performance (3.68), followed by Usability (3.58) and Service Interaction Quality (3.56). A supplementary correlation analysis also confirmed positive associations among the WebQual dimensions and overall website quality. These results suggest that the website delivers accurate information and is easy to use, although improvements are needed in responsiveness and interaction quality.
A SEIR Metapopulation Model for Mpox Transmission Dynamics in the DRC Peter, Kasende Mundeke; MATONDO MANANGA, Herman; Lea Irène, Milolo Kanumuambidi; Patience, Pokuaa Gambrah
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11668

Abstract

Understanding the mechanisms of infectious disease spread is a fundamental prerequisite for any control, management, or eradication strategy. This understanding relies on the rigorous integration of biological knowledge, mathematical tools, and computational resources, which enable in-depth analysis, the formulation of approximate numerical solutions, and the simulation of the temporal evolution of the pathological phenomenon. In this study, we develop an SEIR-type compartmental model to represent the transmission dynamics of Mpox, taking into account a metapopulation structure between two interconnected geographical areas, designated as patches 1 and 2. This model allows us to integrate the effects of interregional mobility on the spread of infection. The SageMath environment (version 9.3) was used to simulate viral dynamics within each patch, incorporating migration flows between the two regions. The system equilibria were determined and adjusted based on available data. The analysis focused on calculating the basic reproduction number, studying the stability of equilibria, and evaluating parameter sensitivity. The results suggest a gradual extinction of the disease in both patches, under certain conditions relating to mobility and recovery rates. Finally, this investigation highlights the relevance of SageMath software as a powerful tool for exploring and simulating spatially structured epidemiological models, with the ability to adapt to a variety of contexts and pathologies.
Optimization of Support Vector Machine Model Performance in Image Classification through Dimension Reduction with Principal Component Analysis (PCA) Ferdian, Zahfar Aziz; Sutopo, Joko
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11675

Abstract

This study examines how to optimize a Support Vector Machine (SVM) model using a dimensionality reduction method called Principal Component Analysis (PCA) to classify images with multiple dimensions. The dataset used is Chessman images with an initial number of features of 12,288. PCA was applied with the aim of retaining 99% of the total variation, resulting in 312 principal components. The results show a significant improvement in computational efficiency: training time was drastically reduced from 29.85 seconds to just 0.17 seconds (168 times faster), and memory usage decreased from 25.83 MB to 0.66 MB (97% more efficient). Although the accuracy experienced a small decrease, namely from 31.58% to 31.22%, PCA still functions as a noise filter that helps improve performance, especially in classes with complex visual patterns, such as an increase in the F1-score of the "Rook" class from 0.32 to 0.37. The conclusions of this study indicate that PCA provides important efficiency improvements without significantly sacrificing classification performance.
Evaluation of YOLOv8 and Faster R-CNN for Image-Based Food Detection Hananta, Julian Kiyosaki; Cahyono, Nuri
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11684

Abstract

Difficulties in manually tracking nutrition lead to the need for automatic food detection systems. However, Indonesian food presents tough challenges to recognize because similar-looking foods and different serving styles make it hard. This study looks at two deep learning models that follow different approaches: YOLOv8, which is known for being fast and efficient, and Faster R-CNN, which is known for being very accurate. The goal is to find the best model for use on mobile devices. This research uses a strict and standardized way to test the models to make sure the comparison is fair. A public dataset with 1,325 images from Roboflow was used. To deal with uneven class distribution, the images were split using Stratified Random Sampling. Before training, the images were resized using letterbox method to keep their original shape and normalized for pixel values. Both models were trained for the same number of epochs (100) and used the same optimizer (SGD) to ensure fair comparisons. The results show that YOLOv8 performs better in all areas. It achieved 88.6% mAP@50 accuracy and 62.0% mAP@50-95 precision. Faster R-CNN got 85.5% and 55.6% respectively. YOLOv8 also excels in sensitivity or Recall, reaching 87.7% compared to 61.7% for Faster R-CNN. The F1-Score, which balances accuracy and sensitivity, is 84.0% for YOLOv8 and 72% for Faster R-CNN. In terms of speed and size, YOLOv8 is much better. It runs in 13.5 ms and is 21.5 MB in size. That makes it 7.7 times faster and 7.3 times smaller than Faster R-CNN. Based on these results, YOLOv8 is the best choice for developing mobile-based nutrition tracking systems.
IoT Application Development for Marine Debris Management in 3T Islands: Supporting a Circular Economy and Community Empowerment Hernando, Luki; Lawi, Ansarullah; Dermawan, Aulia Agung; Aritonang, Mhd Adi Setiawan; Ad, Roni; Kurniawan, Dwi Ely; Manurung, Putriana Carona; Putri, Intan Medisi
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11699

Abstract

Marine debris is a serious problem, especially in the outermost, foremost, and least developed (3T) islands of Indonesia, where limited infrastructure and low public awareness are the main obstacles to effective waste management. This study aims to design, develop, and evaluate an Internet of Things (IoT)-based application integrated with a community-based web platform to support circular economy practices and community empowerment in marine debris management. The research method used is Research and Development (R&D) adapted from Borg & Gall, starting from the needs analysis stage to dissemination. An IoT module equipped with ultrasonic and GPS sensors is used to detect container capacity and location in real-time. Performance testing results show a response time of 1.8 seconds, a data transmission success rate of 98.7%, and a capacity detection accuracy of 96.2%, which meets the established technical standards. User acceptance testing using the Technology Acceptance Model (TAM) involving 15 respondents resulted in an average Perceived Usefulness (PU) score of 4.40 and Perceived Ease of Use (PEOU) of 4.23. Pearson's correlation analysis showed an r value of 0.84 (p = 0.0001), indicating a very strong and significant positive relationship between ease of use and perceived usefulness. This finding confirms that the developed system is technically reliable, easy to use, and capable of promoting environmental sustainability and economic opportunities in the 3T island communities.
Unveiling the Blockchain Intention-Behavior Gap Among Young Developers Suwarno, Suwarno; Yoprisyanto, Josua; Aklani, Syaeful Anas
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11702

