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INDONESIA
Jurnal Pendidikan Sains dan Komputer
Published by Information Technology and Science
ISSN : -     EISSN : 2809476X     DOI : 10.47709/jpsk
Core Subject : Humanities, Science, Education, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Education Energy Immunology & microbiology Materials Science & Nanotechnology Mathematics Physics Other
Jurnal Pendidikan Sains dan Komputer (JPSK) merupakan jurnal akses terbuka nasional yang meliputi hasil kajian ilmiah interdisipliner, orisinal dan diulas oleh mitra bestari yang kompeten di bidangnya. Lingkup jurnal ini meliputi pendidikan sains baik teori dan praktek dengan bidang ilmu pendidikan Matematika, Fisika, Kimia, IPA dan komputer. Jurnal ini juga menyediakan artikel-artikel berkualitas dengan mengikuti perkembangan ilmu pengetahuan terbaru. JPSK diterbitkan 2x setahun yaitu pada bulan Februari dan Oktober.
Arjuna Subject : Matematika - Ilmu Komputer Teoritis
Articles 212 Documents
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Perancangan Website Pendataan Troubleshooting pada Biro Teknologi Informasi Menggunakan Laravel Studi Kasus Universitas Mercu Buana: Website Design for Troubleshooting Data Collection at the Information Technology Bureau Using Laravel: A Case Study at Mercu Buana University Muhammad Ghufroon Roffif; Tamatjita, Elizabeth Nurmiyati
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7739

Abstract

Troubleshooting records at the Information Technology Bureau of Mercu Buana University are still maintained manually, resulting in difficulties tracking reports, data duplication, and delays in handling IT disruptions. These conditions reduce service effectiveness and make it difficult to conduct comprehensive performance evaluations. Therefore, this study aims to design and implement a web-based troubleshooting recording information system capable of managing disruption reports in a structured manner, monitoring repair status in real time, and providing historical data for evaluating IT service performance. The system development method used in this study is the System Development Life Cycle (SDLC), which includes the stages of needs analysis, system design, implementation, and testing. The system was developed using the Laravel framework with a MySQL database to ensure centralised, secure, and integrated data management. System testing was conducted using the black-box testing method to ensure that all functions met user requirements. The test results show that the developed system can speed up the report recording process by up to 45%, increase transparency into the status of disruption handling, and facilitate data-driven decision-making. In addition, the implementation of this system supports the incident management process in accordance with the Information Technology Infrastructure Library (ITIL) principles. It contributes to increasing the efficiency, accountability, and quality of information technology services within the Mercu Buana University environment.
Model Prediktif Kelulusan Mahasiswa Berbasis Machine Learning Menggunakan Pipeline Terintegrasi dan Hyperparameter Tuning: A Machine Learning-Based Student Graduation Prediction Model Using an Integrated Pipeline and Hyperparameter Tuning Mundirin, Mundirin; Hedin, Deden; Idawati, Idawati; Latief, Ibrahim; Lili, Mohamad
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7795

Abstract

Delays in student completion are a critical issue in higher education because they impact academic efficiency, program accreditation, and graduate quality. This study aims to develop a machine-learning-based model for predicting student graduation using an integrated pipeline. This pipeline encompasses data processing, model building, and hyperparameter optimisation. The dataset was obtained from eight semesters of student academic data, totalling 146 credits. This dataset includes both numeric and categorical variables, such as GPA, number of credits passed per semester, study load, and student background characteristics. Preprocessing was performed using ColumnTransformer, which combined StandardScaler for numeric features and OneHotEncoder for categorical features. A classification model was developed using the Random Forest algorithm and optimised with GridSearchCV to identify the optimal hyperparameter settings. Model evaluation was performed using accuracy metrics, confusion matrices, and classification reports. The findings of this study indicate that the model achieves an accuracy of 81%, suggesting a strong ability to classify students as on-time or late graduates. Feature analysis shows that the average Grade Point Average (GPA), the number of Semester Credit Units completed each semester, and consistency in study load are the main factors influencing the timeliness of study completion. The implementation of an integrated channel has proven effective in maintaining preprocessing consistency and reducing the possibility of data leakage. The developed model can be implemented as an early warning system to support data-driven academic decision-making.
Analisis Kinerja Decision Tree dan Random Forest Menggunakan Dataset Breast Cancer: Performance Analysis of Decision Tree and Random Forest Using Breast Cancer Dataset Firdaus, Uus; Alfiah, Ananda; Mohdo, Lorina
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7892

