Article Per Year (5 Year)
p-Index From 2021 - 2026
0.882
P-Index
This Author published in this journals
All Journal TIN: TERAPAN INFORMATIKA NUSANTARA Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer
Andri Firmansyah
Universitas Pelita Bangsa, Bekasi
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : bulletin of computer science research

 1 
Perbandingan Kinerja Naïve Bayes dengan dan Tanpa SMOTE untuk Klasifikasi Gangguan Kecemasan Mahasiswa pada Data Tidak Seimbang Nurhadi Surojudin; Sufajar Butsianto; Andri Firmansyah
Bulletin of Computer Science Research Vol. 6 No. 2 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i2.1021

Abstract

Anxiety disorders are one of the most common mental health problems experienced by university students and may affect learning concentration and academic performance. The analysis of psychological survey data using machine learning techniques can support early detection of student anxiety conditions. However, one of the main challenges in mental health data analysis is the presence of class imbalance within the dataset. This study aims to analyze the effect of applying the Synthetic Minority Oversampling Technique (SMOTE) on the performance of the Naïve Bayes algorithm for multi-class classification of student anxiety levels, which are categorized into three classes: No Stress, Eustress, and Distress. The dataset used in this research was obtained from student questionnaire data and underwent several preprocessing steps including data cleaning, feature transformation, and dataset splitting using the hold-out method with a ratio of 80% training data and 20% testing data. Model performance was evaluated using a confusion matrix with evaluation metrics including accuracy, precision, recall, and F1-score. The results show that the Naïve Bayes model without SMOTE achieved an accuracy of 0.84, precision 0.78, recall 0.41, and F1-score 0.54. After applying SMOTE, the model achieved an accuracy of 0.82, precision 0.74, recall 0.69, and F1-score 0.71. These results indicate that SMOTE improves the model's ability to detect minority classes in multi-class classification problems, although a slight decrease in overall accuracy is observed.
Analisis Pengembangan dan Evaluasi Virtual World Bertema Lingkungan Pegunungan Menggunakan Metode Research and Development (R&D) Robby Firmansyah; Andri Firmansyah
Bulletin of Computer Science Research Vol. 6 No. 4 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i4.1146

Abstract

The development of metaverse technology and virtual worlds has created opportunities for utilizing virtual environments as media for digital exploration, simulation, and interactive learning. However, most previous studies have primarily focused on pedagogical aspects and learning simulations, while research discussing the technical development of terrain modeling, lighting, and mountainous environmental atmospheres on the Roblox Studio platform remains limited. This study aims to develop and evaluate a mountainous environment-themed virtual world using Roblox Studio and to analyze user acceptance of the resulting virtual environment. The research employed the Research and Development (R&D) method, consisting of needs analysis, design, implementation, testing, and evaluation stages. The development process utilized Terrain Editor, Future Lighting, skybox, fog, and Lua scripting features to create an interactive virtual environment. Evaluation was conducted using a Likert-scale questionnaire distributed to 67 respondents. The results showed a feasibility score of 79.88%, which falls into the good category. The highest-rated indicator was the suitability of the virtual world to the mountainous environment concept (4.15), while the lowest-rated indicator was the structured layout of the environment (3.83). These findings indicate that the developed virtual world was able to provide a positive exploration experience for users. The contribution of this research lies in establishing a systematic development framework for a mountainous environment-themed virtual world through the implementation of terrain modeling, lighting and atmospheric configuration, and user experience evaluation using the Research and Development (R&D) approach. In addition, this study provides a practical reference for the development of metaverse-based virtual environments that can be utilized for simulation, digital exploration, and interactive learning applications.
Co-Authors Alfaza Putra Adjie Ariefiansyah Bilal AlHafidz Ikhsan Romli Nurhadi Surojudin Robby Firmansyah Sufajar Butsianto Suherman Suherman Zulham Iftikar Jamaludin