Abstract

This study assesses the factors influencing blockchain technology acceptance among young developers in Batam, Indonesia, with a specific focus on comparing two distinct behaviors: using blockchain-based applications and engaging in blockchain development. Data were collected through a survey of 215 young developers and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The main outcomes reveal two fundamentally different adoption pathways. The intention to use blockchain applications is primarily driven by personal engagement and social influence, reflecting a "hype-driven" interest, and this intention strongly translates into actual usage behavior. Conversely, the model demonstrates a complete failure to explain development behavior, revealing a significant intention-behavior gap where the intention to develop shows no significant effect on actual development activities. The study concludes that for this demographic, hype-driven interest is sufficient for superficial application adoption but wholly inadequate for fostering development capabilities. Substantive adoption requires more than social trends; therefore, industry and educational focus should shift from promoting hype to enhancing technical literacy and demonstrating tangible use cases to bridge the gap from interest to competence.
IoT-Based Water Quality Monitoring and Control System for Koi Fish Ponds Adriansyah, Agil Yafi; Ningrum, Novita Kurnia
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11715

Abstract

Koi fish (Cyprinus rubrofuscus) require stable water quality to support their health and growth, yet conventional pond water management is generally performed manually and tends to be inefficient and inconsistent. This study aims to design and implement an Internet of Things (IoT)-based water quality monitoring and control system for koi fish ponds. The proposed system integrates an ESP32 microcontroller with pH, turbidity, ultrasonic, and water level sensors to monitor pond conditions in real time and support controlled water drainage and refilling through a web-based interface. Sensor data are transmitted to Firebase Cloud, enabling remote monitoring and control via an internet connection. System testing was conducted on four koi ponds with ten measurements for each parameter, resulting in forty data samples per parameter. The experimental results show that the sensors provide stable measurements with average error values below 3%, and the system demonstrates a response time of approximately 1–2 seconds under stable network conditions. These results indicate that the developed system is capable of supporting effective water quality monitoring and control while reducing reliance on continuous manual supervision in koi pond management.
Comparative Analysis of IndoBERT and Classic Machine Learning Models for Sentiment Classification of Education Policy on Social Media X Medantoro, Gabriella Fani Suciarti; Muljono, Muljono
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11723

Abstract

Leadership changes provide an opportunity for new education policies, generating complex public opinions on social media X that often contain implicit sentiments like satire, making automated analysis challenging. This study aims to address this challenge by conducting a comparative analysis to evaluate the effectiveness of the IndoBERT model in capturing nuanced, implicit sentiments compared to traditional machine learning classifiers (SVM, Naïve Bayes, Logistic Regression, KNN, and Random Forest). This research utilized a dataset of Indonesian-language tweets, collected via crawling. Data was pre-processed (cleaning, case folding, etc.) and labeled (positive/negative) using a hybrid Lexicon-LLM approach. The TF-IDF technique was used for feature extraction for the machine learning models, while IndoBERT used its internal tokenization. Models were evaluated using accuracy, precision, recall, and F1-score. The results showed that the IndoBERT model performed best with an accuracy score of 97%, significantly outperforming the other best machine learning models, namely Random Forest 95% and SVM 95%. This study concludes that the IndoBERT model is a superior and more robust solution for analyzing nuanced public sentiment on educational policies, demonstrating a greater ability to understand complex context and implicit language compared to traditional TF-IDF-based methods.
Improvement of User Experience Evaluation For SMEs Digital Application Using TRI, TAM, SUS Integration Ismanto, Ivan; Gamayanto, Indra; Sanyoto, Gabriello Klavin
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11736

Abstract

Micro, Small, and Medium Enterprises (MSMEs) in the service sector, particularly vehicle wash services, continue to face challenges related to queue management, service transparency, and operational efficiency, which negatively affect user experience. This study aims to develop and evaluate a mobile-based service booking and management application prototype by integrating the Design Science Research (DSR) approach with the Technology Readiness Index (TRI), Technology Acceptance Model (TAM), and System Usability Scale (SUS) as an evaluation framework. The artifact was developed through DSR stages, including problem identification, design, demonstration, and evaluation. Qualitative data were collected through interviews with MSME owners, employees, and customers and analyzed using Thematic Analysis. Quantitative evaluation involved 106 respondents to measure technology readiness, user acceptance, and usability quality, accompanied by a descriptive analysis of relationships among the constructs. The results indicate a high level of technology readiness (TRI = 3.53) and very strong user acceptance (TAM = 4.27). However, the usability score falls within the marginal acceptable category (SUS = 62.95), indicating a gap between conceptual acceptance and actual interaction quality. These findings demonstrate that integrating TRI–TAM–SUS within the DSR framework effectively identifies critical contradictions that can serve as a basis for refining UI/UX design and implementation strategies for digital applications in service-based MSMEs.

Page 72 of 81 | Total Record : 805

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