Abstract

Breast cancer is a disease with a high mortality rate in women worldwide, making early detection a crucial factor in increasing the chances of successful treatment and patient survival. Advances in computing technology, particularly machine learning, have created opportunities to use medical data to inform decision-making in the diagnostic process. This study aims to analyze and compare the performance of the Decision Tree and Random Forest algorithms in classifying breast cancer using the Wisconsin Breast Cancer Dataset. The dataset comprises 569 data points with 30 numeric attributes representing cancer cell characteristics and a class label indicating benign or malignant cancer. The research stages include data preprocessing, splitting the data into training and test sets (80:20), applying the classification algorithm, and evaluating model performance using accuracy, precision, recall, and F1-score metrics. The test results show that the Random Forest algorithm outperforms the Decision Tree. Random Forest achieved an accuracy of 98.68% on the training data and 95.61% on the test data, while Decision Tree achieved an accuracy of 96.92% on the training data and 91.23% on the test data. This difference indicates that Random Forest has better generalization capabilities and is more resistant to overfitting. The findings of this study indicate that Random Forest is more effective for data-based breast cancer classification than Decision Tree. Therefore, the Random Forest algorithm is recommended as a more reliable method to support decision support systems in early breast cancer detection.
Model Manajemen Penyimpanan Data Berbasis Pipeline Produksi Film Animasi 3D: Pipeline-Based Data Storage Management Model for 3D Animation Film Production Yuniawan, Aryanto; Sa`di, Ahmad; Anggono, Eko Tri
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7952

Abstract

The 3D animated feature film industry generates a large and diverse volume of digital data due to the complexity of its production pipeline, which spans multiple stages and departments. Each stage of the production pipeline, from pre-production to post-production, generates data with distinct characteristics, access patterns, and importance levels. However, in practice, data storage management is often carried out uniformly, without consideration of its relationship to the production flow. This study aims to develop a data storage managementmodel grounded in the production pipeline of the 3D animated feature film industry. The study uses a descriptive approach, supported by applied modeling, and draws on observations, interviews, and documentation from the 3D animation production environment. The model is developed by identifying production pipeline stages, classifying data types (production, non-production [organizational operations], backup, and archive), and analyzing access characteristics and data storage needs. The results show that the proposed model can map the relationships among production pipeline stages, data types, and appropriate storage strategies, thereby forming a more systematic and contextual data management framework. The implementation of the model in a 3D animation production case study shows that adjusting storage strategies based on the production pipeline and data characteristics is realistic and applicable. This model is expected to serve as a reference for managing data storage in the production environments of 3D widescreen animated films.
Pengembangan Kuis Interaktif Mobile untuk Tahfizh Al-Qur’an dengan Metode MDLC: Development of a Mobile Interactive Quiz for Memorizing the Qur'an Using the MDLC Method Sundara, Denny Cahyadi; Marzal, Jefri; Bintana, Rizqa Raaiqa
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7989

Abstract

This study aims to design and build a mobile-based interactive quiz application as a learning medium at Attaufiq Jambi Private Islamic Elementary School. The research background stems from the need for more engaging and interactive learning media, particularly to support memorization of the Qur'an, which has so far relied on conventional, monotonous methods. To address this issue, this study uses the Multimedia Development Life Cycle (MDLC), which comprises six stages: concept, design, material collection, assembly, testing, and distribution. The application is named Attaufiq Quiz, with main features including interactive quizzes, audio recitations, and simple yet attractive visual displays. The material presented focuses on short surahs from Juz 30 that are relevant to the elementary school curriculum, enabling students to learn independently or with teachers. The test results show that this application meets the functional requirements, with all features running as designed. Subject teachers' validation of the material found that the quiz content is in accordance with the curriculum and suitable for use.In contrast, language validation found that the language used conforms to Indonesian language rules. The final stage, a Perceived Ease of Use (PEOU) test, was conducted with 22 sixth-grade students, yielding a score of 91.27% and a rating of very good. Thus, the Attaufiq Quiz app is considered easy to use and can support memorizing the Quran more effectively, interactively, and enjoyably.
Analisis Kepatuhan Aksesibilitas Web Pemerintah Provinsi DIY Berdasarkan Standar WCAG 2.1. dengan WAVE API : Analysis of the Accessibility Compliance of the Yogyakarta Provincial Government's Website Based on WCAG 2.1 Standards with the WAVE API Nurrohmah, Isnaeni
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7996

