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Journal of Computer Science and Informatics Engineering
Published by Ali Institute of Research and Publication
ISSN : -     EISSN : 28278356     DOI : -
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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 10 Documents
 1 
Search results for , issue "Vol 4 No 3 (2025): July" : 10 Documents clear
Public Complaints Application at Binjai City Police Using the Waterfall Method to Improve the Performance of Binjai District Police Dimas, Dimas; Lubis, Aidil Halim
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1130

Abstract

The web-based public complaints application in Binjai City aims to improve the effectiveness and transparency of police services. The system allows the public to submit reports online, monitor the status of complaints, and communicate more efficiently with civil servants. With features such as real-time notifications, police database reporting, and integration, the app speeds up responses to symptoms and improves the accountability of the local police in Binjai. The use of this technology also reduces manual bureaucracy, speeds up case solutions, and increases public trust in the police. System testing shows that the app can optimize complaint workflows and provide more responsive solutions. Therefore, this app can be an innovative model in modernizing police services in the digital era.
Comparison of K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) Algorithms in Predicting Customer Satisfaction Pratama, Subhan Rizky; Fajri, Ika Nur
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1160

Abstract

This study compares the K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) algorithms in predicting customer satisfaction at Warung Makan Indomie (Warmindo). The research process consists of four stages, namely: data collection, data processing, model formation, and model evaluation. This study aims to compare the performance of two classification algorithms, namely K-Nearest Neighbor (KNN) and Support Vector Machine (SVM), in predicting customer satisfaction levels based on survey data. The evaluation was carried out using accuracy metrics and classification reports to determine the level of precision, recall, and f1-score of each algorithm. The evaluation results show that both algorithms have the same accuracy of 70%. KNN excels in f1-score in class 2 (0.70), while SVM excels in precision in class 2 (0.79). with an average score of both algorithms being 0.61. These results indicate that both KNN and SVM are feasible to use, depending on the performance priority per class
Comparison of Naïve Bayes and Dempster Shafer Algorithms for the Diagnosis of ARI Diseases Haikal, Baginda Fikri; Hasibuan, Muhammad Siddik; Rifki, Mhd Ikhsan
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1161

Abstract

Acute Respiratory Infection (ARI) has a high prevalence in Indonesia, but the manual diagnosis process faces challenges such as limited medical personnel and uncertainty in symptom analysis. This study developed and compared two AI methods, namely Naïve Bayes and Dempster-Shafer, in a web-based expert system to diagnose ARI. Symptom and disease data were collected from literature and experts, then implemented in a PHP and MySQL-based system. Naïve Bayes was used for probability-based classification, while Dempster-Shafer handled uncertainty. Testing was conducted on one case of ARI. Naïve Bayes produced a probability of 21.99% for Pneumonia, while Dempster-Shafer provided a combined probability of 61.6% for five diseases, including Colds, Acute Pharyngitis, and Epiglottitis. The results show that Naïve Bayes is suitable for consistent single diagnoses, while Dempster-Shafer is more appropriate for conditions with overlapping symptoms and uncertain data
Comparative Performance of IndoBERT and IndoLEM Baseline Models for Post-Disaster Health Information Extraction from Indonesian Online News Istiqomah, Nalar; Novika, Fanny
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1174

Abstract

Natural disasters often have significant impacts on public health, yet systematic monitoring of post-disaster diseases in Indonesia remains limited. This study compares the performance of two Named Entity Recognition (NER) models in extracting health impacts, affected locations, and disaster types from Indonesian-language online news articles. The first model is IndoBERT, fine-tuned using 1,137 manually validated disaster-related news articles. The second comprises baseline models from the IndoLEM benchmark, namely mBERT and XLM-RoBERTa, without domain-specific training. Evaluation results show that IndoBERT outperforms the baseline models, achieving 90.00% accuracy and an F1-score of 88.26%, compared to mBERT (72.93%) and XLM-R (76.44%). Further analysis of the extracted entities reveals spatial and temporal disease trends: floods in Java are consistently associated with diarrhea and skin diseases, while volcanic eruptions in eastern Indonesia are linked to respiratory infections and hypertension. These findings highlight the importance of selecting appropriate models to support data-driven public health monitoring systems in disaster-prone regions
Design of Web-Based Project Management System with Multi-Level Role-Based Access Control Zikra, Andi Anzanul; Darnilasari, Aulia; Yanuary, Rahmat; Sari, Komala
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1179

Abstract

Conventional project management using WhatsApp and email creates problems in progress tracking and inefficient team coordination. Research shows 70% of projects fail to deliver what was promised to customers. This research aims to design a web-based project management system using Laravel 12, Filament Shield, and Tailwind CSS. The research methodology employs waterfall SDLC with problem identification, data collection, UML system design, and black box testing stages. The system is designed with an Role-Based Access Control (RBAC) for 6 roles: Super Admin, Project Manager, Team Lead, Developer, QA Tester, and Client. Results demonstrate successful system implementation with integrated platform features, multi-level RBAC, real-time tracking through kanban dashboard, and responsive interface. Black box testing with 21 test cases covering 5 core system functions (authentication, RBAC, project CRUD operations, task management, and kanban board) achieved 100% success rate. The system successfully addresses progress tracking and coordination issues with an integrated solution supporting organizational scalability
Application of Monitoring Handy Talkie Usage as Support For Security Operation Based Android At Polda Gorontalo Harun, Rusni; Manurapon, Reynaldi; D. Paemo, Nuranissa; Ismail, Abdul Rahman
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1183

