cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Mesran
Contact Email
mesran.skom.mkom@gmail.com
Phone
+6282370070808
Journal Mail Official
jurnal.bulletincsr@gmail.com
Editorial Address
Jalan sisingamangaraja No 338 Medan, Indonesia
Location
Kota medan,
Sumatera utara
INDONESIA
Bulletin of Computer Science Research
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27743659     DOI : -
Core Subject : Science,
Computer Science & IT
Bulletin of Computer Science Research covers the whole spectrum of Computer Science, which includes, but is not limited to : • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer Interfacing • Business Intelligence • Chaos theory and intelligent control systems • Clustering and Data Analysis • Complex Systems and Applications • Computational Intelligence and Soft Computing • Distributed Intelligent Systems • Database Management and Information Retrieval • Evolutionary computation and DNA/cellular/molecular computing • Expert Systems • Fault detection, Fault analysis, and Diagnostics • Fusion of Neural Networks and Fuzzy Systems • Green and Renewable Energy Systems • Human Interface, Human-Computer Interaction, Human Information Processing • Hybrid and Distributed Algorithms • High-Performance Computing • Information storage, security, integrity, privacy, and trust • Image and Speech Signal Processing • Knowledge-Based Systems, Knowledge Networks • Knowledge discovery and ontology engineering • Machine Learning, Reinforcement Learning • Networked Control Systems • Neural Networks and Applications • Natural Language Processing • Optimization and Decision Making • Pattern Classification, Recognition, speech recognition, and synthesis • Robotic Intelligence • Rough sets and granular computing • Robustness Analysis • Self-Organizing Systems • Social Intelligence • Soft computing in P2P, Grid, Cloud and Internet Computing Technologies • Support Vector Machines • Ubiquitous, grid and high-performance computing • Virtual Reality in Engineering Applications • Web and mobile Intelligence, and Big Data • Cryptography • Model and Simulation • Image Processing
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 462 Documents
 36   37   38   39   40 
Pengembangan Aplikasi Manajemen Tata Kelola Perusahaan Berbasis Mobile Tri Jaka Satria; Rr Hajar Puji Sejati
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.879

Abstract

The digitalization of corporate governance has become an essential need for improving the effectiveness and accuracy of human resource management. Many companies still rely on manual methods for recording attendance, leave applications, and payroll calculation, which are prone to administrative errors and lack accountability. This research aims to develop a mobile-based corporate governance application capable of integrating various administrative processes into a centralized system. The application offers several key features, namely employee data management, photo-based check-in and check-out attendance, digital leave applications, and an automated payroll mechanism. The attendance system is equipped with location validation to ensure employees are within a ± 30 meter radius of the designated office point, while tardiness is automatically recorded and subjected to a salary deduction of Rp2,000 for every 5 minutes, in accordance with company-established regulations. All data is synchronized in real-time, supporting transparency and expediting administrative processes. The test results show that the application is capable of enhancing operational efficiency, reducing the potential for fraud, and strengthening the principles of transparency and accountability in corporate governance. By integrating several critical processes within a single mobile platform, this system proves to be effective in assisting companies to implement a more modern and measurable governance framework.
Analisis Pengelompokan Wilayah Berdasarkan Frekuensi Kejadian Banjir Menggunakan K-Means Clustering Cinta Aurelya; Yunus Widjaja
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.880

Abstract

Floods are among the most frequent natural disasters occurring in West Java Province and have significant impacts on social and economic conditions. Although the government provides flood incident frequency data down to the village and sub-district levels, its utilization for detailed vulnerability analysis remains limited. This study aims to classify regions based on the frequency of flood events using the K-Means Clustering method as an analytical approach to produce a more comprehensive risk mapping. The dataset consists of flood incident records from 2022 to 2024 obtained from official government sources. The analytical process follows the stages of Knowledge Discovery in Database with a primary focus on the implementation of the K-Means algorithm, while model evaluation is conducted using the Elbow Method and Silhouette Score to determine the optimal number of clusters. The results indicate that three clusters provide the most structured grouping of flood risk. The low-risk cluster consists of 12,454 regions that experienced zero flood events. The medium-risk cluster includes 3,404 regions with flood frequencies ranging from 1 to 6 events. Meanwhile, the high-risk cluster comprises 76 regions with flood occurrences between 7 and 33 events. These findings are expected to support flood mitigation planning, spatial planning strategies, the development of flood-control infrastructure, and to assist communities in evaluating the safety of potential residential areas.
Analisis Komentar Youtube Terhadap Polemik Ijazah Presiden Ke 7 Indonesia Menggunakan Support Vector Machine Ignasius Aditya Anggoro Putra; Salmon Salmon; Kusnandar Kusnandar
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.883

