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All Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Journal of Innovation Information Technology and Application (JINITA)
Afit Ajis Solihin
Universitas Amikom Purwokerto
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Program pendampingan pemilihan jurnal dan teknik submit artikel ilmiah melalui OJS bagi mahasiswa Fakultas Ilmu Komputer Universitas Amikom Purwokerto Fandy Setyo Utomo; Afit Ajis Solihin; Rifqi Arifin Ilham
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 3 (2024): September
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i3.26081

Abstract

AbstrakPermasalahan yang dihadapi oleh mitra sasaran, yakni Fakultas Ilmu Komputer Universitas Amikom Purwokerto adalah rendahnya jumlah publikasi ilmiah yang dihasilkan oleh mahasiswa program sarjana dan magister sebagai luaran matakuliah. Berdasarkan permasalahan tersebut, kami memberikan solusi menyelenggarakan program pendampingan strategi pemilihan jurnal penelitian dan teknik submit artikel ilmiah melalui open journal systems bagi mahasiswa fakultas ilmu komputer. Target yang diharapkan dari program ini, yakni mahasiswa Fakultas Ilmu Komputer memiliki pemahaman dan berkemampuan untuk memilih target jurnal yang tepat sesuai dengan artikel ilmiah yang mereka tulis, mampu memahami persyaratan dan teknik tata tulis dari jurnal yang ditargetkan, serta mampu mengirimkan artikel ilmiah melalui OJS dengan benar. Berdasarkan target luaran yang telah ditetapkan, metode pengabdian masyarakat yang digunanakan dalam program ini mencakup 3 tahap utama, yaitu tahap persiapan kegiatan, implementasi kegiatan, dan pelaporan kegiatan. Setelah mengimplementasikan solusi yang diusulkan, kami mengevaluasi kemampuan peserta program pendampingan dalam memahami kriteria pemilihan jurnal ilmiah dan teknik submit artikel ilmiah melalui OJS. Hasil evaluasi menunjukkan bahwa 97% peserta mampu memahami kriteria pemilihan jurnal penelitian dan 94% mampu memahami teknik submit artikel ilmiah melalui OJS. Kata kunci: pendampingan; jurnal penelitian; artikel ilmiah; open journal system; OJS AbstractThe problem faced by our target partner, the Faculty of Computer Science at Universitas Amikom Purwokerto, is the low number of scientific publications produced by undergraduate and graduate students as course outputs. To address this issue, we proposed a mentoring program on strategies for selecting research journals and techniques for submitting scientific articles through open journal systems for computer science students. The expected outcome of this program is that the students of the Faculty of Computer Science will have the understanding and ability to select appropriate target journals for their scientific articles, understand the requirements and writing techniques of the targeted journals, and be able to submit their articles through OJS correctly. Based on the established outcome targets, the community service method used in this program includes three main stages: activity preparation, activity implementation, and activity reporting. After implementing the proposed solution, we evaluated the participants' ability to understand the criteria for selecting scientific journals and the techniques for submitting articles through OJS. The evaluation results showed that 97% of participants were able to understand the criteria for selecting research journals, and 94% were able to understand the techniques for submitting scientific articles through OJS. Keywords: mentoring; research journal; scientific article; open journal system; OJS
Impact of Stopword Variation on Qur'anic Text Classification using Support Vector Machine and Backpropagation Afit Ajis Solihin; Fandy Setyo Utomo; Azhari Shouni Barkah
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.3069

Abstract

This study aims to analyze the impact of varying stopword sets on the performance of Qur'anic text classification models in Indonesian translations, using two machine learning algorithms: Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN). The research involved six stopword variants: Sastrawi, Damian Doyle, Fadillah Z. Tala, Natural Language Toolkit (NLTK) Indonesian, Yudi Wibisono, and a combination of all these lists. The preprocessing steps included cleaning, case folding, tokenization, stopword removal, and stemming, followed by TF-IDF (Term Frequency-Inverse Document Frequency) text representation. Feature selection was performed using the Chi-Square method to select the top 1,000 features. The evaluation results showed that SVM consistently outperformed BPNN across all metrics, including accuracy, precision, recall, and F1-score. The Sastrawi stopword variant delivered the best performance with an F1-score of 0.6697, followed by Fadillah Z. Tala and Damian Doyle. In contrast, BPNN showed lower performance, with the highest F1-score of 0.4607 achieved using the NLTK stopword variant. These findings highlight that selecting relevant, contextually appropriate stopwords is critical to classification Effectiveness. SVMs proved more reliable at handling high-dimensional text data while preserving the semantic meaning of Qur'anic verses.
Co-Authors Azhari Shouni Barkah Fandy Setyo Utomo Rifqi Arifin Ilham