Abstract

Information Technology is developing rapidly and it has a significant impact on various aspects of life, including the government sector. The process of data collection that used Microsoft Excel software and paper filing have drawbacks such as difficult data collection, data loss due to natural factors, and it was difficulty in determining the condition of HTs. The purpose of this reseacrh was to designed an application of innovative monitoring HTs for security based Android. This application utilizes Android technology and HT devices to improve the effectiveness and coordination of security within the Information and Communication Technology Division of Regional Police in Gorontalo. The methodology of research used was Research and Development (R&D). The application was created using Java programming using Android Studio, PHP, and HTML. It allows Polda personnel to log in, view HT types and stock, borrow and return devices, and upload transaction receipts. The database used was MySQL. The modeling used Unified Modeling Language. This system utilizes whitebox and blackbox testing. As a sample, researchers tested the HT Borrowing flowchart, obtaining a region (R) value of 3, an Independent Path value of 3, and a Cyclometric Complexity (CC) value of 3. Test scenarios, including login, menu, HT type, and history displays, were successful, demonstrating that the system correctly authenticates users, manages HT data accurately, displays complete information, manages returns and validation appropriately, and handles usage securely
Beach Tourism Destination Recommendation System in Padang City Using the ROC-MOORA Method Feriantano Sundang Pranata; Yuke Permata Lisna; Retnaningtyas Susanti
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1216

Abstract

Padang City's tourism sector has great potential, but there is no data-based destination recommendation system for beach tourism. This study develops a recommendation system using the Rank Order Centroid (ROC) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) methods. The system evaluates 10 alternative beaches based on five criteria: entrance fees, safety, operating hours, facilities, and cleanliness. Criteria weights are determined objectively using ROC, while destination rankings are calculated using MOORA. The results show that destination A4 obtained the highest score (Yi = 0.3015). This system is proven to be able to provide objective recommendations and can be implemented in the form of a web application to support the decisions of tourists and destination managers. This study contributes to the integration of the ROC-MOORA method in the tourism domain based on decision support systems.
Sentiment Analysis of Triv Application Reviews using Support Vector Machine Algorithm Megawan, Sunario; Gohzali, Hernawati; Halim, Ferry; Ramadhan, Harry; Sitepu, Desy Okatvia
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1223

Abstract

The growing popularity of the Triv application as a cryptocurrency transaction platform in Indonesia has generated various user reviews that reflect perceptions of service quality. This study focuses on exploring user opinions through sentiment analysis techniques employing a classification approach based on the Support Vector Machine (SVM) algorithm. The data, sourced from user reviews on the Google Play Store, is analyzed through a series of systematic stages, including sentiment labeling, text preprocessing, feature extraction, model construction, and performance evaluation of the resulting classifier. The experimental results show that SVM can accurately identify sentiment polarity, achieving an accuracy rate of 96%. These findings highlight the potential of machine learning approaches in understanding user perceptions of digital financial applications.
Analysis of Shopee Adoption as a Medium for Tuition Payment at Universitas Mikroskil Using the UTAUT 3 Model Saragih, Yuni Marlina; Ginting, Tri Wulandari; Elly
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1229

Abstract

The development of technology and information is progressing rapidly, encompassing all aspects of life. One aspect that has developed from technological and information advances is education, for example, digital tuition payments. At Universitas Mikroskil, tuition payments can be made using an electronic payment system, namely through the Blibli website/app. Since September 29, 2022, Universitas Mikroskil announced the addition of a tuition payment application, namely the Shopee application. This electronic tuition payment is expected to make it easier for students to fulfill their responsibilities. However, no test has ever been conducted regarding student acceptance of the Shopee application, specifically for tuition payments. Therefore, the purpose of this study is to test student acceptance of the Shopee application for tuition payments using the UTAUT 3 model. The test was conducted using the PLS-SEM statistical analysis method with a total of 186 respondents. The results show that the personal innovation variable in IT has a positive and significant effect on utilization intention, the habit variable has a positive and significant effect on utilization intention, and a positive and significant effect on usage intention. The utilization intention variable has a positive and significant effect on usage intention. The results of this study are expected to help Universitas Mikroskil in making decisions on selecting a better tuition payment application.
NutriWise Mobile App Design for Daily Nutrition Recommendations Based on User Preference Mar’atullatifah, Yulaikha; Mahmudah, Himmatunnisak; Prasetyo, Deni; Fauzi, Muhammad Anwar; Tamtomo, Agatha Pricilia Sekar
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1236

Abstract

Nutritional imbalances caused by modern lifestyles and limited awareness of healthy eating remain widespread issues requiring technology-driven solutions. This study aims to design and evaluate a mobile application prototype, NutriWise, that provides daily meal recommendations tailored to users' nutritional needs and preferences. A User-Centered Design (UCD) approach was employed, involving users throughout the stages of requirement analysis, interface design, and initial prototype evaluation. The results indicate that the application is easy to use, delivers relevant meal suggestions, and supports nutritional monitoring through food logging and visual tracking features. These findings are supported by previous studies emphasizing the effectiveness of personalization and user-centered approaches. The study offers practical contributions to the development of adaptive digital solutions for daily nutrition management

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