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All Journal QUANTUM: Jurnal Inovasi Pendidikan Sains Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Tarbiyah : Jurnal Ilmiah Kependidikan JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) JURNAL PENGABDIAN MASYARAKAT AKADEMISI KREATIF: Jurnal Pengabdian Masyarakat Nusantara
Muhammad Bahit
Universitas Lambung Mangkurat
Religion Arts Humanities Chemistry Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Law, Crime, Criminology & Criminal Justice Physics Social Sciences

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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): June 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.
Meningkatkan Kompetensi Pemrograman Siswa Melalui Pelatihan Pemrograman di MAN Kota Banjarbaru Muhammad Bahit; Muhammad Alkaff; Eka Setya Wijaya; Fadliyanur; Erischa Marsela; Muhammad Ilham
JURNAL PENGABDIAN MASYARAKAT AKADEMISI Vol. 4 No. 3 (2026): JULI : JURNAL PENGABDIAN MASYARAKAT AKADEMISI
Publisher : CV. ALIM'SPUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/jpma.v4i3.2313

Abstract

The rapid advancement of digital technology has increased the demand for coding skills among students as one of the essential competencies in the Industrial Revolution 4.0 and Society 5.0 eras. However, many high school students have limited opportunities to learn programming through formal education. This community service activity aimed to improve the coding competence of students at MAN Kota Banjarbaru through intensive coding training that combined theoretical explanations with hands-on programming practice. The activity involved 12 students who participated in classroom instruction, guided practice, discussions, and evaluations using a structured questionnaire consisting of four dimensions: training quality, self-efficacy, coding competence, and learning interest. Evaluation results showed that participants perceived the training positively. The average scores for training quality (3.70), self-efficacy (3.44), coding competence (3.41), and learning interest (3.70) indicate that the program successfully enhanced students' understanding, confidence, and motivation to continue learning programming. The findings demonstrate that practical coding training is an effective community service approach for strengthening students' digital competencies and fostering greater interest in information technology).
Mapping The Eye Tracking Application To Assess Students’ Metacognitive Skills In Chemistry Learning Khairiatul Muna; Muhammad Bahit
Tarbiyah : Jurnal Ilmiah Kependidikan Vol. 15 No. 1 (2026)
Publisher : Universitas Islam Negeri Antasari Banjarmasin, South Kalimantan, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18592/tarbiyah.v15i1.15310

Abstract

Metacognitive skills impact learning in a variety of significant and tangible ways, including problem solving. A method that may be employed to assess problem-solving and metacognitive skills is the eye tracking method. The purpose of this research is to conduct systematic analysis and to map the application of eye tracking in chemistry learning, including its relationship to metacognition and problem-solving skills. Thus, it is anticipated that a greater comprehension of how to use the eye tracking and how it has been applied. This research was conducted using the bibliometric method with the assistance of Publish or Perish (PoP), Zotero, and VOSviewer software. The analysis of the data was conducted qualitatively and quantitatively descriptively. Fifty-five (55) articles were analyzed through the utilization of VOSviewer. The results indicate that there is a scarcity of Scopus-indexed journal articles that detail research on the application of eye tracking for assessing metacognitive skills in chemistry learning (in one study). It is therefore imperative to undertake additional research and disseminate the findings. The primary objective of additional research is to ascertain the efficacy of eye tracking. The findings of the analysis also yielded a comprehensive synopsis of the procedures employed in eye tracking for educational purposes, encompassing both chemistry and non-chemistry domains. Additionally, eye tracking has the capability to systematically and comprehensively delineate, examine, and define the learning process, encompassing the application of metacognitive skills in problem solving and learning.
Identifikasi Sentimen pada Data Teks Media Sosial Melalui Pendekatan Pembelajaran Terawasi Muhammad Bahit; Yuslena Sari; Andreyan Rizky Baskara; Eka Setya Wijaya; Harry Pratama Yunus; Alysa Armelia
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i2.16032

Abstract

Analisis sentimen pada data teks media sosial menjadi penting untuk memahami opini publik, sehingga penelitian ini bertujuan untuk mengidentifikasi sentimen pada data teks media sosial melalui pendekatan pembelajaran terawasi. Dataset yang digunakan terdiri dari tweet dan ulasan produk yang telah dilabeli sentimen positif maupun negatif. Proses penelitian dilakukan melalui beberapa tahapan, yaitu prapemrosesan data (Removal of Stopwords, Lemmatization and Word Stemming, Spell Correction), Ekstraksi Fitur (N-Grm, Word count dan Tf-Idf Vectorizer) serta penerapan algoritma Multinomial Naive Bayes, dan Support Vector Machine (SVM). Hasil penelitian menunjukkan bahwa penghapusan stopwords menurunkan kinerja model, sehingga tetap menggunakan stopwords. Stemming dan lemmatization juga tidak memberikan pengaruh terhadap kinerja model, sedangkan spell correction dapat meningkatkan akurasi sekitar 2% tetapi dengan trade-off waktu komputasi yang tinggi. Pada tahap ekstraksi fitur, TF-IDF menghasilkan akurasi yang lebih tinggi dibandingkan Word Count. Algoritma Multinomial Naive Bayes menghasilkan akurasi sebesar 79,73% dengan AUC-ROC sebesar 0,85. Sedangkan SVM dengan kernel linear mendapatkan hasil terbaik dengan akurasi 82% dan AUC-ROC 0,88, lebih tinggi daripada RBF kernel yang hanya mencapai akurasi 77,79% dan AUC-ROC 0,82. Hasil penelitian ini dapat disimpulkan bahwa SVM dengan kernel linear lebih sesuai untuk klasifikasi teks berdimensi tinggi.
Co-Authors Alysa Armelia Andreyan Rizky Baskara Erischa Marsela Fadliyanur Fadliyanur Fadliyanur Harry Pratama Yunus Ihya Ihya Khairiatul Muna Khairiatul Muna Lutfiana Marisa Monika Handayani, Monika Muhammad Alkaff Muhammad Fajrian Noor Muhammad Fauzan Ahsani Muhammad Ilham Muhammad Rivaldi Akbar Sinar Nadhif Ilyasa Sulthan Alfarisy Syahrial Shaddiq Wijaya, Eka Setya Yuslena Sari, Yuslena