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All Journal Jurnal Informatika dan Rekayasa Perangkat Lunak Journal of Social Sciences and Technology for Community Service Komputasi : Jurnal Ilmiah Ilmu Komputer dan Matematika
Gustian Rama Putra
Computer Science, Faculty of Mathematics and Natural Sciences, Pakuan University
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics

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Faculty Information Systems Project Management: A Comparison of CPM And PERT Methods Gustian Rama Putra; Reza Ariftiarno; Lita Karlitasari; Dinar Munggaran Akhmad
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol. 22 No. 1 (2025): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Program Studi Ilmu Komputer, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v22i1.5

Abstract

This research evaluates the Critical Path Method (CPM) and the Program Evaluation and Review Technique (PERT) to determine the most efficient scheduling method for the development of an information system at the Faculty of Economics and Business, Universitas Pakuan. The system aims to consolidate work unit information and assist faculty leaders in decision-making. Both methods identified the same critical path (A-B-C-E-G-H), ensuring focus on activities critical to project completion. The CPM method estimated a project duration of 50 days, while the PERT method estimated 52 days. The two-day difference reflects CPM’s deterministic and optimistic approach, making it suitable for projects with predictable timelines. PERT, with its probabilistic calculations, incorporates activity duration variations and risks, providing more conservative estimates for projects with higher uncertainty. Due to its shorter duration and potential cost savings, the CPM method is recommended for the Faculty's information system development project. This research emphasizes the importance of selecting a scheduling method aligned with project complexity and uncertainty.
Computer Programming with JAVA Java JumpStart: A Hands-on Training from Basics to Building Blocks Gustian Rama Putra
Journal Social Science And Technology For Community Service Vol. 6 No. 1 (2025): Volume 6, Nomor 1, March 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v6i1.46

Abstract

This community service activity represents a collaborative effort between the College of Science and Technology, Guimaras State University, Philippines, and the Computer Science, Universitas Pakuan, Indonesia. The initiative was designed to support the Sustainable Development Goals (SDGs), specifically SDG 4: Quality Education, SDG 8: Decent Work and Economic Growth, SDG 9: Industry, Innovation, and Infrastructure, SDG 10: Reduced Inequalities, and SDG 17: Partnerships for the Goals. The primary objective of this program was to equip participants with foundational knowledge and practical skills in Java programming, fostering digital literacy, critical thinking, and problem-solving abilities essential for personal and professional growth in an increasingly technology-driven world. The expected outputs of the activity included equipping participants with a solid understanding of Java basics, enabling them to create simple Java applications independently, use integrated development environments (IDEs) like Eclipse or NetBeans effectively, and develop enhanced problem-solving skills through programming exercises. Participants were also introduced to foundational object-oriented programming concepts such as classes, objects, inheritance, and polymorphism, culminating in the creation of a functional project that integrates key Java programming concepts. Additionally, teachers gained the confidence and skills to incorporate Java programming into their classrooms or workshops, ensuring the program's long-term impact. The program demonstrated significant outcomes, as evidenced by the data in Table 3, where the average participant understanding exceeded 90%. This notable achievement underscores the success of the initiative in promoting knowledge transfer and skill development. Furthermore, it highlights the effective collaboration between Guimaras State University and Universitas Pakuan in advancing the tri dharma of higher education: teaching, research, and community service while delivering tangible benefits to the community. This success encourages both institutions to continue fostering partnerships that contribute to sustainable development and societal well-being.
Pemberdayaan Desa Seuseupan melalui Implementasi Energi Surya dan Teknologi IoT menuju Smart Village Gustian Rama Putra; Agus Ismangil; Cyntia Wulandari; Mutiara Shakila
Journal Social Science And Technology For Community Service Vol. 7 No. 1 (2026): Volume 7 Nomor 1 Maret 2026
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v7i1.1215

Abstract

Abstrak- Program pengabdian ini dilaksanakan di Desa Seuseupan, Kecamatan Caringin, Kabupaten Sukabumi, sebagai respons terhadap dua permasalahan utama, yaitu rendahnya produktivitas pertanian akibat metode konvensional dan keterbatasan penerangan publik yang menghambat aktivitas sosial-ekonomi. Kegiatan dirancang untuk memperkuat ketahanan pangan dan kemandirian energi desa melalui penerapan teknologi Internet of Things (IoT) pada sistem pertanian serta instalasi solar panel pada ruang publik. Metode pelaksanaan mencakup observasi lapangan, Focus Group Discussion, pelatihan teknis, pembangunan Green House Smart Village, pemasangan lampu tenaga surya, serta monitoring dan evaluasi. Implementasi smart farming berbasis IoT menghasilkan peningkatan hasil panen sebesar 28%, efisiensi penggunaan air 35%, serta penurunan kerusakan tanaman. Penerapan solar panel di titik strategis desa meningkatkan keamanan malam hari, menekan biaya listrik hingga 37%, dan mendorong pertumbuhan aktivitas ekonomi sebesar 23%. Pelatihan yang diberikan kepada petani dan perangkat desa meningkatkan pemahaman teknologi lebih dari 90%, serta mendorong terbentuknya Kelompok Tani Cerdas Seuseupan sebagai pengelola keberlanjutan program. Secara keseluruhan, kegiatan ini menunjukkan bahwa integrasi IoT dan energi surya mampu memperbaiki kualitas pengelolaan pertanian, memperkuat infrastruktur energi, dan meningkatkan partisipasi masyarakat. Program ini membangun fondasi desa cerdas yang mandiri secara pangan dan energi, sekaligus membuka peluang perluasan inovasi ke desa-desa lain dengan karakteristik serupa.
Advancing Smart City Infrastructure: A Deep Learning-Based Framework for Real-Time Traffic Monitoring and Violation Detection Using YOLOv11 Gustian Rama Putra; Adrian Jaleco Forca; Reiner Jun Gepayo Alminaza; Fajar Delli Wihartiko; Raid Rafif
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Volume 7 Number 1 March 2026
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v7i1.1354

Abstract

Urban traffic congestion and violations of dedicated bus lanes in metropolitan cities, such as Jakarta, are significant challenges affecting the efficiency of public transportation systems. Traditional traffic monitoring methods are insufficient to address these issues, particularly in real-time violation detection. This research proposes an AI-based smart traffic monitoring framework using YOLOv11 for real-time detection of vehicle violations in TransJakarta’s Bus Rapid Transit (BRT) lanes. The study aims to improve urban mobility by enhancing the detection accuracy and speed of traffic monitoring systems. The methodology involves data collection from surveillance cameras, data annotation using Roboflow, and model training with YOLOv11, utilizing transfer learning and hyperparameter optimization. The system's performance is evaluated through precision, recall, F1-score, and mean Average Precision (mAP@0.5), as well as real-time inference speed. The results show that YOLOv11 achieves a mAP@0.5 of 0.946 and an F1-score of 0.898, demonstrating the model's high accuracy in detecting vehicle violations across different lighting conditions. Real-time inference is achieved at a rate of 35-40 FPS, making it suitable for deployment in real-world urban environments. This research concludes that the YOLOv11-based framework is an effective solution for automated traffic monitoring, offering significant implications for smart city development and intelligent transportation systems. Further research is needed to address lighting challenges and improve the system's scalability across various urban settings.
Co-Authors Adrian Jaleco Forca Agus Ismangil Cyntia Wulandari Dinar Munggaran Akhmad Fajar Delli Wihartiko Lita Karlitasari Mutiara Shakila Raid Rafif Reiner Jun Gepayo Alminaza Reza Ariftiarno