Abstract

This study aims to analyze public sentiment toward the controversy surrounding President Joko Widodo’s academic credentials by examining user comments on YouTube. A total of 20,294 comments were collected and processed through text cleaning, normalization, tokenization, stopword removal, and stemming. Sentiment labels were assigned using a lexicon-based approach, producing positive, negative, and neutral categories. The experimental results indicate that the combination of SVM, TF-IDF, and SMOTE achieved strong classification performance, with an accuracy of 86.87%. The model demonstrated better performance in identifying negative and neutral sentiments, while some positive sentiments tended to be misclassified as neutral. Overall, this study shows that sentiment analysis based on YouTube comments can serve as an effective approach for mapping public opinion on socio-political issues in an automated and large-scale manner. Feature extraction utilized Term Frequency–Inverse Document Frequency (TF-IDF), and sentiment classification was performed using a Support Vector Machine (SVM). The model achieved an accuracy of 86.87% and a macro F1-score of 0.87, indicating that the integration of TF-IDF, SMOTE, and SVM is effective for large-scale sentiment classification of YouTube comments related to socio-political issues.
Hybrid EGARCH-LSTM for Price Forecasting and Risk Estimation of Daily USD/IDR (2015–2025) Alfaiz Arifin Setia Budi; Siti Salsabila Maryanto; Muhammad Althafino; Salsabila Sekar Nadia; Zulvania Armiana; Shaifudin Zuhdi
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.884

Abstract

Forecasting volatility in the USD/IDR exchange rate poses a critical challenge for Indonesia's financial stability, especially given how the data tends to display non-linear characteristics along with extreme outliers—what we commonly call fat-tails. This research develops a hybrid EGARCH-LSTM architecture to address these challenges by bringing together the precision of econometric modeling with deep learning's adaptability. Our dataset consists of 2,605 daily observations of the USD to IDR exchange rate ranging from 2015 to 2025. We extract volatility features using an EGARCH(1, 1) model with a t-distribution, which will then be entered as exogenous input into a Long-Short-Term Memory (LSTM) network. Our analysis shows a strong contrast between price predictions and risk estimates. In terms of price forecasting, the market demonstrates remarkable efficiency. The simple Naive Forecast, with an RMSE of 100.47, proved extremely difficult to outperform, lending support to the Random Walk Hypothesis. However, the Hybrid EGARCH-LSTM demonstrated superior volatility prediction capabilities, achieving the lowest Out-of-Sample Volatility MAE of 0.0075 compared to 0.0083 for the standalone EGARCH model. The EGARCH-LSTM hybrid model achieved the best performance, passed the Kupiec backtest (P-value = 0.4373), and significantly outperformed the pure econometric model, which failed due to excessive conservatism in its estimation. This study concludes that although accurate price predictions are still unattainable in efficient markets, the EGARCH-LSTM hybrid architecture provides a powerful and reliable tool for risk estimation. These results offer significant implications for hedging and risk management practices in the Indonesian foreign exchange market.
Evaluasi Kualitas Platform Marketplace BUMDesa Menggunakan Metode Grey-Box Testing berbasis Standar ISO/IEC 9126 Dinda Maylan Setianti; Ariq Cahya Wardhana
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.890

Abstract

The BUMDesa marketplace platform was developed to support the digitalization of village business processes, enhance local economic activities, and strengthen the role of BUMDesa in managing community-based enterprises. Although the platform has been utilized by several user categories, a comprehensive evaluation of its software quality has not yet been conducted. This study aims to assess the quality of the BUMDesa marketplace platform using the grey-box testing method integrated with the ISO/IEC 9126 standard. The grey-box testing approach was employed to examine both internal and external system behaviors across three platforms: the website, Android mobile application, and API. Quality evaluation was carried out based on five ISO/IEC 9126 aspects: functionality, reliability, efficiency, maintainability, and portability. The results show that the functionality aspect achieved a feasibility score of 73% (“Fair”), reliability reached 86% (“Good”), efficiency obtained 100% (“Very Good”), maintainability scored 62% (“Poor”), and portability achieved 100% (“Very Good”). These findings indicate that the platform meets quality standards in terms of reliability, efficiency, and portability, while improvements are still needed in functionality and maintainability. This study provides recommendations for enhancing software quality and may serve as a reference for evaluating similar digital platforms within village-owned enterprises.
Pengembangan Fitur Penelitian Tugas Real–Time Pada Sistem E-Learning Berbasis Web Untuk Meningkatkan Interaktivitas Siswa Majid Armansyah; Adam Sekti
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.891

