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Bulletin of Computer Science Research
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27743659     DOI : -
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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 476 Documents
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Perancangan Infrastruktur Virtual Laboratory Multi-Layanan Berbasis Cloud Computing Menggunakan Metode NDLC Metalika Gunena; Anritsu Steven Christian Polii; Antonius P. G. Manginsela; Franky Manoppo; Olga Engelien Melo
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.v6i5.1253

Abstract

The limited hardware specifications of student devices remain a major obstacle in conducting computation-based practical courses in higher education, particularly in practicums that require applications with high computational resource demands, such as programming software, network simulation tools, and various other supporting applications, which often cannot run optimally on student devices with low specifications. This condition causes practical learning to become inconsistent and highly dependent on the capability of each student's personal device. Based on this problem, this research aims to design and simulate a cloud computing-based Virtual Laboratory system that can be accessed through a web browser without requiring high hardware specifications on the user side, while also contributing an integrated virtual laboratory architecture that combines three cloud computing service models simultaneously, namely Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). As a solution, IaaS is built using Proxmox Virtual Environment (VE) as a type-1 hypervisor, pfSense as a virtual firewall, Ubuntu Server as the service host, and Docker as the containerization platform, along with Cloudflare Tunnel using a Zero Trust architecture to ensure accessibility from outside the campus network without dependence on a static public IP. The system is equipped with multi-role authentication (student, lecturer, admin) based on Student ID Number (NIM) or National Lecturer ID Number (NIDN) verification and OTP verification, a QR code-based Attendance module integrated with the Timetable module, and a main portal built as an installable Progressive Web App (PWA) on user devices. The system was developed using the Network Development Life Cycle (NDLC) method. Preliminary functional testing results show that all services in the Programming Class and Network Class, including the Attendance and Timetable modules, were successfully accessed from outside the campus network, and the multi-role authentication system functioned as designed.
Prediksi Time Series Permukaan Air Sungai Menggunakan Long Short-Term Memory-Autoregressive Integrated Moving Average Norita Febriyanti; Michael Ardita; I Komang Somawirata
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.v6i5.1262

Abstract

River water level prediction is an essential component of flood early warning systems, as it provides information on potential water level increases before overflow occurs. The Kebonagung River in Sumenep Regency was selected as the study area due to its fluctuating water levels, which are influenced by variations in river discharge and water volume, thereby requiring a prediction model capable of capturing both linear and nonlinear patterns. The Autoregressive Integrated Moving Average (ARIMA) model is effective in modeling linear and seasonal time-series patterns, whereas the Long Short-Term Memory (LSTM) model is capable of learning nonlinear relationships and long-term temporal dependencies with high accuracy. This study aims to compare three prediction approaches: Long Short-Term Memory (LSTM), ARIMA-based discharge integrated with LSTM, and the Hybrid Autoregressive Integrated Moving Average–Long Short-Term Memory (ARIMA–LSTM) model for predicting river water levels using one year of historical data collected at one-hour intervals, consisting of water level, discharge, and water volume variables. Model performance was evaluated using Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The experimental results show that the LSTM model achieved an RMSE of 128.15, an MAE of 96.61, and a MAPE of 3.56%, while the ARIMA (discharge)-LSTM model obtained an RMSE of 127.63, an MAE of 96.33, and a MAPE of 3.55%. The Hybrid ARIMA–LSTM model produced the lowest RMSE of 127.06, although its MAE and MAPE were slightly higher at 96.81 and 3.59%, respectively. These findings indicate that integrating ARIMA and LSTM can reduce large prediction errors, resulting in a lower RMSE; however, the performance improvement over the other models is not substantial because all models exhibit relatively similar error levels. Therefore, the Hybrid ARIMA–LSTM model is better regarded as an approach that improves prediction stability rather than one that delivers a significant increase in predictive accuracy. The main contribution of this study lies in the evaluation of two ARIMA–LSTM integration strategies, namely the use of ARIMA-based discharge predictions as input features for the LSTM model and a residual-based Hybrid ARIMA–LSTM approach, using the same hydrological dataset to enable an objective comparison of the characteristics, strengths, and limitations of each approach. The findings are expected to provide a useful reference for the development of river water level prediction models to support time-series-based flood early warning systems.
Pengembangan Sistem Monitoring Data Keuangan Berbasis Web Menggunakan Metode MOORA Anief Fauzan Rozi; A. Sidiq Purnomo; Dina Yulina Heriyani
Bulletin of Computer Science Research Vol. 6 No. 6 (2026): October 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i6.1189

