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Journal of Practical Computer Science (JPCS)
Published by Universitas Pelita Bangsa
ISSN : -     EISSN : 28098137     DOI : https://doi.org/10.37366/jpcs
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Journal of Practical Computer Science (JPCS) sebagai media kajian ilmiah dari hasil penelitian, pemikiran dan kajian dan implementasi berkaitan dengan bidang Ilmu Komputer Praktis. Fokus dan ruang lingkup Journal of Practical Computer Science (JPCS) meliputi: - Rekayasa Perangkat Lunak - Kecerdasan Buatan - Data Mining - Machine Learning - Internet of Things - Jaringan Komputer - Keamanan Informasi - Topik kajian lain yang relevan
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 48 Documents
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Analisis Pemanfatan Pemodelan Data Mining untuk Pola Permainan Timnas Sepakbola Ardiantoro, Luki; Ristono, Joko
Journal of Practical Computer Science Vol. 4 No. 2 (2024): November 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v4i2.6074

Abstract

Football is a sport that has a very complex variety of tactics, strategies and formations. In this study, the researcher observed and studied the game patterns, tactics and game strategies applied by the Indonesian men's national football team. The methods used are the FP-Tree algorithm and FP-Growth Data Mining to learn the tactical patterns used in the match. Data is collected from a variety of secondary sources, the internet, and match recordings. The purpose of the research is to model the national team's game activities to be simulated with a data mining algorithm, so that competitive game level standards are obtained from national teams that are able to compete at the Asian level. This can be the standard for the quality of performance and coaches of the national team in the next era. The result obtained is that the data mining algorithm can be used to analyze the game pattern of a football team
Sistem Informasi Pencatatan Hafalan Al-Qur’an dan Iqro Berbasis Website pada TPA Pesayidan Kota Cirebon Nurpuriani, Zahrina; Nurpatimah, Suci; Asfi, Marsani
Journal of Practical Computer Science Vol. 4 No. 2 (2024): November 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v4i2.5051

Abstract

This research aims to design and develop a web-based information system for recording Quran memorization and Iqro at TPA Pesayidan, Kota Cirebon. The system is expected to facilitate the process of recording and monitoring students' memorization progress and to reduce the errors commonly encountered with manual methods, specifically conventional record-keeping in achievement books. The primary issues addressed include inaccuracies and inefficiencies in managing memorization data using traditional methods. To address these problems, the research employed direct observation, literature review, system design analysis, system development, implementation, and system testing. The resulting information system allows educators to record, monitor, and evaluate students' memorization more effectively and efficiently. System testing indicates that the web-based system significantly improves the accuracy and efficiency of managing memorization data and accelerates the evaluation process for teachers. In conclusion, the implementation of this system has the potential to enhance the quality of learning and provide significant benefits to TPA administrators in managing students' memorization data. The results of system testing demonstrate the success in overcoming the limitations of manual recording with a more structured and measurable solution
Pengembangan Sistem Aplikasi E-Kaizen Berbasis Website Menggunakan Metode Agile (Studi Kasus PT Cataler Indonesia) Maulana, Donny; Surojudin, Nurhadi; Juluw, Sephia Maharani Niki
Journal of Practical Computer Science Vol. 4 No. 2 (2024): November 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v4i2.5233

Abstract

Technological developments are increasingly developing with technological developments, the activities carried out benefit many parties, one of which is in the manufacturing industry. PT Cataler Indonesia is still experiencing difficulties in the keizen application process because it still uses manual, namely using Microsoft Excel, data collection is in the form of paper, this is prone to data loss or document damage. Therefore, it is necessary to carry out research to develop a website-based e-kaizen application system. The aim of this research is to make it easier for employees to submit kaizen applications and process kaizen data. The method used is the Agile Method, a software development that emphasizes flexibility and responsiveness to change. In implementing the e-kaizen system, it uses the Javascript programming language and Firebase as the database. Based on the research, it can be concluded that the development of a website-based e-kaizen application system that replaces manual processes really supports the fulfillment of needs quickly, accurately and with more updates.
Identifikasi Kerentanan Website untuk Meningkatkan Keamanan Menggunakan Open Source Security Testing Methodology Manual Rusdan, Muchamad; Hendayun, Mokhamad
Journal of Practical Computer Science Vol. 4 No. 2 (2024): November 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v4i2.5427

Abstract

This study aims to identify and analyze security vulnerabilities on the online learning website of Utama University using the Open Source Security Testing Methodology Manual (OSSTMM). This method offers a structured framework for security testing with a systematic and evidence-based approach. The research findings indicate several vulnerabilities in authentication mechanisms, input validation, SSL/TLS configuration, and API security. The identified vulnerabilities include weaknesses in authentication mechanisms against brute force attacks, input validation susceptible to injection attacks, SSL/TLS configuration not meeting security standards, and inadequate API security. The mitigation recommendations include implementing CAPTCHA, limiting login attempts, using prepared statements, enhancing SSL/TLS configuration, and implementing security headers such as X-Frame-Options, Content-Security-Policy, and X-Content-Type-Options. By applying these recommendations, the overall security level of the website is expected to improve, ensuring the confidentiality, integrity, and availability of user data, and increasing trust in the university's digital services.
Analisis Big Data Kesiapan Digital Global Menggunakan PCA dan FASTCLUS Setiawan, Ariyono; Yudianto, Prima Yudha; Ika, Ni Made; Masdiyas, I Gede Susrama
Journal of Practical Computer Science Vol. 5 No. 2 (2025): November 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i2.6075