Abstract

This research develops a real-time assignment assessment feature in a web-based e-learning system to enhance student interactivity and learning effectiveness. One of the main challenges commonly found in conventional e-learning systems is the delay in the assessment process, which prevents students from receiving timely feedback. This condition negatively affects learning motivation, student engagement, and the speed at which students grasp the material. To address this issue, this study designs and implements a real-time assessment feature using the CodeIgniter framework, HTML, and MySQL with a three-layer architecture. The developed features include automatic assessment, direct feedback, instant notification systems, and an integrated score-monitoring dashboard. The research employs a Research and Development (R&D) method with the Waterfall development model, which consists of requirement analysis, system design, implementation, and testing phases. Data were collected through interviews, observations, and expert validation to ensure the feasibility and appropriateness of the system. The test results indicate that the real-time assessment feature significantly improves teacher efficiency in grading assignments, accelerates the delivery of scores, and increases student motivation during the learning process. Expert validation showed that the system is highly feasible, while user evaluations revealed enhanced interactivity and ease of use. Overall, the implementation of the real-time assessment feature in this web-based e-learning system successfully creates a more responsive, adaptive, and interactive learning environment. This development provides tangible benefits for supporting digital learning processes and serves as a foundation for future feature enhancements in e-learning platforms.
Optimasi Hyperparameter Pada Model Hybrid Bidirectional LSTM-GRU Untuk Prediksi Harga Saham Bank Adam Maulidin Duha; Anggyi Trisnawan Putra
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.903

Abstract

Stock price prediction in the Indonesian capital market is highly complex due to the significant influence of market volatility and the non-linear nature of time-series data. Errors in predicting price trends can significantly increase investment risks. This study aims to enhance the accuracy of stock price prediction for blue-chip banking companies (a case study on one of the largest state-owned banks) by addressing the limitations of single models. The proposed method is a Hybrid Deep Learning architecture combining Bidirectional Long Short-Term Memory (Bi-LSTM) to capture long-term dependencies and Bidirectional Gated Recurrent Unit (Bi-GRU) for computational efficiency. To ensure maximal model performance, automatic hyperparameter optimization was performed using the Hyperband algorithm, which utilizes an adaptive resource allocation strategy. The data employed consists of 10 years of historical daily trading data (2014–2024), which underwent Min-Max normalization and a 60-day window size formation. Experimental results demonstrate that the Hyperband algorithm successfully identified the optimal configuration of 128 Bi-LSTM units and 32 Bi-GRU units with the tanh activation function. Model evaluation on the test data indicated a high level of accuracy, with a Root Mean Squared Error (RMSE) of IDR 171.41 and a Mean Absolute Error (MAE) of IDR 142.53. These results confirm that the systematically optimized hybrid approach is capable of minimizing prediction errors significantly better and is reliable for modeling fluctuating stock price dynamics.
Desain UI/UX Aplikasi MediSaku untuk Edukasi Obat Menggunakan Pendekatan User-Centered Design Rasmila Rasmila; Muhammad Erlangga Fauzi; M Zakiansyah; Dzikri Thoriq Al Ariiq; Rachmat Adiaz Arrofi
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.910

Abstract

The rapid development of mobile device technology has encouraged the utilization of digital applications in various fields, including the provision of health information, particularly related to medications. Although many drug-education applications are currently available, a significant number of them still have complex user interfaces that make it difficult for general users to understand the information presented. This condition may lead to potential medication misuse. Therefore, this study aims to design the User Interface (UI) and User Experience (UX) of the MediSaku drug-education application based on Android that is simple, informative, and easy to use. The research method consists of preliminary study, user needs analysis, navigation structure and interface design, as well as the development of a high-fidelity prototype. The design process adopts a user-centered design approach and considers usability principles such as ease of use, consistency, and clarity of information. The result of this study is a high-fidelity prototype that includes several main pages, namely the splash screen, login, home, drug information, medication reminder, health articles, and user profile pages. Based on the conceptual design evaluation using heuristic principles, the MediSaku interface design is considered capable of facilitating users in accessing drug information and improving interaction comfort. This design is expected to serve as a foundation for the future implementation stage of the MediSaku application.
Penerapan Metode TOPSIS untuk Pemeringkatan Saham Jakarta Islamic Index 70 Zulfiandri Zulfiandri; Balqis Aulia Rahma; Zafira Fayyaza Lutfun Nisa; Farah Adila; Rinda Hesti Kusumaningtyas
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.912