Abstract

Financial data monitoring is a crucial aspect of vocational high school administration. SMK Ma’arif 1 Temon still performs financial recording and recapitulation manually and semi-computerized using office applications, potentially causing data duplication, reporting delays, and weak long-term decision-making. This research aims to develop a web-based financial data monitoring system and apply the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to rank student payment priorities. Software development uses the System Development Life Cycle (SDLC) waterfall model, while the decision model uses MOORA with three objective criteria: SPP payment (C1, benefit, weight 0.5), arrears (C2, cost, weight 0.3), and SPP payment timeliness (C3, benefit, weight 0.2). The result is a web-based financial monitoring system prototype. MOORA calculation shows that Alternative-5 and Alternative-9 obtained the same highest optimization value of 0.1854, while Alternative-16 obtained the lowest value of -0.0225. This negative value is mathematically valid as a relative preference score, not a monetary amount. Black-box functional testing shows that all 11 main features are successfully implemented. This system is expected to help schools monitor, recapitulate, and make financial decisions more effectively, efficiently, and measurably.
Peningkatan Akurasi Klasifikasi Tutupan Lahan Menggunakan Histogram Spesifikasi dan Random Forest Berbasis Citra Sentinel-2 Petricia Oktavia; Muhamad Meky Frindo
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.v6i5.1276

Abstract

Land cover conversion dynamics in Penajam Paser Utara (PPU) Regency have accelerated drastically following its designation as the core and buffer zone of the Nusantara Capital City (IKN). Optical remote sensing monitoring using Sentinel-2 imagery faces severe physical constraints from tropical atmospheric interference, haze, and pronounced spectral confusion between natural rainforest canopies and oil palm plantations exhibiting overlapping chlorophyll biomass reflectance. This study aims to improve the accuracy and robustness of 6-class land cover classification (Forest, Cultivated Vegetation, Settlement, Water Body, Bare Land, and Oil Palm) by integrating Histogram Specification (HistSpec) radiometric normalization, feature engineering of 9 spectral attributes, and Random Forest (RF) ensemble classification. The performance of RF was systematically benchmarked against six alternative Machine Learning algorithms (Extra Trees, Decision Tree, Gradient Boosting, Logistic Regression, Naive Bayes, and SGD Classifier) using 675 points (472 training and 203 independent testing points). Experimental findings demonstrate that Histogram Specification coupled with Random Forest attained stable performance, Overall Accuracy (OA) of 79.80% (an improvement from 78.33% on the RAW scenario) and a Cohen's Kappa coefficient of 0,7549. In contrast, Gradient Boosting exhibited severe overfitting on raw imagery (accuracy plummeted from 83.25% on RAW to 78.33% on HistSpec). Given its high computational efficiency (~123 ms) and scale-invariance, Random Forest proves to be the most dependable model for generating distortion-free thematic land cover maps to support sustainable spatial planning in the IKN region.
Konsolidasi Pelaporan Multi-Divisi pada Sistem Informasi Eksekutif Berbasis Web Menggunakan Rapid Application Development Riesty Herlia Mawarti; Novri Hadinata
Bulletin of Computer Science Research Vol. 6 No. 6 (2026): October 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i6.1348

Abstract

Executive decision making requires concise, up-to-date, and consolidated information, whereas operational reporting in energy support service companies is generally still scattered across divisions, so the information has to be collected and checked manually before it can be used. This research aims to design and build a web-based Executive Information System that consolidates the reports of four operational divisions, namely General Affair, Human Resource Development, Engineering Rig & Development, and Transport, into a single shared reporting structure and presents them as executive indicators. The system was developed using the Rapid Application Development method in four phases: requirements planning through observation, interviews, documentation, and literature study; user design producing process models, database structure, indicator mapping, and twelve interface wireframes; construction using the PHP programming language and a MySQL database iteratively through prototypes; and cutover consisting of final testing, user training, and system implementation. This research offers three contributions: (1) the design of a lightweight consolidation layer that maps the heterogeneous indicators of four divisions into a single shared reporting structure, so that the benefits of an Executive Information System can be obtained without building a data warehouse; (2) the application of Rapid Application Development in the Executive Information System domain, which has so far been dominated by sequential approaches, with the executive involved directly in every prototyping cycle; and (3) a tiered presentation pattern from summary to detail combined with role-based access control, so that inter-divisional data confidentiality is preserved when the reports are consolidated. The resulting system implements fifteen functional requirements across twelve interface pages and shortens the executive information retrieval flow from five manual cross-division steps into a single dashboard access, while reducing the number of information sources that must be opened from four divisional report files into one integrated interface, equivalent to an 80% reduction in the number of steps and a 75% reduction in the number of information sources. Black box testing of nine scenarios representing all functional requirements produced valid results in every scenario (100%), therefore the system is declared functionally valid within the tested prototype scope. The limitations of this research are that the system still runs on a local network, data updates depend on divisional user input, and advanced analytics such as trend analysis, forecasting, and anomaly detection are not yet available; these become the agenda for the further research.
Sistem Informasi Penerimaan Siswa Baru Terintegrasi Berbasis Web Menggunakan Extreme Programming Dinda Fahmilia; Irman Effendy
Bulletin of Computer Science Research Vol. 6 No. 6 (2026): October 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i6.1354

