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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Techno: Jurnal Penelitian Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Inspiration Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SMARTICS Journal International Research Journal of Business Studies (E-Journal) IT JOURNAL RESEARCH AND DEVELOPMENT JTERA (Jurnal Teknologi Rekayasa) Jurnal Komtika (Komputasi dan Informatika) Jurnal Informatika Universitas Pamulang Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal ULTIMA InfoSys MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Respirologi Indonesia Journal of Electronics, Electromedical Engineering, and Medical Informatics JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Generation Journal JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Buletin Profesi Insinyur Jurnal Teknik Informatika (JUTIF) Jurnal Teknologi Berkelanjutan Pharmaceutical Sciences and Research (PSR) JURNAL PENGABDIAN MASYARAKAT AKADEMISI Jurnal Penyakit Dalam Indonesia Dalwa Islamic Economic Studies: Jurnal Ekonomi Syariah Nidhomiyyah: Jurnal Manajemen Pendidikan Islam International Research Journal of Business Studies JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komtika (Komputasi dan Informatika)
Muhammad Alkaff
Universitas Lambung Mangkurat
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Social Sciences Transportation Other

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Sistem Rekomendasi Buku pada Perpustakaan Daerah Provinsi Kalimantan Selatan Menggunakan Metode Content-Based Filtering Muhammad Alkaff; Husnul Khatimi; Andi Eriadi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 20 No. 1 (2020)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v20i1.617

Abstract

Perpustakaan Daerah Provinsi Kalimantan Selatan merupakan salah satu perpustakaan dan pusat penyedia layanan informasi yang ada di Kalimantan Selatan. Namun. selama ini pengunjung perpustakaan kesulitan dalam mencari buku yang berkaitan dengan buku yang dipilih sebelumnya dan juga dalam menemukan alternatif buku lain ketika buku yang diinginkan tersebut telah dipinjam. Dengan adanya rekomendasi atau saran buku-buku lain yang berhubungan diharapkan membantu dalam mendapatkan buku yang sesuai dan diinginkan pengunjung perpustakaan. Pada penelitian ini penerapan sistem rekomendasi menggunakan metode Content-Based Filtering dalam memberikan rekomendasi buku yang bekerja dengan melihat kemiripan item yang dianalisis dari fitur yang dikandungnya dengan Weighted Tree Similarity. Berdasarkan hasil pengujian yang telah dilakukan pada 5 skenario pengujian yang diujikan dihasilkan nilai precision sebesar 88%.
Hate Speech Detection for Banjarese Languages on Instagram Using Machine Learning Methods Muhammad Alkaff; Muhammad Afrizal Miqdad; Muhammad Fachrurrazi; Muhammad Nur Abdi; Ahmad Zainul Abidin; Raisa Amalia
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 3 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i3.2939

Abstract

Hate speech refers to verbal expression or communication that aims to provoke or discriminate against individuals. The Ministry of Communication and Information of Indonesia has encountered and dealt with 3,640 cases of hate speech transmitted through digital channels between 2018 and 2021. Particularly in South Kalimantan, hate speech in the local language, Banjarese has become increasingly prevalent in recent years. Surprisingly, there is a lack of research on using machine learning to detect hate speech in the Banjarese language, specifically on Instagram. Therefore, this study aimed to address this gap by constructing a dataset of Banjarese language hate speech and comparing various feature extraction and machine learning models to detect Banjarese language hate speech effectively. Thisresearch used several feature extraction techniques and machine learning methods to detect Banjareselanguage hate speech. The feature extraction methods used were Word N-Gram, Term Frequency- Inverse Document Frequency (TF-IDF), a combination of Word N-Gram and TF-IDF, Word2Vec, and Glove, while the machine learning methods used were Support Vector Machine (SVM), Na¨ıve Bayes, and Decision Tree. The results of this study revealed that the combination of TF-IDF for feature extraction and SVM as the model achieves exceptional performance. The average Recall, Precision, Accuracy, and F1-Score score exceeded 90%, demonstrating the model’s ability to identify Banjarese hate speech accurately.
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).
Co-Authors Abdullayev, Vugar Agus Dwi Susanto Ahmad Zainul Abidin Ainiyyah, Ainiyyah Akhmad Rojali Aldy Heriwardito Andi Eriadi Andi Farmadi Andreyan Rizky Baskara ARIF RAHMAN, MUHAMMAD Arina Ihda Rahmah Syarifah Ariska Deffy Anggarany, Ariska Deffy Baskara, Andreyan Budhi Antariksa Ceva W. Pitoyo Dany Primanita Kartikasari Darmawan, Puja Dewi Rizqia Najipah Dewi Yennita Sari Dodon Turianto Nugrahadi Erischa Marsela Erlina Burhan Fadliyanur Fadliyanur Fadliyanur Fajar Zulkarnain, Andry Fatma Indriani Friska Abadi Gusti Nizar Syafi'i Halimah Halimah Hayatun Nufus Henning Titi Ciptaningtyas Hera Afidjati Herry Purnomo Husnul Khatimi Ibrahim Nur Insan Putra Darmawan Iftihatul Aulia Rahmah Iphan Fitrian Radam Iphan Fitrian Radam Iqbal Rizqi, Muhammad Irwan Budiman Jumadi Mabe Parenreng Marimin Marimin Maulani, Irham Maulidiya, Erika Maya Amalia Mohamad Fahmi Alatas Muhammad Afrizal Miqdad Muhammad Bahit Muhammad Fachrurrazi Muhammad Ilham Muhammad Nur Abdi Muhammad Reza Faisal, Muhammad Reza Muhammad Ridho A.G.D. Muhammad Ziki Elfirman Muti'a Maulida Mutia Maulida Nandang Eko Yulianto Nurul Fathanah Mustamin Nurul Qamaria Paramita, Diana Putra, Andika Chandra Putri Ridha Amalia Raisa Amalia Rakhmadhany Primananda, Rakhmadhany Rani Sauriasari, Rani Reza Karimi Rita Rogayah Rudy Ansari, Rudy Ryan Ramel Samoedro, Erlang Saragih, Triando Hamonangan Sa’diah, Halimatus Sinar Nadhif Ilyasa siti sheilawati Soehardiman, Dicky Sugiantoro Sugiantoro Sugiantoro Sugiantoro Sukamto Koesnoe Sukardi Sukardi Supeno Djanali Syarifah Soraya Takhwifa, Famila Taufik, Feni Fitriani Wenny Puspita Wijaya, Eka Setya Winarto Chandra Winda Agustina Windarsyah Windarsyah Yandra Arkeman Yulianto, Nandang Eko Yuslena Sari, Yuslena