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All Journal Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Prioritas : Jurnal Pengabdian Kepada Masyarakat
Boni Oktaviana
Universitas Harapan Medan
Computer Science & IT Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice

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Penerapan Aplikasi E-Masjid pada Masjid Al-Muttaqin Lingkungan XI Kelurahan Tegal Sari Mandala III Kecamatan Medan Denai Putri Harliana; Nenna Irsa Syahputri; Mufida Khairani; Boni Oktaviana; Mochammad Iswan
Prioritas: Jurnal Pengabdian Kepada Masyarakat Vol 3 No 02 (2021): EDISI SEPTEMBER 2021
Publisher : Universitas Harapan Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35447/prioritas.v3i02.413

Abstract

Website is one of technological tools that is widely used to quickly distribute information to the public today. The Al-Muttaqin Mosque Council (BKM) is a division that aims to carry out religious activities in the community. To increase the dissemination of information to the public, the implementation of website technology at BKM Al-Muttaqin can be the right solution. This community service activity develops a website-based application in the form of an e-mosque which is intended to provide a forum and means of information for BKM Al-Muttaqin to disseminate information related to religious activities so that the public can find out the latest news and information regarding BKM Al-Muttaqin activities. In addition, this activity is also a means to share technological insights with BKM Al-Muttaqin.
Tren Penelitian Dan Struktur Pengetahuan Explainable Artificial Intelligence Untuk Pemodelan Prediktif : Bibliometric Review Eka Rahayu; Boni Oktaviana; Mufida Khairani; Arie Rafika Dewi
Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Vol. 8 No. 1 (2026): Edisi April
Publisher : Universitas Harapan Medan

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Abstract

This study aims to analyze research trends and knowledge structures in explainable artificial intelligence (XAI) for predictive modeling through a bibliometric review approach. Data were obtained from Scopus metadata in BIB format exported on June 30, 2026. The initial search strategy yielded 343 documents, which were then filtered based on article document type, English language, and journal source, resulting in 177 articles analyzed for the period 2015-2026. The analysis was conducted using a bibliometric approach through mapping publication productivity, journals and primary authors, influential documents, country contributions, keyword co-occurrence, trend topics, thematic maps, and thematic evolution. The results show that XAI research for predictive modeling experienced a strong acceleration after 2023, indicating a shift in focus from predictive models that are solely accuracy-oriented to models that are transparent, explainable, and accountable. The intellectual structure of this field is interdisciplinary, with contributions from computer science, education, health, energy, environment, geospatial, industry, materials, and engineering. The dominant themes center on machine learning, data mining, forecasting, interpretability, SHAP, LIME, and deep learning, while emerging themes focus on counterfactual explanation, causality-aware forecasting, physics-informed learning, transformers, and graph neural networks. This study identifies five key gaps: method, data, application, theory, and evaluation. The primary contribution of this research is to provide a systematic mapping of the developments, intellectual actors, dominant themes, emerging themes, and future research agendas of XAI to build more accurate, transparent, auditable, and accountable predictive modeling
Co-Authors Arie Rafika Dewi Eka Rahayu Mochammad Iswan Mufida Khairani Syahputri, Nenna Irsa