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UPAYA PERLINDUNGAN KORBAN DARI TINDAKAN KEKERASAN BAGI WARGA KAMPUS DI UNIVERSITAS GALUH Fahmi Zulkipli Lubis; Nana Yudi Permana; Muhammad Amin Effendy; Fitriyana Ramdani; Siska Susilawati
Jurnal Ilmiah Galuh Justisi Vol 14, No 1 (2026): Jurnal Ilmiah Galuh Justisi
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/justisi.v14i1.21849

Abstract

Kekerasan di lingkungan kampus merupakan persoalan serius yang mengancam keamanan dan martabat sivitas akademika. Minimnya sistem pelaporan yang aman dan responsif sering kali membuat korban enggan melapor, sehingga hak mereka atas perlindungan hukum terabaikan. Artikel ini mengkaji upaya perlindungan korban dari tindakan kekerasan di Universitas Galuh melalui implementasi sistem berbasis elektronik “Viktima” yang dikembangkan sesuai amanat Permendikbudristek Nomor 55 Tahun 2024 tentang Pencegahan dan Penanganan Kekerasan di Lingkungan Perguruan Tinggi. Penelitian ini menggunakan pendekatan normatif-empiris dengan metode Rapid Application Development (RAD). Hasil menunjukkan bahwa aplikasi Viktima mampu meningkatkan efektivitas pelaporan, menjaga kerahasiaan korban, dan memperkuat mekanisme perlindungan hukum yang cepat, aman, dan terintegrasi. Sistem ini sejalan dengan prinsip viktimologi modern yang menempatkan korban sebagai subjek perlindungan hukum
Perancangan Enterprise Architecture Event Management System Dengan Metode TOGAF ADM: (Studi Kasus: PT SEKARMENUH EVENTAMA) Muhammad Gilang Taufiq; Maulana Sidiq; Nana Yudi Permana
Jurnal Mahasiswa Sistem Informasi Galuh Vol 2 No 2 (2026): Journal of Galuh Information Systems Student
Publisher : Fakultas Teknik Jurusan Sistem Informasi Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jmsig.v2i2.5448

Abstract

The event management industry encounters major challenges due to the complexity of organizing events and the absence of integrated systems. These limitations result in inaccurate data, slow processes, and decision-making barriers that undermine professionalism and competitiveness. PT. Sekarmenuh Eventama, as the case study, faces issues including the lack of a collaborative platform for budget approval (RAB), non-digitalized information, and limited real-time reporting. This study aims to design an information technology architecture based on Enterprise Architecture (EA) using the TOGAF framework to support event management systems. The focus lies in integrating event planning, execution, and evaluation while building an effective EA framework. A qualitative case study approach was applied in Denpasar, Bali, with data collected through interviews, observations, and literature studies. System design was developed using the TOGAF ADM framework up to Phase E (Opportunities and Solutions). The results deliver an integrated IT architecture blueprint covering business, application, data, and technology layers. The proposed business process model reduces manual work and provides application functions such as participant registration, vendor management, reporting, and event analysis. Findings show that TOGAF effectively improves data consistency and decision-making speed, although challenges remain in system integration and IT infrastructure readiness.
PERANCANGAN SISTEM INFORMASI ARSIP MENGGUNAKAN METODE ZACHMAN FRAMEWORK (STUDI KASUS BPN CIAMIS) Rizal Zafar Gimnastiar; Nana Yudi Permana; Maulana Siddiq
Jurnal Mahasiswa Sistem Informasi Galuh Vol 2 No 2 (2026): Journal of Galuh Information Systems Student
Publisher : Fakultas Teknik Jurusan Sistem Informasi Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jmsig.v2i2.5452

Abstract

This research aims to design a web-based archival information system using the Zachman Framework approach. The framework is selected because it provides a comprehensive perspective in analyzing system requirements from different viewpoints, including the owner, planner, and designer perspectives. The research stages include identifying data entities, designing use case diagrams, activity diagrams, class diagrams, sequence diagrams, and developing user interface wireframes. Each stage is structured systematically to produce a system design that aligns with the organizational needs. The results show that the designed system is capable of mapping essential data requirements, such as incoming letters, outgoing letters, dispositions, and digital archives.
PENERAPAN ALGORITMA C4.5 UNTUK PREDIKSI PRESTASI SISWA DI MTS PGII BANJAR BERDASARKAN FAKTOR AKADEMIK DAN NON-AKADEMIK Erva Zulia; Maulana Sidiq; Nana Yudi Permana
Jurnal Mahasiswa Sistem Informasi Galuh Vol 2 No 2 (2026): Journal of Galuh Information Systems Student
Publisher : Fakultas Teknik Jurusan Sistem Informasi Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jmsig.v2i2.5928

Abstract

Student academic performance is an important indicator for measuring the success of learning processes in educational institutions. This study aims to apply the C4.5 algorithm to predict student performance at MTs PGII Banjar based on academic and non-academic factors. This research uses a quantitative approach with computational experimental methods following the CRISP-DM methodology. The research data were obtained from 652 students of MTs PGII Banjar for the academic years 2021/2022-2023/2024 selected using purposive sampling technique. Research variables include academic factors (subject grades, attendance) and non-academic factors (learning motivation, parental support, socioeconomic status). The C4.5 algorithm implementation was conducted using RapidMiner Studio with parameters of minimum instances per leaf = 5, confidence factor = 0.25, and minimum gain threshold = 0.01. The results show that the prediction model using the C4.5 algorithm achieved an accuracy of 78.68%, precision of 77.84%, recall of 78.12%, and F1-score of 77.98%. The AUC-ROC value of 0.842 indicates excellent model discrimination capability. Validation using 10-fold cross validation demonstrated consistent performance with low standard deviation (0.57%). Information gain analysis shows Mathematics grade as the strongest predictor (0.847), followed by Science grade (0.723), attendance level (0.689), and learning motivation (0.634). The generated decision tree identified 23 classification rules with an average confidence of 84.2% that can be interpreted as an early warning system for identifying at-risk students. This model can be implemented as a decision support system to improve academic management quality through data-driven decision making.
The integration of artificial intelligence in water conservation: A systematic literature review and thematic analysis Ali Nurdin; Rian Dwicahya Supriatman; Maulana Sidiq; Nana Yudi Permana
Interdisciplinary International Journal of Conservation and Culture Vol 4 No 1 (2026): April 2026
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/iijcc.v4i1.6033

Abstract

Water scarcity and mismanagement represent critical global challenges exacerbated by climate change and rapid urbanization. In response, Artificial Intelligence (AI) and Machine Learning (ML) have emerged as pivotal technologies optimizing equitable water distribution, real-time monitoring, and sustainable conservation strategies. This study conducts a Systematic Literature Review (SLR) based on the PRISMA guidelines to synthesize the current landscape of computational AI applications targeting water conservation. From an initial identification of 1,449 records gathered from the Scopus database, stringent inclusion criteria filtered specifically for English publications within the Computer Science structural domain spanning the years 2015-2025. This uncompromising filtration yielded exactly 19 empirical, high-impact peer-reviewed articles for qualitative synthesis. A robust thematic analysis reveals three primary domains mapping this niche research architecture: (1) Precision Agriculture and Smart Irrigation Systems leveraging IoT, (2) Predictive Modeling and Real-time Grid Monitoring for urban leakages, and (3) Water Quality and Biodiversity Modeling. Finally, this review highlights critical future research directions, including the demand for explainable AI (XAI) models in hydrology, resolving data privacy and sparse data scenarios using federated learning, and integrating extreme-event climate indices into dynamic resource planning algorithms.