Abstract

The new student admission process in many vocational high schools is still carried out manually, causing accumulated paper files, recording errors, slow data retrieval, and delayed reporting. Prior studies generally stop at digitising the registration form and have not integrated the entire admission service chain into a single system. This study aims to design, build, and test a web-based admission information system that integrates seven service stages sequentially, namely public information delivery, online account registration and enrolment, payment proof upload, payment verification, online selection test, self-service admission announcement based on the registration number, and recapitulation as well as cross-period comparison reporting. The novelty lies in integrating that service chain into one application with three-role access control and built-in framework security mechanisms. The system was developed using the Extreme Programming method through the planning, design, coding, and testing stages with the Laravel framework and a MySQL database consisting of eleven relational tables. Functional testing applied black box testing based on equivalence partitioning and boundary value analysis covering seventeen positive scenarios and fifteen failure scenarios, complemented by boundary input validation and verification of security mechanisms against SQL injection and XSS. The test results show that the system meets the functional needs of the admission committee and prospective students and rejects invalid input as designed, making it feasible for improving the efficiency, accuracy, and traceability of admission administration.
Klasifikasi Tingkat Kepuasan Tamu Terhadap Pelayanan Hotel Menggunakan Metode Decision Tree Junaidy Pratama; Amelia Yusnita; Renni Mayasari
Bulletin of Computer Science Research Vol. 6 No. 6 (2026): October 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i6.1357

Abstract

In the highly competitive era of the modern hospitality industry, service quality, cleanliness, and the completeness of facilities are the main pillars in maintaining guest loyalty and business reputation. Hotel NICI, as one of the accommodation service providers, faces challenges in extracting valuable insights from the accumulation of large-volume guest feedback survey data. This study aims to systematically classify the level of guest satisfaction with Hotel NICI's services using a Decision Tree machine learning algorithm based on survey data. The dataset used covers various evaluation dimensions, particularly guests' perceptions of staff service quality, the cleanliness level of hotel areas, and the functionality of the facilities provided. To produce a valid model, the raw data first undergoes a series of rigorous preprocessing stages. These stages include handling missing values using imputation methods, normalizing nomenclature or column names for data consistency, as well as[1] converting qualitative textual responses into structured categories, namely 'satisfied', 'fairly satisfied', and 'dissatisfied'. To determine the global sentiment label, a majority voting approach is applied to consolidate the three satisfaction dimensions into a single target variable representing the overall guest satisfaction category. Subsequently, these categorical features along with the target variable are numerically encoded using the label encoding technique, then divided into training data (training set) and testing data (testing set) with a proportional ratio of 80:20. The Decision Tree Classifier model is trained by optimizing the tree depth parameter to prevent overfitting.
Implementasi Sistem Digital dalam Pengelolaan Surat Izin Keluar Karyawan dari Area Perusahaan Terintegrasi Notifikasi E-Mail Riska Hidayah Putri; Dendy K Pramudito; Aswan Supriyadi Sunge
Bulletin of Computer Science Research Vol. 6 No. 6 (2026): October 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i6.1359

