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Journal of Computer Science and Informatics Engineering
Published by Ali Institute of Research and Publication
ISSN : -     EISSN : 28278356     DOI : -
Core Subject : Science,
Computer Science & IT
Artificial Intelligence Machine Learning Natural Language Processing Computer Vision Text Speech Text Mining Data mining Cryptography Data visualization Expert System Deep Learning Fuzzy Logic IoT and smart environments Neural Networks Pattern Recognition Image Processing Optimization Digital Signal Processing Networking Technology Web intelligence
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 125 Documents
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Testing and Evaluation of an IoT-Based Smart Irrigation System for Soil Moisture Monitoring Yahya Zakaria; Imam Husen Al Munawaroh; Siti Nurul Widyaningsih; Erwin Apriliyanto
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1492

Abstract

Manual plant watering often does not consider real-time soil moisture conditions, which can lead to inefficient water usage. This study presents a performance evaluation of an Internet of Things (IoT)-based smart irrigation system using ESP32 for soil moisture monitoring and both automatic and manual watering control. The system was developed by integrating a soil moisture sensor with an IoT platform to support remote monitoring. Experimental testing showed an average communication delay of 1.8 seconds and automatic irrigation activation based on soil moisture thresholds: 20 seconds under very dry conditions (≤20%), 15 seconds under dry conditions (21–40%), and 5–10 seconds under moist conditions (41–59%), with irrigation stopping under wet conditions (≥60%). These results indicate that the system can provide responsive and consistent real-time irrigation control. However, the testing was conducted on a limited scale and did not include long-term field validation, so further research is needed to evaluate scalability and conduct comparative performance analysis with other systems. Academically, this study contributes to the development of a performance evaluation model for IoT-based smart irrigation systems using an adaptive threshold approach.
Implementation of Reverse Engineering Techniques for Malware Risk Level Categorization Using Simple Additive Weighting Muhammad Firdaus Aldiansyah; Khaerul Ma'mur
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1520

Abstract

The rapid growth of Android devices has been accompanied by an increasing number of malware threats, particularly spyware that can steal sensitive user information. This study aims to classify the risk level of Android spyware using reverse engineering techniques, VirusTotal API integration, and the Simple Additive Weighting (SAW) method. Reverse engineering is performed to extract internal malware attributes such as the number of permissions and the category of dangerous permissions from APK files. In addition, external attributes are obtained through VirusTotal API integration, including the number of antivirus engines detecting the malware and the threat category. These attributes are then processed using the SAW method to generate preference values used for classifying spyware risk levels into low, medium, and high categories. The malware sample used in this study is AhMyth, which represents Android spyware. The results indicate that the developed system is capable of providing systematic spyware risk classification and presenting more informative risk information to users. This research is expected to improve user awareness of spyware threats and support the development of more informative malware detection systems
Fire Detection and Distance Measurement Based on Infrared Sensors and Internet of Things (IoT) Decky Ari Irwanto; Jaine Faleri Nona; Irawati Dewi Syahwir; Dewi Setiawati
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1657

Abstract

This research was motivated by the need for a fire detection system capable of detecting the presence of fire while providing real-time fire distance information that has the potential to be applied in automatic fire extinguishing systems. The result of this study is a prototype of a fire detection and distance measurement system based on the YG1006 infrared sensor integrated with the Internet of Things (IoT). The method used was an experimental approach through hardware and software design using ESP32, the HX711 module as a 24-bit Analog-to-Digital Converter (ADC), and transistor-based signal amplification. The results showed that the system was able to distinguish between the presence and absence of fire with an ADC threshold value of 1000 and measure fire distance up to 250 cm. The logarithmic regression model used had a coefficient of determination of 0.9949 with a maximum absolute error of 9% within the range of 60–250 cm. The system was also capable of real-time monitoring through Google Spreadsheet. The accuracy of fire distance measurement decreased when the fire was positioned very close to the sensor, specifically at distances less than 60 cm, due to sensor saturation.
Patient Visit Prediction Using the C5.0 Algorithm at Regina Maris Hospital Muhammad Sowban Adilla; Rakhmat Kurniawan R; Raissa Amanda Putri
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1670

