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All Journal Edutech MEDIA EKONOMI & TEKNOLOGI INFORMASI Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik JSI: Jurnal Sistem Informasi (E-Journal) CommIT (Communication & Information Technology) Jurnal Penelitian Ekonomi dan Bisnis Jurnal Manajemen Atma Jaya JAIS (Journal of Applied Intelligent System) Journal of Animation & Games Studies Binus Business Review Journal of Information System JADECS (Journal of Art, Design, Art Education and Culture Studies) SISFOTENIKA International Journal Ihya' 'Ulum al-Din CogITo Smart Journal Indonesian Journal of Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) Jurnal Telematika Adimas : Jurnal Pengabdian Kepada Masyarakat ComTech: Computer, Mathematics and Engineering Applications CSRID (Computer Science Research and Its Development Journal) JE (Journal of Empowerment) Jurnal Audience Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Layanan Masyarakat (Journal of Public Service) IJISTECH Jurnal Litbang Kota Pekalongan Media Jurnal Informatika J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Manajemen Jurnal Pengabdian Masyarakat Information Technology (JPM ITech) MANGGALI JGGAG (Journal of Games, Game Art, and Gamification)
Indra Gamayanto
Universitas Dian Nuswantoro
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
Optimizing Customer Loyalty Through The Information System Customer Approach at Harapan Hospitals Angelia Dwi Ceissa; Gamayanto, Indra; Wibowo, Sasono
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9202

Abstract

This research aims to optimize hospitals customer loyalty through a Customer Relationship Management (CRM) approach. In the increasingly competitive healthcare industry, customer satisfaction is key to retaining and attracting new customers. SERVQUAL is one of the methods we use in this study so that by implementing CRM, hospitals can understand patient needs, improve service quality, and build long-term relationships. This study uses a quantitative approach with a survey method of 106 respondents who are hospital customers. The results of the analysis show that the implementation of CRM has a significant effect on patient satisfaction and loyalty. Although the overall satisfaction rate reached 84.9%, several aspects needed to be improved, such as the waiting time of doctors and the speed of the registration process. Recommendations to improve the effectiveness of CRM in hospitals include the development of digital systems and staff training.
Comparing Decision Tree and Support Vector Machines in Hospital Satisfaction Anggraini, Dinda; Gamayanto, Indra; Wibowo, Sasono
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9203

Abstract

Patient satisfaction is a key indicator of hospital service quality. This study compares the performance of Decision Tree and Support Vector Machine (SVM) in classifying patient satisfaction at Harapan Hospital Magelang for service optimization. The dataset, derived from a 2024 survey, consists of 577 samples and 13 predictor variables, covering patient demographics and medical service aspects. Preprocessing includes data cleaning, normalization, encoding, and class balancing using SMOTE. The Decision Tree is applied with gini impurity and max_depth=11, while SVM uses the RBF kernel (C=100, gamma=0.01). Model evaluation metrics include accuracy, precision, recall, F1-score, and ROC-AUC.Results show that Decision Tree outperforms SVM, achieving 86% accuracy vs. 81%. It also has 86% precision and 95% recall for the Dissatisfied category, higher than SVM (93% recall). The McNemar test confirms a statistically significant performance difference (p-value = 0.037). With higher accuracy and interpretability, Decision Tree is recommended as the primary method for hospital patient satisfaction analysis. These findings support the development of an adaptive classification system for Indonesian healthcare data.
Frontend Implementation on EngVenture Application at IntSys Research Lab Nurhana Rifki, Slamet Ikhvan; Gamayanto, Indra; Wibowo, Sasono; Sirwenda, Alfian Bisma Daniswara; Ismanto, Ivan; Kurniawan, Michael Christ
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11337

Abstract

In today's digital era, the use of mobile applications for English learning is increasingly popular as an alternative to self-study. However, many available applications still lack the ability to provide an interactive, adaptive, and enjoyable learning experience, and do not provide integrated proficiency measurement features such as the TOEFL test. This research focuses on the frontend implementation of the EngVenture application, an English learning platform developed at IntSys Research Lab using the Rapid Application Development (RAD) method. This application is designed to address these issues by integrating gamification elements and a TOEFL-like practice test system to increase engagement and measure user progress. Data were collected through literature studies and questionnaires distributed to 100 respondents from various educational levels. The results showed that 82% of respondents needed a fun learning medium, 92% wanted a TOEFL test feature, and 88% were interested in the gamification feature. The application was developed using Flutter and Dart, with a responsive UI/UX design and real-time feedback features. System testing was conducted using two methods: black-box User Acceptance Testing (UAT) to assess functionality, and a System Usability Scale (SUS) to measure the application's usability. Test results showed that all features functioned well, with an average SUS score of 84.25, which falls into the Acceptable (Grade B+, Excellent) category. These results demonstrate that EngVenture meets user needs in terms of functionality and usability, and has the potential to become an interactive and effective English language learning tool.
Design and Implementation of a Backend System and DevOps Workflow for Interactive Learning Applications Daniswara Sirwenda, Alfian Bisma; Wibowo, Sasono; Gamayanto, Indra; Rifki, Slamet Ikhvan Nurhana; Ismanto, Ivan; Kurniawan, Michael Christ
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11338

