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Journal : Madani: Multidisciplinary Scientific Journal

Pengembangan E-Modul Interaktif Dengan Menggunakan Model Pbl Dalam Pembelajaran IPA Materi Organ Pencernaan Pada Hewan dan Manusia di SD N 0601 Paringgonan Parapat, Khoiriah Marta; Rahmadani, Annisa; Ardiyani, Fenika; M, Maswariyah; Ulkhaira, Nabila; Ramadhani, Rizki
Madani: Jurnal Ilmiah Multidisiplin Vol 1, No 12 (2024): Madani, Vol. 1 No. 12 2024
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

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Abstract

Electronic modules or e-modules, are defined as learning media using computers that display text, images, graphics, audio, animation and video in the learning process. The aim of this research is to find out how to develop an interactive e-module using the PBL model in science learning regarding Digestive Organs in Animals and Humans at SD N 0601 Paringgonan. The method used in this research is to use the ADDIE model, namely Analysis, Design, Development, Implementation and Evaluation. The results of this research state that this PBL-based interactive e-module has been successfully developed. This PBL-based interactive e-module was declared suitable for use in learning according to the validation results of material experts, media experts and language experts with an average of 885, 895 and 91.75% respectively. The implementation results stated that student learning outcomes increased from series 1 to the next series. Students' responses to the use of PBL-based interactive e-modules in the teaching and learning process were classified in the very good category with an average of 90.86%.
Optimalisasi Intelijen Ancaman Siber di Security Operation Centers dengan Pemanfaatan Large Language Models (LLM) dan SIEM Ramadhani, Rizki; Christie, Angella; Dewani, Alma Amira; Krisnawan R., Marselinus; Ardhana, Rafif Dhimaz
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 5 (2025): Volume 3, Nomor 5, June 2025
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

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Abstract

In the era of increasing digital transformation, cyber threats have become a major concern for higher education institutions such as Institut Teknologi Sepuluh Nopember (ITS). Security Operations Center (SOC) plays a crucial role in detecting and responding to security incidents, often supported by Security Information and Event Management (SIEM) systems like Wazuh. However, traditional SIEM systems generate high volumes of alerts, many of which are false positives, causing alert fatigue and slowing incident response. This study explores the integration of Large Language Models (LLM), such as GPT-4 and LLaMA 3, to enhance SOC performance through intelligent triage automation. Using a qualitative descriptive approach based on literature review, this research proposes a conceptual system framework that combines SIEM with LLM as an analytical agent. The designed system features components for alert processing, natural language explanation, automated reporting, and a feedback loop for continuous improvement. The proposed framework is expected to reduce the workload of SOC analysts, improve alert classification accuracy, and accelerate threat response in academic environments.