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All Journal Jurnal Online Mahasiswa (JOM) Bidang Keguruan dan Ilmu Pendidikan JAM : Jurnal Aplikasi Manajemen Journal of Physical Education Health and Sport Journal Of Vocational Health Studies Pendekar : Jurnal Pendidikan Berkarakter Journal of Educational Research and Evaluation Jurnal PORKES Jurnal Stamina Yayasan Cita Cendikiawan Al Khwarizmi Jurnal Informatika Terpadu Brilliance: Research of Artificial Intelligence Sepakbola QISTINA: Jurnal Multidisiplin Indonesia AGROTECH Research Journal DBESTI: Journal of Digital Business and Technology Innovation AGRONIMAL: Jurnal Ilmiah Pertanian dan Peternakan
Rusmanto, Rusmanto
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Predictive Maintenance on Fortinet Firewall Devices Using Artificial Intelligence Rustianto, April; Murobbie, Faqih; Rusmanto, Rusmanto
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7448

Abstract

The growing complexity of enterprise network infrastructures has increased the importance of predictive maintenance for network security devices, particularly firewall systems. In operational environments using Fortinet firewalls, large volumes of firewall logs are continuously generated, while existing monitoring tools such as FortiAnalyzer remain limited to descriptive analysis and lack predictive capabilities. This study aims to evaluate the effectiveness of artificial intelligence, specifically Large Language Models (LLMs), for predictive maintenance through automated analysis of firewall logs. Four open-source LLMs-Gemma 2B, Mistral 7B, DeepSeek-R1 7B, and Qwen 2.5-Coder 7B-were benchmarked using a standardized Indonesian-language prompt designed to extract high-severity events, including emergency, alert, and critical conditions, from multi-severity Fortinet log data. The evaluation focused on AI benchmarking metrics such as severity filtering compliance, reasoning accuracy, linguistic consistency, structural clarity, and processing efficiency. The results indicate that Qwen 2.5-Coder 7B provides the most reliable overall performance, demonstrating strong adherence to severity constraints, consistent Indonesian-language output, and well-structured analytical results suitable for operational predictive maintenance. Mistral shows superior contextual reasoning but exhibits language inconsistency, while Gemma offers the fastest processing time with moderate severity accuracy. DeepSeek performs least effectively due to instruction non-compliance. This study addresses an existing research gap by demonstrating how large language models can support predictive maintenance for firewall-based network security systems and provides a comparative framework for future AI-driven firewall and log-analysis research.
SUSTAINABLE DEVELOPMENT AS A PARADIGM FOR ENVIRONMENTAL CONSERVATION Rusmanto, Rusmanto
AGRONIMAL: Jurnal Ilmiah Pertanian dan Peternakan Vol. 2 No. 1 (2024): AGRONIMAL: Jurnal Ilmiah Pertanian dan Peternakan
Publisher : Tahta Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55080/agronimal.v2i1.1897

Abstract

This study aims to analyze the implementation of sustainable development principles as a paradigm for environmental conservation in Klaten Regency and to examine the roles of local government and community participation in supporting sustainable development. The research employed a qualitative approach with a case study design. Data were collected through in-depth interviews, field observations, and analysis of regional policy documents, and were analyzed using thematic analysis involving data reduction, data display, and conclusion drawing. The findings indicate that the local government has integrated sustainable development principles into planning documents and environmental programs, such as community-based waste management and environmental rehabilitation initiatives. However, policy implementation still faces challenges, including limited cross-sectoral coordination, inconsistency in program execution, and the predominance of economic growth-oriented development. Meanwhile, community participation through environmental groups and local initiatives demonstrates significant potential for strengthening socially based sustainability. The study concludes that sustainable development in Klaten Regency requires strengthened collaborative governance, integrated cross-sector policies, and the internalization of sustainability values within regional development practices to ensure systematic and long-term environmental conservation.
Co-Authors 'afina, Dindha Tri Agi Ginanjar Agustria, Weni Ali Mandan, Ali Arafah, Nurfauziah Ardiah Juita Ardiansyah, Ahmad Rio Aref Vai Aspa, Agus Prima Bayanussabil, Muhammad Syahid Davied Wahyu Wismanindra Dinan Mitsalina Fekie Adila Hertini, Etty Sri Ida Mentayani Juhariah, Jujuk Kasman Rukun Mardiansyah, Firman Margaretha Praba Aulia Muhammad Faisal Muqmiroh, Lailatul Murobbie, Faqih Pramudiawardani, Shelly Praptono, Soegardo Indra Putri Adita Wulandari Rahmadi, Catur Riga Rahmatullah, Muhammad Imam Ramadani, Desta Ramadhan, Riki Risalatul Latifah Rustianto, April Sapriandi, Sapriandi Sensusiati, Anggraini Dwi Sigit Muryanto, Sigit Sulastio, Agus Wijaya, Regi Wismanindra, Davied Wahyu