Abstract

English language learning in Indonesia faces significant challenges, including limited vocabulary retention, poor pronunciation, and passive learning methods. The EngVenture application was developed to address these issues by integrating gamification principles with interactive English learning environments. This study aims to design and implement a backend system and DevOps workflow that ensure optimal performance, security, and stability for gamification-based learning applications. The Rapid Application Development (RAD) method was employed, comprising requirements planning, user design, construction, and cutover phases. System requirements were identified through a validated questionnaire (Cronbach's α = 0.89) distributed to 101 respondents from diverse backgrounds. Results indicated that users prioritized data security (90.1%), system speed (91.1%), and secure authentication (69.3%) as critical factors. Based on these findings, a RESTful API-based backend was designed and integrated with Docker, Jenkins, and Nginx, incorporating security features such as JWT authentication, API key validation, and SSL/TLS encryption. Quantitative evaluation over a 20-day period demonstrated significant improvements: 85% faster deployment time (6.23→1.48 minutes), 43.4% reduction in error rate (211→138 errors), 95.7% build success rate, stable API response time (~160ms) under load testing with 1,000 concurrent requests, and near-zero downtime (<5 minutes). This research demonstrates that the integration of structured backend architecture and automated DevOps practices significantly enhances system reliability, deployment efficiency, and user satisfaction in educational technology applications such as EngVenture.
Optimizing F1 Tyre Performance Prediction with SVC, XGBoost, and Optuna For Dutch GP 2022 Anandatama, Dimas Haydar; Gamayanto, Indra
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11452

Abstract

Formula 1 has evolved into a data-centric sport where strategic decisions, particularly tire compound selection (Soft, Medium, Hard), are critical for success. The ability to accurately identify a competitor's compound from observable telemetry data offers a significant strategic advantage, yet the predictive signals are subtle and difficult to distinguish. This study implements and compares two distinct machine learning methodologies to classify F1 tyre compounds using telemetry data from the 2022 Dutch Grand Prix. First, a baseline model was established using standard dynamic features (e.g., avg_speed, avg_rpm). While this approach confirmed the superiority of XGBoost over SVC, it yielded a modest accuracy of 67.99% and revealed a critical deficiency: a failure to reliably identify the HARD compound, registering a poor F1-score of 0.57. To address these limitations, an advanced methodology was developed, integrating hybrid feature engineering (e.g., LapTime, SectorTime, TyreLife) with deep hyperparameter optimization via Optuna. This enhanced approach resulted in a significantly more robust XGBoost model, achieving a final, stable accuracy of 77.34%. More importantly, it solved the baseline's primary flaw, increasing the F1-score for the critical HARD compound by 36.8% to 0.78. A feature importance analysis confirmed this methodological shift, as the most dominant predictors changed from the baseline's generalized avg_speed to the advanced model's outcome-based features (LapTime, Sector3Time). The findings definitively conclude that while algorithm selection is important, the most critical factor for this task is the quality of feature engineering. Integrating outcome-based and strategic-context features is essential to successfully extracting the subtle performance signatures that differentiate F1 tyre compounds.
Security Evaluation of Keycloak-Based Role-Based Access Control in Microservice Architectures Using the OWASP ASVS Framework Gamayanto, Indra; Christ Kurniawan , Michael; Klavin Sanyoto , Gabriello
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11604

Abstract

The Rocket Car Wash Semarang application operates using a microservice architecture that handles sensitive information such as user identity data, transaction history, and vehicle details. As multiple services interact through authenticated API calls, strong access control is required to protect the system from unauthorized access and privilege escalation. This research evaluates the Keycloak-based Role-Based Access Control (RBAC) implementation by referencing relevant domains of the OWASP Application Security Verification Standard (ASVS) Level 2, specifically V2: Authentication, V3: Session Management, V4: Access Control, and V14: Configuration. The RBAC structure consists of three primary roles—Admin, Owner, and Customer—and the assessment examines the correctness of role–permission mapping and token-based authorization across microservices. The security evaluation was conducted through configuration auditing, API endpoint verification using Postman, JWT token validation, and automated penetration testing using OWASP Zed Attack Proxy (ZAP). The ZAP scan targeted common web vulnerabilities, particularly misconfigurations and weaknesses in HTTP security headers. The results indicate that Keycloak effectively enforces centralized authentication and authorization, with no critical issues such as Broken Access Control identified. However, several non-critical weaknesses were found, including incomplete Content Security Policy (CSP) directives and missing HSTS headers. These findings show that the RBAC implementation meets core ASVS Level 2 controls, while further improvements in security header configuration are required to enhance overall system resilience.
Addressing Extreme Class Imbalance in Multilingual Complaint Classification Using XLM-RoBERTa Ariyanto, Muhammad; Alzami, Farrikh; Sani, Ramadhan Rakhmat; Gamayanto, Indra; Naufal, Muhammad; Winarno, Sri; Iswahyudi
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.v10i1.11606