Abstract

This study aims to evaluate and rank sharia stocks included in the Jakarta Islamic Index 70 (JII70) as a basis for investment recommendations based on fundamental performance. The problem discussed is the need for investors to have an objective and structured decision-making model in selecting sharia stocks, considering the large number of stock alternatives available in the JII70 index. This study uses the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method implemented using RStudio. Of the total 70 stocks in the JII70 index, this study analyzes five sharia issuers, namely TLKM, CTRA, ADRO, KLBF, and ICBP, which were selected purposively based on their level of liquidity, availability of financial ratio data, and cross-sector representation of the industry. The criteria used include Price to Earnings Ratio (PER), Price to Book Value (PBV), Return on Equity (ROE), Debt to Equity Ratio (DER), and Net Profit Margin (NPM). The criteria weighting was conducted using a subjective approach based on investor preferences, considering the relative importance of each ratio to investment decisions. The results of the study show that PT Adaro Energy Indonesia Tbk (ADRO) consistently obtained the highest preference value with a value of 0.771, followed by PT Ciputra Development Tbk (CTRA) in second place. These findings demonstrate that the TOPSIS method is capable of providing a systematic and transparent ranking of sharia stocks, although this study has limitations in the number of issuer samples analyzed. Future research can expand the number of issuers and add macroeconomic criteria.
Analisis Penggunaan Teknologi E-Learning Menggunakan Technology Acceptance Model (TAM) pada Mahasiswa Perguruan Tinggi Swasta Imam Fauzi Akmal; M Hafizh Azhar Ar; Debi Irawan
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.914

Abstract

This research is motivated by the increasing use of e-learning systems in Indonesian universities post-COVID-19 pandemic, which has accelerated digital transformation in the learning process. Although the implementation of e-learning is becoming increasingly widespread, students' acceptance levels of the system still vary and are influenced by their perceptions of ease of use and perceived benefits. Therefore, this study aims to analyze student acceptance of the e-learning system using the Technology Acceptance Model (TAM) approach, focusing on the influence of Perceived Ease of Use (PEOU) on Perceived Usefulness (PU), as well as the influence of PEOU and PU on Behavioral Intention to Use (BIU). This research uses a quantitative approach with an associative-causal design. The research respondents were 100 active students who had used the e-learning system for at least one semester, selected thru purposive sampling. Data was collected online using a closed questionnaire and analyzed using simple linear regression and multiple linear regression techniques. The research findings indicate that PEOU has a positive and significant effect on PU. Furthermore, PEOU is also proven to have a positive and significant effect on BIU, while PU does not show a significant effect on BIU. These findings suggest that the ease of use of the e-learning system is the dominant factor in shaping students' interest in using e-learning continuously. The results of this research are expected to contribute theoretically to the development of technology acceptance studies in higher education and serve as a basis for practical recommendations for universities in designing and managing more effective, adaptive, and user-needs-oriented e-learning systems.

Page 38 of 47 | Total Record : 462

 36   37   38   39   40 

Filter by Year

2020 2026


Reset
Filter By Issues
All Issue Vol. 6 No. 5 (2026): August 2026 Vol. 6 No. 4 (2026): June 2026 Vol. 6 No. 3 (2026): April 2026 Vol. 6 No. 2 (2026): February 2026 Vol. 6 No. 1 (2025): December 2025 Vol. 5 No. 6 (2025): October 2025 Vol. 5 No. 5 (2025): August 2025 Vol. 5 No. 4 (2025): June 2025 Vol. 5 No. 3 (2025): April 2025 Vol. 5 No. 2 (2025): February 2025 Vol. 5 No. 1 (2024): December 2024 Vol. 4 No. 6 (2024): Oktober 2024 Vol. 4 No. 5 (2024): August 2024 Vol. 4 No. 4 (2024): June 2024 Vol. 4 No. 3 (2024): April 2024 Vol. 4 No. 2 (2024): Februari 2024 Vol. 4 No. 1 (2023): December 2023 Vol. 3 No. 6 (2023): October 2023 Vol. 3 No. 5 (2023): Agustus 2023 Vol. 3 No. 4 (2023): June 2023 Vol. 3 No. 3 (2023): April 2023 Vol. 3 No. 2 (2023): Februari 2023 Vol. 3 No. 1 (2022): Desember 2022 Vol. 2 No. 3 (2022): Agustus 2022 Vol. 2 No. 2 (2022): April 2022 Vol. 2 No. 1 (2021): Desember 2021 Vol. 1 No. 3 (2021): Agustus 2021 Vol. 1 No. 2 (2021): April 2021 Vol. 1 No. 1 (2020): Desember 2020 More Issue