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All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Bulletin of Computer Science Research
Cucut Hariz Pratomo
Universitas Muhammadiyah Karanganyar, Karanganyar
Computer Science & IT Decision Sciences, Operations Research & Management

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Pengembangan Website Responsive Sebagai Portal Informasi Kegiatan dan Berita Himpunan Mahasiswa Menggunakan Metode Research And Development dengan Model Waterfall Satria Cahya Syaputra; Cucut Hariz Pratomo
Journal of Information System Research (JOSH) Vol 7 No 4 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i4.10463

Abstract

The dissemination of activity information and news within Student Associations is often carried out through various separate platforms, resulting in information fragmentation and reducing the effectiveness of information delivery to students. This condition makes it difficult for students to obtain information due to the increased risk of missing important organizational activities and news. Therefore, a centralized information platform is needed to provide integrated information that can be easily accessed through various devices. This research aims to design and develop a responsive website as a centralized portal for Student Association activities and news using the Next.js framework. This study applies the Research and Development (R&D) method with the Waterfall development model, which consists of several stages, namely requirements analysis, system design, implementation, and testing to ensure that the website operates in accordance with user requirements. The system was developed using Next.js as the main framework and Tailwind CSS to support the implementation of Responsive Web Design, enabling the website to be accessed optimally on desktop, tablet, and smartphone devices. This research resulted in a system that successfully integrates news, activities, organizational profiles, and documentation into a single centralized digital platform. System testing was conducted using the Black Box Testing method by evaluating all major functions based on predetermined input and output scenarios without examining the internal structure of the program code. The test results showed that all functions operated in accordance with the specified functional requirements, achieving a 100% success rate across all testing scenarios. The developed website enables students to access centralized information on Student Association activities and news more conveniently through a wide range of devices.
Rancang Bangun Sistem Computer Based Test (CBT) Penerimaan Mahasiswa Baru Berbasis Web Menggunakan Metode Research And Development dengan Model Waterfall Ardiansyah Cahya Nugroho; Cucut Hariz Pratomo
Journal of Information System Research (JOSH) Vol 7 No 4 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i4.10588

Abstract

The implementation of the New Student Admission (PMB) selection process requires an efficient, transparent, and effective system to support accurate decision-making. Previously, the Computer-Based Test (CBT) system used for PMB selection relied on the CodeIgniter framework, which was prone to limitations in data management flexibility, security, and scalability as the number of applicants increased. To address these challenges, this study redesigns a web-based PMB CBT system using the Laravel framework, which adopts the Model-View-Controller (MVC) architecture, and integrates a relational database MySQL to provide structured and maintainable data management. Most previous studies have primarily focused on the digitalization of examination processes, usability improvements, or basic system efficiency. The main innovation and contribution of this research is the implementation of a live score feature that ensures transparent and immediate presentation of examination results for participants. This study employs the Research and Development (R&D) method to design, develop, and evaluate the proposed system. The developed system includes several key features, such as participant management, question bank management, online examinations, automatic score calculation, and a live score feature for real-time result monitoring. Based on Black Box Testing, the system achieved a functional validity rate of 100%, indicating that all testing scenarios were successfully executed without errors. The proposed system contributes by enhancing the transparency of score calculation and utilizing a scalable technology architecture to assist the admission committee in managing large-scale applicant data efficiently.
Pola Perilaku Pemain Roblox: Pemodelan Klasifikasi Berbasis Naïve Bayes Risqi Nur Avianti; Cucut Hariz Pratomo
Bulletin of Computer Science Research Vol. 6 No. 5 (2026): August 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i5.1188

Abstract

The development of digital technology has driven the growth of online gaming as a medium for entertainment, social interaction, and creativity development. One platform that has grown rapidly is Roblox, which allows users to play, interact, and create digital content. This diversity of activities causes player behavior characteristics to become increasingly complex, making them difficult to identify manually. Therefore, a machine learning-based approach is needed to classify player behavior more objectively and systematicallys. This study aims to classify Roblox player behavior into four categories, namely active, casual, social, and creative players, using the Naïve Bayes algorithm. This algorithm was chosen because it has a simple and efficient computational process and is suitable for questionnaire data that has been transformed into numerical form. A total of 523 responses were successfully collected, and after the selection and preprocessing stages, 520 data points were obtained to be used as the research dataset. The data were processed through data cleaning, encoding, missing value handling, and dataset splitting using an 80% training data and 20% test data. The results showed that the model achieved an accuracy of 62.5%. Evaluation using precision, recall, and F1-score metrics revealed that The results showed that the model produced an accuracy of 62.5%, with a precision value of 63%, recall of 62%, and F1-score of 62%. Although the accuracy obtained is not yet high, these results indicate that the Naïve Bayes algorithm can be used as a baseline in classifying player behavior based on questionnaire data that has subjective and complex characteristics. The his study contributes by providing a baseline classification model for Roblox player behavior based on questionnaire data, along with insights into player characteristics that can serve as a reference for developers in understanding user behavior, thereby supporting the development of more adaptive features that better align with players' needs.
Co-Authors Ardiansyah Cahya Nugroho Risqi Nur Avianti Satria Cahya Syaputra