Abstract

The increasing number of patient visits demands hospital readiness in providing facilities and supporting infrastructure for healthcare services, especially in planning drug needs and medical services. Inappropriate planning can lead to a mismatch between the number of patients and the availability of resources. Therefore, a patient visit prediction system is needed that can assist hospitals in decision-making. This study aims to predict patient visits at Regina Maris Hospital Medan to support service planning and improve patient satisfaction. The method used is data mining by applying the C5.0 algorithm as a classification method. Patient visit data is processed to produce a prediction model in the form of a decision tree and rules. The results show that the C5.0 algorithm is able to produce an accuracy rate of 71% in predicting patient visits. Thus, the system developed can be used as a recommendation tool for hospitals in preparing service needs, especially related to drug management and other supporting facilities.
Optimizing Heart Disease Prediction Using SMOTE, Decision Tree, and Random Forest: A Regional Analysis Approach Ryan Harrys Pratama; Ade Surya Budiman; Amin Nur Rais
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1675

Abstract

Heart disease remains the leading cause of mortality globally, including Indonesia. However, developing accurate predictive models is often hindered by class imbalance in medical datasets, where positive cases significantly outnumber negative cases. This study optimizes heart disease prediction by applying SMOTE (Synthetic Minority Oversampling Technique) regionally to Decision Tree and Random Forest algorithms using the "Heart Attack Prediction in Indonesia" dataset from Kaggle, which contains rural and urban attributes. Following the CRISP-DM framework, SMOTE was applied separately for each region to capture local distributional diversity and reduce regional bias. Results demonstrate that regional SMOTE significantly improved recall and F1-scores for both algorithms, particularly in rural areas where Random Forest recall increased from 60.50% to 70.34%. Statistical significance was confirmed through paired t-tests and Wilcoxon signed-rank tests on 5-fold cross-validation results (p < 0.001). Fairness analysis using Demographic Parity Difference and Equalized Odds Difference confirmed equitable performance across populations (DPD < 0.005, EOD < 0.008). Random Forest consistently outperformed Decision Tree, achieving the highest F1-score of 66.19% in urban regions post-SMOTE. These findings support that regional SMOTE effectively enhances model sensitivity toward minority classes while maintaining spatial fairness in heart disease prediction
Quality Evaluation of the IZAT Application Based on ISO 25010 an PLTU Tembilahan A. Rukib; Fitri Yunita; Bayu Rianto
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1692

Abstract

The Zero Accident Assistant (IZAT) application is a mobile-based system developed to support occupational safety management at PLTU Tembilahan, Indragiri Hilir Regency. The research gap identified in this study stems from the absence of systematic and standardized software quality evaluation for occupational safety applications in the power generation sector, particularly using the ISO 25010 standard. Although this application has been operationally deployed, no standardized quality testing has been conducted, making it difficult to systematically identify potential weaknesses. The novelty of this study lies in the comprehensive application of ISO 25010 combined with technical testing tools (OWASP ZAP and GTmetrix) in the industrial occupational safety domain — a methodological combination not previously found in the literature. This study aims to evaluate the quality of the IZAT Application using the ISO 25010 standard, covering eight quality characteristics: functional suitability, performance efficiency, usability, reliability, security, maintainability, portability, and compatibility. The method used is structured questionnaire-based testing and technical testing using automated tools. Respondents consisted of 35 active users selected through purposive sampling and 5 application developers. The results showed that the IZAT application achieved an overall average quality score of 84.76%, classified as "Good". The functional suitability characteristic obtained the highest score of 88.5%, while maintainability obtained the lowest score of 80.5%. The contributions of this study include: (1) an integrated ISO 25010 evaluation model for occupational safety applications in the energy industry; (2) a quality profile of the IZAT application as a baseline for future development; and (3) evidence-based improvement recommendations. This research provides quality improvement recommendations that can serve as a reference for developers for the next iteration.
An Intelligent Search Adaptation Mechanism For Improving Retrieval Efficiency In Structured And Unstructured Data Environments M. Abyan Nuha; Atha Harshavardhana; Dara Amalia Azzahrah; Bintan Kamila; Harun Ibrahim Abdallah Mohammad; Nukman Zadi; Imam Prayogo Pujiono
Journal of Computer Science and Informatics Engineering Vol 5 No 3 (2026): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i3.1732