Abstract

Government complaint management systems often suffer from extreme class imbalance, where a few public service categories accumulate most reports while many others remain under-represented. This research examines whether simple class weighting can improve fairness in multilingual transformer models for automatic routing of Indonesian citizen complaints on the LaporGub Central Java e-governance platform. The dataset comprises 53,877 Indonesian-language complaints spanning 18 service categories with an imbalance ratio of about 227:1 between the largest and smallest classes. After cleaning and deduplication, we stratify the data into training, validation, and test sets. We compare three approaches: (i) a linear support vector machine (SVM) with term frequency inverse document frequency (TF-IDF) unigram and bigram and class-balanced weights, (ii) a cross-lingual RoBERTa (XLM-RoBERTa-base) model without class weighting, and (iii) an XLM-RoBERTa-base model with a class-weighted cross-entropy loss. Fairness is operationalised as equal importance for categories and quantified primarily using the macro-averaged F1-score (Macro-F1), complemented by per-class F1, weighted F1, and accuracy. The unweighted XLM-RoBERTa model outperforms the SVM baseline in Macro-F1 (0.610 vs 0.561). The class-weighted variant attains similar Macro-F1 (0.608) while redistributing performance towards minority categories. Analysis shows that class weighting is most beneficial for categories with a few hundred to several thousand samples, whereas extremely rare categories with fewer than 200 complaints remain difficult for all models and require additional data-centric interventions. These findings demonstrate that multilingual transformer architectures combined with simple class weighting can provide a more balanced backbone for automated complaint routing in Indonesian e-government, particularly for low- and medium-frequency service categories.
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.
Co-Authors -, Suhariyanto Abas Setiawan Abas Setiawan Abdul Syukur Achmad Wahid Kurniawan Acun Kardianawati Adriana Dina Agus Prayitno Agus Winarno, Agus Ahmad Zainul Fanani Al zami, Farrikh Alzami, Farrikh Anandatama, Dimas Haydar Angelia Dwi Ceissa Anggraini, Dinda Arief Setyayoga ARIYANTO, MUHAMMAD Arta Moro Sundjaja, Arta Moro Asih Rohmani Asih Rohmani Asih Rohmani Asih Rohmani, Asih Budi Widjajanto Budi, Setyo Christ Kurniawan , Michael Christian, Henry Daniswara Sirwenda, Alfian Bisma De Rosal Ignatius Moses Setiadi Dena Trixie Rahma Tifany Destya Khairuna Desy Dwi Prasetyowati Devi Ajeng Efrilianda Devi Purnamasari Dewi Agustini Santoso Dewi Agustini Santoso Edi Faisal efrilianda, Devi ajeng efrilianda Elok Iedfitra Haksoro Fahmi Amiq Fajrian Nun Adnan Farrikh Al Zami Farrikh Al Zami Fenny Angelina Fitri Febriani Florentina Esti Nilasari Florentina Esti Nilawati Florentina Esti Nilawati Hadi, Heru Pramono Hanny Haryanto Harini Harini Harisa, Ardiawan Bagus Henry Christian Henry Christian Herisa, Ardiawan Bagus Herman Try Maulana Herowati, Wise I Gusti Bagus Wiksuana Ibnu Utomo WM Ihya Ulumuddin, Dimas Irawan Ismanto, Ivan Iswahyudi Klavin Sanyoto , Gabriello Kurniadi, Agung Kurniawan, Michael Christ Kustiadi, Josse Kustiadi, Kustiadi Lusi Noviani Prasetyo Mailangkay, Adele B L Marjuni, Aris Maulana, Herman Try Melianie, Melianie Muhammad Naufal, Muhammad Nugraha, Alvin Satria Nugraha, Rizka Nurhana Rifki, Slamet Ikhvan Nurhindarto, Aris Pangesti, Galih Mentari Prabawaseputra, Rafael Agusto Prasetyo, Lusi Noviani Purnamasari, Devi Ramadhan Rakhmat Sani Rifki, Slamet Ikhvan Nurhana Rindang Widuri Rizka Nugraha S, Dewi Agustini Sanyoto, Gabriello Klavin Saroji Saroji Sasono Wibowo Sendi Novianto Sendi Novianto Sendi Novianto Sendi Novianto Setiawan, Aries Setyo Budi Setyo Budi Sirait, Tamsir Hasudungan Sirwenda, Alfian Bisma Daniswara Sri Winarno Sri Winarno Suharnawi Suharnawi Suharnawi Suharnawi Suharnawi Sukamto, Titien Sukamto, Titien S Sukamto, Titien Suhartini Titien S Sukamto Titien S sukamto Titien S Sukamto Titien Suhartini Sukamto Titien Suhartini Sukamto Utomo WM, Ibnu Wahid Kurniawan, Achmad Zaenal Arifin Zami, Farrikh Al