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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 8 Documents
 1 
Search results for , issue "Vol. 5 No. 6 (2025): October 2025" : 8 Documents clear
Analisis dan Perancangan Sistem Informasi Pendaftaran Magang Berbasis Web di Sektor Pemerintahan Menggunakan Metode RAD Nurmiati, Evy; Aulia Rahma, Balqis; Kamil, Musthafa
Bulletin of Computer Science Research Vol. 5 No. 6 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i6.797

Abstract

Internships are a practical learning experience for students in government agencies and other sectors. However, the administrative process often faces challenges, particularly in terms of efficiency and order. This research was conducted in a government agency, focusing on the design of a web-based internship registration information system. The problem encountered was that the internship administration process still required many manual steps, potentially causing verification delays and suboptimal information delivery. To address these issues, this study employed the Rapid Application Development (RAD) method, with the main stages being requirements planning, design, implementation, and system testing. Data were collected through literature studies, observations, and system requirements analysis using the SWOT and PIECES approaches. The objective of the research was to design a prototype system capable of supporting an integrated internship registration process, from participant registration and application submission, document verification, to application status notification. The results showed that the designed system was able to improve administrative efficiency, accelerate communication between related parties, and provide transparency to interns in monitoring application status. With this system, it is hoped that agencies can reduce administrative problems and provide more effective and structured internship services.
Penerapan Augmented Reality Pada Media Pembelajaran Sains di Sekolah Dasar Swasta Andriyanto, Sidhiq; Parulian Silalahi; Fateh Tikal Zamzami
Bulletin of Computer Science Research Vol. 5 No. 6 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i6.801

Abstract

This research focuses on developing an interactive augmented reality learning media to address the problem of low learning interest and understanding of science concepts at SDS Maria Goretti Sungailiat, particularly on the topics of photosynthesis, energy transformation, states of matter, and force effects. The augmented reality application was developed through six stages of MDLC - concept, design, material collecting, assembly, testing, and distribution - using Unity 3D and Vuforia as the AR development platform, Canva for graphic design, and Autodesk Maya for 3D object modeling. After undergoing functionality and compatibility testing, the application was confirmed to work properly. Subsequent User Acceptance Testing (UAT) with 34 fourth-grade students at SDS Maria Goretti showed that this media successfully improved students' understanding by 87.4%, proving that the use of AR can be an effective solution for visualizing abstract science concepts to make them easier to comprehend.
Perbandingan Teknik Penyeimbang Kelas Pada Multi-Layer Perceptron (MLP) Berbasis Backpropagation Untuk Klasifikasi Diabetes Mellitus Robby Azhar; Siska Kurnia Gusti; Iis Afrianty; Elvia Budianita
Bulletin of Computer Science Research Vol. 5 No. 6 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i6.804

Abstract

Diabetes Mellitus (DM) is a chronic disease that can lead to serious complications if not detected early; therefore, early diagnosis is highly important. One of the methods that can be applied for early diagnosis is the classification technique in data mining. However, the classification process often faces challenges due to class imbalance, which can reduce model performance. This study aims to analyze the effect of class balancing techniques on the performance of the Backpropagation Neural Network (BPNN) in classifying DM cases. BPNN is a form of Multi-Layer Perceptron (MLP) with a simple structure and the ability to solve complex problems with good accuracy. The dataset used in this study is the Pima Indians Diabetes Dataset, consisting of 768 instances, including 500 non-diabetic and 268 diabetic cases. The research was conducted using three scenarios: without balancing, Synthetic Minority Over-sampling Technique (SMOTE), and Random Under Sampling (RUS). The BPNN model was designed with two architectural variations (one hidden layer and two hidden layers), three learning rate values (0.1, 0.01, and 0.001), and a varying number of neurons. The dataset was divided using the 10-Fold Cross Validation technique. The results show that applying SMOTE achieved the best performance, with an average accuracy of 90.89%, precision of 91.22%, recall of 90.89%, and F1-score of 90.89% on the BPNN architecture with one hidden layer. Furthermore, the single hidden layer architecture proved more stable than the two hidden layers, especially when the dataset size decreased due to RUS. Therefore, the combination of SMOTE and BPNN with one hidden layer provides better performance in classifying Diabetes Mellitus cases.
Aplikasi Pembelajaran Organ Tubuh Manusia dengan Teknologi Augmented Reality Berbasis Markerless Untuk Sekolah Dasar Findyka Ayuningtyas; Asriningtias, Yuli
Bulletin of Computer Science Research Vol. 5 No. 6 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i6.806

Abstract

The rapid development of technology in the modern era has led to the education sector being required to innovate learning activities that are more interesting, effective, and efficient. In the education sector, the challenge in biology learning materials is the lack of interest in learning caused by learning media that still use printed or physical books. Physical learning media such as images and text are less effective in explaining conceptual material, especially in human anatomy material that requires students to learn with geometric visualization skills. A potential solution to this issue involves applying Augmented Reality (AR) technology through a markerless approach. The development method used is the waterfall software development method. AR is a technology that integrates digital components with the physical environment, allowing users to interact with virtual objects via mobile devices, especially those utilizing the Android operating system.  The markerless method allows students to use an AR camera and display human organ objects without using markers. This research aims to introduce human body organs with Augmented Reality technology in the form of three-dimensional objects with a markerless method to reduce complexity, provide an interactive learning experience with rotation and scaling features of three-dimensional objects to improve students' visualization understanding of anatomy, as well as quiz features to hone students understanding.
Penerapan Desain UI/UX pada Aplikasi Web Portal Berita Dengan Metode Design Thinking Melanda Sari; Reflan Nuari
Bulletin of Computer Science Research Vol. 5 No. 6 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i6.808