Abstract

Paper-based employee exit permits hinder approval tracing, data recapitulation, and coordination with security personnel. This study implements SIKAK Online, a web-based work-area exit permit system integrated with email notifications at PT Vision Ease Asia. Development followed a prototyping approach comprising requirements communication, rapid design, prototype construction, user evaluation, and refinement. Requirements were gathered through observation, interviews, and document review, and the application was developed using PHP and MySQL. Evaluation comprised black-box functional testing, checks covering ten security aspects, and a 20-item Likert-scale questionnaire administered to 46 respondents. The test summary reported that all 24 functional scenarios passed and that security checks produced responses consistent with the mechanisms examined. Of 920 possible item responses, 916 valid responses yielded an actual score of 4,065 out of an ideal score of 4,580, equivalent to 88.76%; perceived usefulness obtained the highest indicator score, 90.43%. The questionnaire results describe users’ assessments of the system. This study contributes an implemented exit–return permit workflow integrating submission, supervisor approval, email notifications, monitoring by security personnel, reporting, and activity logs. Its empirical contribution is an initial evaluation of functionality, security mechanisms, and user perceptions to inform the development of traceable permit administration in a manufacturing setting. The findings support an initial evaluation of digital permit administration, with further research needed on service-time measurement, instrument validation, and more extensive security testing.
Segmentasi Permintaan Pelanggan Paket Dekorasi Wedding Menggunakan K-Means Berbasis Web Nuraina Nuraina; Hadi Zakaria
Bulletin of Computer Science Research Vol. 6 No. 6 (2026): October 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i6.1361

Abstract

This study aims to analyze customer demand segmentation for wedding decoration packages using a web-based K-Means algorithm at PT. WPD. The research problem is the manual processing of historical customer data, which requires considerable time and may cause errors in grouping. The dataset consists of 250 historical customer records randomly selected from 500 transaction records for the January–December 2025 period to obtain a representative sample and accelerate model testing without reducing the variation in customer characteristics. The modeling attributes include package price or budget, decoration theme, number of add-ons, and venue scale, with categorical attributes (decoration theme and venue scale) converted into numerical values through label encoding before all numerical attributes were normalized using Min-Max Normalization. The research stages consist of observation, interviews, literature study, data collection, preprocessing, normalization, cluster determination (K=3) using the Elbow method based on the Within-Cluster Sum of Squares (WCSS) value, K-Means implementation, web-based system implementation, and testing. The analysis produced three customer segments: an economy/budget segment containing 60 customers, a middle/personalization segment containing 50 customers, and a premium/exclusive segment containing 140 customers. The premium segment is the largest group and is dominated by customers choosing the Classic International Elegance package with high budgets, extensive add-ons, and large-scale venues. The web-based system successfully automates data processing and clustering and provides analytical results to support evaluation and marketing strategies. A questionnaire involving 20 respondents on user acceptance and perceived usefulness of the system resulted in a score of 88%, categorized as very strong, reflecting user acceptance of the system rather than the accuracy of the K-Means algorithm.
Analisis Korelasi Dimensi End User Computing Satisfaction (EUCS) terhadap Kepuasan Pengguna Internal Website Pemerintahan Daerah Muhammad Habib; Kiky Rizky Nova Wardani
Bulletin of Computer Science Research Vol. 6 No. 6 (2026): October 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i6.1381

Abstract

Local government websites are usually evaluated from the perspective of the public as external users, whereas the perceptions of internal users who are close to the information provision process remain rarely examined, particularly for provincial communication and informatics office websites; prior studies on government websites also tend to involve the public as respondents or stop at describing satisfaction per dimension without testing which dimension is most strongly associated with overall satisfaction. This study aims to measure the satisfaction of internal users with the South Sumatra Provincial Communication and Informatics Office (Diskominfo) website and to identify the End User Computing Satisfaction (EUCS) dimensions most strongly associated with overall user satisfaction. Data were collected through a five-point Likert questionnaire from 80 purposively selected Diskominfo employees and analyzed using validity testing, reliability testing, mean analysis, and Pearson correlation. All items were valid and all dimensions were reliable (Cronbach’s Alpha 0.779–0.842). Mean scores of the five dimensions ranged from 3.00 to 3.15 (moderately satisfied), with Ease of Use the highest (3.15) and Accuracy the lowest (3.00). Correlations with overall satisfaction were strongest for Format (r = 0.78) and Content (r = 0.71), while Ease of Use (r = 0.45), Accuracy (r = 0.40), and Timeliness (r = 0.32) showed lower correlations. These findings indicate association rather than causation and apply only to the study sample. The contribution of this study is to provide empirical evidence on the EUCS dimensions most strongly associated with internal user satisfaction on a provincial communication and informatics office website, providing a basis for prioritizing improvements in display quality and content completeness, and for strengthening the verification of information accuracy.

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