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All Journal QUANTUM: Jurnal Inovasi Pendidikan Sains Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) KREATIF: Jurnal Pengabdian Masyarakat Nusantara
Muhammad Bahit
Universitas Lambung Mangkurat
Chemistry Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Law, Crime, Criminology & Criminal Justice Physics

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Network Security Analysis with Hybrid Intrusion Detection System, Firewall, and Attacker Log Visualisation Sulthan Alfarisy; Eka Setya Wijaya; Muhammad Fajrian Noor; Muhammad Bahit
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 1 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i1.462

Abstract

The current digital era brings convenience to people in various industries, including access to information that can be obtained from various sources on the Internet. However, the freedom of the Internet has also led to an increase in cybercrime, which has become a serious problem. According to a monitoring report from the National Cyber and Crypto Agency (BSSN), Indonesia experienced a total of around 2.4 billion cyberattack anomalies between January 2021 and August 2022. With so many cases, an effective system is needed to detect, prevent, and monitor computer networks. This research applies a hybrid Intrusion Detection System (IDS) system that uses OSSEC and Suricata, and uses Elastic Stack for log management for server monitoring. The results show that this hybrid IDS system is able to detect all types of attacks tested, including port scanning, brute force, SQL injection, and denial of service (DoS). In addition, this system can also block attack access by utilising firewall features such as Iptables. The detection results of the hybrid IDS were successfully visualised using Elastic Stack, demonstrating the effectiveness of the system in improving computer network security.
Penguatan Manajemen Keuangan pada Kelompok Usaha Bersama (KUBE) Berkat Ilahi Desa Pulantani Muhammad Bahit; Syahrial Shaddiq; Monika Handayani; Harry Pratama Yunus; Ihya Ihya; Muhammad Fauzan Ahsani; Muhammad Rivaldi Akbar
KREATIF: Jurnal Pengabdian Masyarakat Nusantara Vol. 6 No. 1 (2026): Jurnal Pengabdian Masyarakat Nusantara
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/kreatif.v6i1.8422

Abstract

This Community Partnership Program (PKM) aims to improve the financial management capacity of the Berkat Ilahi Joint Business Group (KUBE), a purun weaving artisan group in Pulantani Village, Hulu Sungai Utara Regency, South Kalimantan. The partners' main challenges were the lack of structured financial records and inaccuracies in calculating the cost of goods sold (COGS). To address these challenges, a web-based accounting information system was developed to facilitate financial recording, COGS calculations, and budget planning. Implementation methods included outreach, workshops, mentoring, and evaluation. Results showed that more than 85% of KUBE members were able to independently manage COGS reports, financial reports, and digital marketing content. The implementation of this program not only increased transparency and accountability in financial management but also opened broader market access through digital platforms. This program is expected to support the sustainability of the purun weaving business and strengthen the local economy based on empowerment and innovation
Validity of Chemistry Comic Learning Media on Reaction Rate Material Integrated with Islamic Values Lutfiana Marisa; Khairiatul Muna; Muhammad Bahit
QUANTUM: Jurnal Inovasi Pendidikan Sains Vol 16, No 1 (2025): April 2025
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/quantum.v16i1.21012

Abstract

Reaction rate material requires an understanding of chemical multirepresentations, which is a challenge for students. Although digital comics are increasingly used in learning, research on the integration of Islamic values and multirepresentation in chemical comics is still limited. In addition, the use of Webtoon as a learning platform in science education is still rarely researched. The research aims to find out how the validity of chemical comic learning media on reaction rate materials that are integrated with Islamic values. The research method used is R&D with the ADDIE design model; validation was carried out by experts in media, material, and Islamic integration, with the scores obtained categorized into very valid, valid, invalid, and very invalid using quantitative descriptive analysis. Research with the ADDIE model goes through five stages, namely, Analysis, Design, Development, Implementation, and Evaluation. The validity results obtained a score of 89% for media validity, 84% for material validity, and 83% for integration validity with all categories very valid. The results of the study show that the developed comic media is proven to be very valid so that the developed media is suitable for further testing to the Implementation stage.
Indonesian Hate Speech Detection under Class Imbalance Using a Soft-Voting Ensemble of IndoBERTweet and IndoRoBERTa Muhammad Alkaff; Eka Setya Wijaya; Fadliyanur Fadliyanur; Muhammad Bahit; Sinar Nadhif Ilyasa
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): Juni 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7681

Abstract

Hate speech detection on Indonesian social media remains challenging due to the coexistence of formal and highly colloquial language, as well as the moderate class imbalance typical of real-world datasets. Models trained under these conditions often skew toward the majority class and generalize poorly across linguistic registers. This study investigates whether a simple, training-free model-level ensemble can improve Indonesian hate speech detection under such conditions without resampling the data. IndoBERTweet and IndoRoBERTa, pretrained respectively on informal Twitter text and broader formal corpora, serve as complementary base models, and their class probabilities are combined through equal-weight soft voting. On the Indonesian Hate Speech Superset (N = 14,306), evaluated across five random seeds with paired significance testing, the soft-voting ensemble attains a macro-averaged F1 of 0.898 ± 0.003 and a macro recall of 0.899 ± 0.003. It significantly outperforms a TF-IDF SVM baseline and the IndoRoBERTa base model, while showing no significant difference from the stronger IndoBERTweet base model and a trained logistic-regression stacking ensemble. Notably, the ensemble matches the stacking ensemble without any additional training stage or meta-learner, and a calibration analysis shows it improves probability calibration over both base models. These results indicate that equal-weight probability averaging is a simple, reproducible, and competitive strategy for Indonesian hate speech detection under moderate class imbalance.
Co-Authors Fadliyanur Fadliyanur Harry Pratama Yunus Ihya Ihya Khairiatul Muna Lutfiana Marisa Monika Handayani, Monika Muhammad Alkaff Muhammad Fajrian Noor Muhammad Fauzan Ahsani Muhammad Rivaldi Akbar Sinar Nadhif Ilyasa Sulthan Alfarisy Syahrial Shaddiq Wijaya, Eka Setya