Abstract

Although data retrieval is a fundamental task in any computational system, search algorithms are often used statically and ignore runtime dataset properties. This frequently results in wasted computing power in structured, semi-structured, and unstructured data environments. This study presents a lightweight dynamic search algorithm selection framework called the Intelligent Search Adaptation Mechanism (ISAM), which operates at runtime and uses the cardinality, sortedness, and uniformity of the dataset's value distribution as criteria for selecting the optimal search algorithm. ISAM is an adaptive dispatch mechanism for selecting intelligent algorithms, unlike traditional algorithms.ISAM is an intelligent algorithm selection unified dispatch mechanism. ISAM has been tested with synthetic data sets of 1,000 to 1,000,000 elements implemented in C++. For unsorted datasets, the overhead incurred by ISAM is negligible, and for sorted datasets, it can reduce query latency by up to 73.1× over a non-adaptive baseline of Sequential Search. In fact, the retrieval performance is found to be close to the theoretical complexity of the chosen search algorithm, through scalability analysis. The results show how intelligent runtime search orchestration works well in a heterogeneous data environment.
Development of an Integrated Web-Based School Information System at SMK Negeri 1 Lumban Julu Dhea Romantika Marpaung; Muhammad Syahputra; Rizky Fadillah; Sunario Megawan; Erlina Halim
Journal of Computer Science and Informatics Engineering Vol 5 No 3 (2026): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i3.1752

Abstract

Digital technology encourages schools to provide faster, more transparent, and more structured information and academic administration services. SMK Negeri 1 Lumban Julu did not yet have an integrated information system combining a public website and a role-based academic portal. This study aims to develop a web-based school information system to support school information delivery and academic data management. The system was developed using the Scrum method through requirements analysis, product backlog preparation, design, sprint implementation, and testing. The developed system provides a public website for school information, publications, departments, extracurricular activities, and tracer study, as well as an academic portal for staff, teachers, and students. Testing was conducted using blackbox testing by three prospective users, consisting of one staff member, one teacher, and one student. Testing covered 260 scenarios, consisting of 198 staff scenarios, 41 teacher scenarios, and 21 student scenarios. All scenarios were successfully executed, resulting in a functional success rate of 100%. These results indicate that the system can support integrated school information and academic data management.
RFID-Based Door Security System Performance Optimization Using Particle Swarm Optimization on the ESP32 Platform Hamdani Setiawan; Rahmad Hidayat; Paris Hasbi; Ike Yuni Wulandari; Yudi Herdiana
Journal of Computer Science and Informatics Engineering Vol 5 No 3 (2026): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i3.1758

Abstract

The development of the Internet of Things (IoT) has accelerated the adoption of RFID- and ESP32-based door security systems as more secure and flexible alternatives to conventional locks. However, previous studies have primarily focused on system implementation and functional testing without systematically optimizing RFID operational parameters, resulting in suboptimal reading performance and response time. This study aims to optimize the performance of an RFID-based door security system using the Particle Swarm Optimization (PSO) algorithm on the ESP32 platform. The proposed method includes prototype development, experimental evaluation under varying RFID reading distances and angles, and PSO-based optimization using a fitness function that integrates reading success rate, effective reading distance, and response time. The novelty of this study is integrating PSO to simultaneously optimize ESP32-based RFID parameters for improved authentication performance. Experimental results show that PSO increased the fitness value from 0.636 to 0.923, improved the RFID reading success rate from 60% to 95%, extended the effective reading distance from 4.2 cm to 4.8 cm, and reduced the response time from 0.59 s to 0.43 s. These findings demonstrate that PSO effectively improves the reliability, speed, and service quality of RFID-based access control systems in IoT environments
Evaluating the Usability and User Experience of an Augmented Reality Application for Kaba-Kaba Tourism Village, Tabanan, Bali Using SUS and UEQ I Made Dedi Suardika; Made Ratna Witari; Ni Made Asri Sasmita
Journal of Computer Science and Informatics Engineering Vol 5 No 3 (2026): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i3.1763

Abstract

This study explores the growing use of Augmented Reality (AR) in the tourism sector, while addressing the limited integration of usability and user experience evaluations in village based tourism applications. It presents an evaluation of the AR application for Kaba-Kaba Tourism Village as a medium for visualization and digital promotion. The evaluation was conducted using the System Usability Scale (SUS) and the User Experience Questionnaire (UEQ), involving 30 respondents representing typical AR technology users. The results indicate that the application achieved a SUS score of 63.58, which falls into the marginal acceptability category (grade D), suggesting that the system is usable but not yet optimal. Furthermore, the UEQ results show that the dimensions of Attractiveness (0.878), Stimulation (0.875), and Novelty (0.800) are rated positively, while Perspicuity (0.417), Efficiency (0.650), and Dependability (0.408) remain at a neutral level. These findings suggest that the application demonstrates strong hedonic quality, particularly in delivering engaging and innovative experiences, but still exhibits weaknesses in pragmatic quality aspects such as ease of use, efficiency, and system reliability. This study contributes by providing an empirical evaluation of AR implementation in village-based tourism and recommends an iterative user-centered design approach to improve usability and user experience in a sustainable manner

Page 11 of 13 | Total Record : 125

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