Abstract

Digital transformation requires the government to provide inclusive services for all people, including people with disabilities. However, a paradox often arises between the excellence of visual communication and compliance with technical accessibility standards. This study aims to evaluate the level of accessibility compliance of the Yogyakarta Provincial Government website (jogjaprov.go.id)—winner of the 2025 Public Relations Media Award—with the Web Content Accessibility Guidelines (WCAG) 2.1 standard. Using a quantitative descriptive design, this study automatically evaluates 30 purposively selected sample pages using the WAVE API to map the website's quality against the POUR (Perceivable, Operable, Understandable, Robust) principles. The results show excellent aggregate performance with an average AIM score of 9.1. However, in-depth analysis reveals non-compliance with accessibility principles on the main page (homepage), which has the lowest AIM score (5.1) due to 26 errors and 12 contrast errors.Furthermore, the most significant finding indicates the presence of Institutionalized Accessibility Barriers in the form of systemic violations of heading structures (h1 issues) on 96.7% of pages, which proves a structural deficit in the core template. Theoretically, this study introduces the concept of the Intra-domain Accessibility Divide, in which a gap in access quality arises within a domain due to unequal development priorities between aesthetics and inclusivity. The policy implications call for reforming government award assessment criteria and integrating WCAG standards into the system development life cycle (SDLC) to realize truly inclusive digital governance.
Pengembangan dan Optimasi Kalman Filter Adaptif Multi-Timeframe dalam Kerangka State-Space untuk Prediksi Arah Harga Valuta Asing: Development and Optimization of Multi-Timeframe Adaptive Kalman Filter in State-Space Framework for Foreign Exchange Price Direction Prediction Baradja, Abdillah; Sukoco, Sukoco; Mukti, Bayu
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.8007

Abstract

The foreign exchange market is non-stationary, noisy, and highly sensitive to changes in information, making short-term price direction prediction a significant challenge. Although the Kalman Filter has been widely used within a state-space framework for trend and dynamic parameter estimation, most previous research has focused on statistical accuracy without directly linking it to actual trading performance. This study aims to develop and evaluate an adaptive Kalman Filter-based forex price direction prediction model and empirically test its implications for the performance of algorithmic trading systems. The study uses a quantitative experimental approach, analyzing historical EUR/USD data across the H1, H2, H3, and H4 timeframes over 1 year. The state-space-based Kalman Filter model is implemented in a MetaTrader 5 Expert Advisor and compared with the Moving Average Crossover strategy and the classic Kalman Filter. Evaluations are conducted at the prediction and trading levels using Total Net Profit, Profit Factor, Sharpe Ratio, and Drawdown. The proposed model demonstrates consistently positive performance across all timeframes, with a Profit Factor of 1.39–2.13 and a Sharpe Ratio of up to 5.70, significantly outperforming the technical baseline and the classic Kalman Filter, which exhibit unstable results. The integration of the Kalman Filter approach into an algorithmic trading system improved signal quality and risk efficiency during testing.
Peningkatan Wisata Desa Sindangjaya Cipanas Melalui Pelatihan Pelayanan Prima: Improving Tourism in Sindangjaya Village, Cipanas, Through Excellent Service Training Adriyanto, Hendaris; Melati, Dewi; Subakti, Agung Gita
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7862

