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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 329 Documents
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Perbandingan Metode MAUT dan Profile Matching Terhadap Sistem Pendukung Keputusan Seleksi Calon Paskibraka Azizah, Rizthy Shavna; Murniati, Wafiah; Mardi, Mardi
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.765

Abstract

The selection of candidates for the Flag Raising Troop (Paskibraka) requires an objective, transparent, and consistent assessment system based on physical criteria, general intelligence, personality, marching skills, and physical fitness. This study compares the Multi Attribute Utility Theory (MAUT) and Profile Matching (PM) methods in supporting selection decision making. The MAUT method produces a utility score by considering the weight of each criterion, while PM assesses the level of conformity to the ideal profile through GAP analysis grouped into Core Factor (CF) and Secondary Factor (SF). The purpose of this study is to compare the accuracy of the MAUT and Profile Matching methods in the decision support system for Paskibraka candidate selection. The calculation results show that candidate A3 obtained the highest score in both methods (MAUT = 0.970; PM = 3.600), followed by A1 (MAUT = 0.957; PM = 3.500) and A9 (MAUT = 0.918; PM = 3.450). This consistency indicates a convergence in the assessment of high-performing candidates. However, differences emerge in the middle ranks, for example, A2, which ranked 8th on the MAUT (0.856) but rose to 4th on the PM (3.100). Differences in assessment principles are the main factor: MAUT emphasizes an even distribution of scores across all criteria, while PM focuses more on fit with the ideal profile, particularly on the core criteria (CF). This finding emphasizes that the choice of methods should be tailored to selection priorities, or used in combination to obtain more accurate and objective results.
Analisis Klaster Penyebaran Berat Produk Mesin Sachet Menggunakan Metode Algoritma K-Means Ermanto, Ermanto; Surojudin, Nurhadi
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.766

Abstract

This study aims to analyze the distribution patterns of sachet machine product weights using the K-Means algorithm as a clustering technique. The dataset consists of 940 entries of primary production records, each containing ten weight measurement samples per production cycle. The data underwent a cleaning process to ensure the absence of missing values, duplicates, and outliers, followed by the selection of relevant attributes (product weight samples) and transformation using Min-Max normalization to scale all variables within the 0–1 range. The clustering process was performed iteratively by updating the centroids until convergence was achieved. The evaluation results indicate that the optimal number of clusters is three (k=3) with a Silhouette Coefficient of 0.55, reflecting a good balance between intra-cluster homogeneity and inter-cluster separation. Cluster 1 represents products with relatively low weights (8.00–8.18 grams), Cluster 2 includes medium-weight products (8.19–8.34 grams), and Cluster 3 consists of high-weight products (8.36–8.98 grams). Overall, the product weights tend to be stable with low variation, although some anomalies were observed in certain machines. These findings demonstrate that the K-Means algorithm can effectively classify product weight data, providing valuable insights for quality control, product variation identification, and minimizing risks of deviation from production standards.
Pemanfaatan Artificial Intelligence Dalam Implementasi Chatbot Helpdesk untuk Mendukung Layanan TIK Publik pada Instansi Pemerintahan Kartini, Kartini; Malabay, Malabay; Widayanti, Riya
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.769

Abstract

Public services in many government institutions are still traditional, characterized by slow processes, bureaucracy, and limited working hours. This condition makes it difficult for the public to obtain information quickly and accurately. This study aims to analyze the utilization of Artificial Intelligence (AI) in the form of chatbots as a digital innovation to improve the quality, efficiency, and accessibility of public services. The research method used is a qualitative approach through literature review, observation, and interviews with ICT Public Service staff or employees at government agency, as well as users from the community. The research findings, as presented in Table 1 in Discussion sub-chapter 3.4, show that chatbots are able to provide instant and consistent responses, operate more efficiently (saving human resources and time), respond within one minute (real-time, 24/7), support automation, and reduce the workload of government officials through interactive services available around the clock. However, key challenges remain, including limitations in natural language understanding, data security issues, and user resistance to new technologies. With appropriate development strategies and attention to digital literacy among citizens, AI-based chatbots have the potential to become an effective solution in supporting the transformation of public services toward smart, transparent, and citizen-oriented governance.
Penerapan Metode Fuzzy Sugeno Untuk Optimalisasi Persediaan Pakaian Wijaya, Agung; Putri, Raissa Amanda
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.770

Abstract

In the fashion retail industry, inventory management is a major challenge due to fluctuating and unpredictable customer demand. Errors in inventory planning may lead to overstocking or stockouts, increased storage costs, and decreased customer satisfaction. This study aims to develop a decision support system using the Sugeno fuzzy logic method to optimize clothing inventory. The input variables consist of initial stock, incoming goods, and outgoing goods, which are processed through fuzzification, inference, and defuzzification stages to produce the predicted final stock. Experimental results show that the Sugeno fuzzy model achieves better accuracy compared to conventional methods, with a Mean Absolute Percentage Error (MAPE) of 17.99%, equivalent to a prediction accuracy of 82.01%. The main contribution of this research lies in the application of the Sugeno fuzzy method to local fashion retail inventory management, which has generally been carried out manually. This approach enables the system to provide more precise stock recommendations, thereby helping stores reduce the risk of overstocking and stockouts, improve operational efficiency, and enhance business competitiveness.
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.

Page 27 of 33 | Total Record : 329

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