Abstract

This study aims to identify global digital readiness patterns using an innovative big data approach by integrating Principal Component Analysis (PCA) and the FASTCLUS clustering algorithm. By analyzing 1,076 observations from 2000 to 2023, this study focuses on four key indicators: secure server deployment and ICT infrastructure index. Referring to the Digital Readiness Framework, this study positions digital infrastructure and cybersecurity as the foundation of national digital capacity. PCA results show that two main components explain 56.35% of the total variance, and the clustering process produces strong segmentation with Pseudo F = 1275.85 and R² = 70.4%. Three digital readiness clusters were successfully identified: advanced (4 countries), moderate (64 countries), and transitional (1008 countries), each exhibiting distinct infrastructure and digital index characteristics. This study contributes a replicable, globally scalable classification framework for comparing digital readiness across countries. Its originality lies in the integration of big data techniques and unsupervised learning into national digital readiness assessments. These findings are important for supporting data-driven digital policy formulation, particularly for developing countries in designing more precise and contextual ICT resource allocation strategies.
Prediksi Risiko Hipertensi Dini di Puskesmas Sukabumi Menggunakan Algoritma Support Vector Machine (SVM) Mubharak, Gilang Fauzul; Asriyanik, Asriyanik; Prajoko, Prajoko
Journal of Practical Computer Science Vol. 5 No. 2 (2025): November 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i2.6109

Abstract

Perancangan dan Analisis Optimasi Metode Akuisisi Disk Paralel Menggunakan Python Thread dan Multiprocess Pada Odroid H4 Plus Nugroho, Catur Adi; Sabila, Fadlilah Izzatus; Fauziah, Fauziah; Sholohati, Ira Diana
Journal of Practical Computer Science Vol. 5 No. 2 (2025): November 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i2.6382

Abstract

Digital data acquisition in a forensic context requires high efficiency, especially when handling large-capacity storage media with limited power consumption devices such as Single Board Computers (SBCs). This study aims to design and evaluate a parallel disk acquisition tool based on the Odroid H4 Plus SBC with a multiprocess and thread approach. Three methods are compared: Serial DC3DD, Parallel DC3DD, and the Designed Method (parallel multiprocess and thread). Evaluations are conducted on various disk sizes (4GB, 16GB, 240GB, and 500GB) and two media types (USB and SATA), with key metrics including execution time, throughput, memory (RAM) usage, and hash validity. The test results show that the design method has the most efficient execution time, with significant time savings especially on large disks. The highest throughput is also achieved by this method, especially on SATA media. In terms of memory consumption, this method shows an increase in RAM usage of up to 32 MB, which is still within the light and efficient limits for SBC devices. All methods produce hash values identical to the reference hash, proving that data integrity is maintained. These findings demonstrate that a multiprocess and thread-based parallel approach effectively improves digital forensic acquisition performance significantly without sacrificing accuracy or resource efficiency. Future research can focus on optimizing buffer management, supporting a higher number of disks simultaneously, and integrating automation into a web-based interface to improve portability and ease of use
Pengembangan AI Generatif ChatBot berbasis Mobile App dengan MIT App Inventor Suharto, Agus; Hartono, Rahmat
Journal of Practical Computer Science Vol. 5 No. 2 (2025): November 2025
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v5i2.6395

Abstract

This research explores the integration of generative artificial intelligence (AI) into mobile app development using MIT App Inventor, a visual programming platform widely adopted in educational settings. As generative AI technologies such as Large Language Models and image synthesis tools become more accessible, the potential for significantly enhancing creativity, personalization, and automation in mobile apps becomes clear. The research presents a prototype chatbot application with AI to a dynamic story generator built using Web App Inventor components to interact with external AI APIs. Through usability testing with high school students to evaluate technical feasibility, user experience, and pedagogical value, the research shows that generative AI can enrich learning outcomes and application functionality, although challenges remain in managing latency, API complexity, and ethical considerations. . The results of the study were evaluated using EUCS and Likert Scale as measurements, namely: Content 75% “Satisfied”, Accuracy 76% “Satisfied”, Ease Of Use 87% “Very Satisfied”, Format 69% “Satisfied”, Timeliness 67% “Satisfied”, so that the final result of the average index is 74.8%. It is hoped that it can recommend platform improvements, and be used for future research to support the development of AI-powered applications in a block-based environment.

Page 5 of 5 | Total Record : 48

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