Abstract

The development of community-based tourism villages requires competent human resources (HR), especially in the area of tourist services, which are key to creating visitor satisfaction and loyalty. Good service quality not only influences the destination's image but also contributes to the local community's economic and social sustainability. Sindangjaya Village, Cipanas District, Cianjur Regency, has attractive natural tourism potential and homestay-based accommodations that continue to grow as the number of tourist visits increases. However, this potential has not been fully realized due to inadequate service standards, necessitating systematic efforts to improve the local community's human resource capacity. This study aims to improve the human resource capacity of the Sindangjaya Village community through excellent service training using an Asset-Based Community Development (ABCD) approach that emphasizes the use of local assets and the community's own potential. The method used is participatory community service activities, including training, mentoring, and outreach, for members of the Tourism Awareness Group (Pokdarwis), the main actors in managing the tourism village. Data collection was carried out through participatory observation, in-depth interviews, and post-test evaluations using pre-test and post-test instruments to measure increases in participants' knowledge and understanding. The results of the activity showed a significant increase in participants' understanding of the concepts of excellent service and effective service communication techniques, the implementation of environmental cleanliness and comfort, and a growing collective awareness of the importance of service quality in supporting the competitiveness and sustainability of tourist villages. These findings confirm that strengthening human resource capacity through local assets and the ABCD approach plays a strategic role in realizing independent, professional, and sustainable tourist villages.
Pengaruh Penggunaan Animasi Model TGT terhadap Hasil Belajar PKN Kelas IV SDN 61 Banda Aceh: The Effect of Using TGT Model Animation on Civics Learning Outcomes of Class IV SDN 61 Banda Aceh Sakdiah, Sakdiah; Musdiani, Musdiani; Helminsyah, Helminsyah
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7914

Abstract

This study evaluates the effectiveness of combining the Teams Games Tournament (TGT) learning model with animated audiovisual media in improving fourth-grade students' learning outcomes at SDN 61 Banda Aceh. The background of this study is low student interest and learning outcomes due to monotonous conventional methods, with the average initial score (pretest) at 65, which is still below the KKM standard of 75. Using a one-group pretest-posttest design with 27 students in the even semester of 2025/2026, data were analyzed using the Wilcoxon Signed-Rank test. The results showed a significant positive effect, with the average score increasing to 84.26. It was concluded that integrating animated media with the TGT model created an interactive, effective learning environment that improved students' cognitive understanding. Suggestions put forward include: for teachers, apply this strategy routinely in Civics and other subjects; for schools, provide multimedia facilities and teacher training; for future researchers, use a quasi-experimental design with a control group to strengthen validation.
Keterkaitan Kecerdasan Emosional dan Soft Skills Siswa dalam Pembelajaran Jasmani: Analisis Literatur 2020–2025: The Relationship Between Emotional Intelligence and Students' Soft Skills in Physical Education: A Literature Analysis 2020–2025 Gregorius Andrea Mustikaningrat, Gregorius Andrea Mustikaningrat; Augustina Sulastri, Augustina Sulastri
Jurnal Pendidikan Sains dan Komputer Vol. 6 No. 01 (2026): Artikel Riset, February 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v6i01.7575

Abstract

This study aims to analyse the relationship between emotional intelligence and the development of students' soft skills in the context of physical education. The study's background is the growing need to master non-technical skills such as cooperation, empathy, and emotional regulation in the modern world of education. Physical activity is considered to have great potential in stimulating these abilities through social interactions and competitive situations that require self-control. This study used the Systematic Literature Review method to examine six national and international articles published between 2020 and 2025, sourced from Google Scholar, ScienceDirect, DOAJ, and SINTA databases. The analysis was conducted using Goleman's theoretical framework of emotional intelligence, which includes five main dimensions: self-awareness, self-control, motivation, empathy, and social skills. The study's results indicate that emotional intelligence positively affects students' soft skills development, particularly in communication, discipline, cooperation, and social empathy. Physical activity has been shown to increase self-confidence, reduce anxiety, and strengthen students' mental toughness and commitment to goals. Conceptually, this research confirms that physical education serves as a strategic medium for character education grounded in emotional intelligence, while also providing direction for curriculum development that balances the cognitive, affective, and social aspects of students in the 21st-century educational era.

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