Abstract

The rapid advancement of technology and digitalization has significantly transformed how people access information, making web applications a primary platform for reading news. In this context, User Interface (UI) and User Experience (UX) design play crucial roles in determining the success of a news platform. This study aims to explore the application of the Design Thinking method in designing the UI/UX of the Paparan Lampung news application to enhance reader engagement and optimize user experience. The Design Thinking approach was chosen because it focuses on user needs through stages of empathy, problem definition, ideation, prototyping, and testing, enabling the creation of relevant and innovative design solutions. This research employs a descriptive quantitative method, utilizing the System Usability Scale (SUS) to assess the application’s usability level. The results show that Paparan Lampung achieved a SUS score of 88.5, categorized as “Excellent” (Grade A) and exceeding the industry acceptance threshold of 68. Furthermore, the MAUS score of 80.3 reinforces that the application is not only efficient and effective but also delivers a highly satisfying user experience. Overall, the implementation of Design Thinking has proven to enhance UI/UX design quality, directly improving user comfort and engagement. Despite the highly positive results, this study has limitations in terms of the number of respondents and the controlled testing environment. Therefore, future research is recommended to involve a larger and more diverse group of participants to obtain more comprehensive and generalizable findings.
Implementasi Metode Cosine Similarity Dalam Sistem Profiling Dosen Berbasis Data Bibliometrik Untuk Pemetaan Kompetensi Akademik Jefry Sunupurwa Asri; Firnanda Amalia; Muhammad Thifaal Dzaki; Muhammad Fikri; Ardra Rianisa
Bulletin of Computer Science Research Vol. 5 No. 6 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i6.811

Abstract

Lecturer profiling based on scientific publications is a strategic component in managing human resources in higher education institutions. The manual process of identifying lecturer competencies often requires considerable time and may lead to inaccuracies. This study aims to develop an automated application for lecturer profiling and competency mapping to relevant courses using an unsupervised text similarity approach based on the Term Frequency–Inverse Document Frequency (TF-IDF) and Cosine Similarity methods. The application was developed using the Streamlit framework with integrated data from Google Scholar, SINTA, and Scopus. The evaluation involved 50 lecturers and 120 lecturer–course pairs, measured using accuracy, precision, recall, F1-score, response time, and usability metrics. The results show an accuracy of 85.3%, an F1-score of 0.853, an average response time of 2.3 seconds, and a usability score of 86.4, which falls into the excellent category. The system is capable of displaying interactive lecturer profiles, performing competency mapping to relevant courses, and generating automatic reports in PDF format. Therefore, this application effectively supports data-driven academic decision-making processes for assigning lecturers according to their areas of expertise.
Optimalisasi Prediksi Parameter Lingkungan Menggunakan Model LSTM Multivariat dan Univariat Nilasari Yunantara, Chandra; April Firman Daru
Bulletin of Computer Science Research Vol. 5 No. 6 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i6.813

Abstract

Environmental parameter prediction plays an essential role in supporting weather monitoring and data-driven decision-making, particularly in urban areas. However, prediction accuracy is often limited by a model’s ability to capture the interrelationships among environmental parameters. This study aims to analyze and compare the performance of two Long Short-Term Memory (LSTM) approaches Multivariate and Univariate in predicting air temperature as the dependent variable. In the Multivariate model, temperature prediction is influenced by other independent variables such as humidity, pressure, and altitude, whereas in the Univariate model, temperature prediction is based solely on its historical data. The model architecture consists of three main layers an input layer, two hidden layers, and an output layer. Model performance was evaluated using Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE). The experimental results show that the multivariate LSTM model produces lower error values for temperature and pressure parameters, while the univariate LSTM model performs better for humidity and altitude. Therefore, the multivariate model is more suitable when the interrelationships among environmental parameters significantly influence prediction outcomes.
Sistem Pendukung Keputusan Penilaian Kinerja Pegawai Kantor Kepala Desa Menerapkan Metode WASPAS Rosdiana, Rosdiana
Bulletin of Computer Science Research Vol. 5 No. 6 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i6.815

Abstract

An agency cannot be separated from the role of human resources (HR) working in it. The quality of HR is one of the important factors that influences the increase in productivity and effectiveness of agency performance. However, in practice, the employee performance assessment process is often still carried out manually or based on subjective considerations, so that it has the potential to cause injustice in decision making. To overcome this problem, this study designed a decision support system (DSS) based on the [mention method, for example: Weighted Product, AHP, MOORA, or others] method to evaluate employee performance objectively and measurably. This method was chosen because it is able to compare a number of alternatives based on several predetermined criteria, such as discipline, responsibility, initiative, and cooperation. This system was designed using [mention tools or platforms if any, for example: Microsoft Excel, PHP, MySQL, etc.] and tested using employee data from related agencies. The test results show that the developed system can help decision makers in evaluating employee performance more quickly, objectively, and efficiently. With this system, it is hoped that the performance assessment process will be more transparent and accountable and can increase employee work motivation.

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