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All Journal Journal of Informatics and Computer Science (JINACS) International Journal of Research and Community Empowerment International Journal of Advances in Artificial Intelligence and Machine Learning Journal of Digitalization in Physics Education (JDPE)
Husni Mubarok
Universitas Negeri Surabaya
Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Education Industrial & Manufacturing Engineering Mathematics Physics Social Sciences

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Sistem Analisa Lowongan Kerja di Indonesia pada Media Sosial Facebook Dengan Metode TF-IDF dan Decision Tree Husni Mubarok; Dedy Rahman Prehanto
Journal of Informatics and Computer Science (JINACS) Vol 3 No 02 (2021)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1187.013 KB) | DOI: 10.26740/jinacs.v3n02.p200-206

Abstract

Indonesia adalah negara berkembang dan juga memiliki populasi penduduk hingga 274.9 juta jiwa. Perkembangan ini juga terjadi bidang teknologi informasi, dan perkembangan tersebut cukup pesat terjadi, perkembangan tersebut merambat ke berbagai lapisan masyarakat. Salah satu teknologinya adalah jejaring sosial. Pengguna media sosial di Indonesia sendiri mencapai 170 juta pengguna. Salah satunya adalah Facebook, di Indonesia sendiri tercatat 140 juta pengguna Facebook. Dari banyaknya pengguna Facebook tersebut maka juga semakin banyak juga informasi yang tersedia dan tersebar pada media tersebut salah satunya adalah lowongan kerja. Informasi lowongan kerja tersebut sangatlah membantu bagi para pencari kerja dan juga fresh graduate terlebih di masa pandemi covid-19. Pandemi covid-19 ini menciptakan dampak tersendiri pada sektor ketenagakerjaan, mulai dari kebijakan pemerintah mengenai pembatasan sosial, work from home dan juga terjadinya pemberhentian terhadap tenaga kerja oleh instansi di masa pandemi. Dengan informasi lowongan kerja pada media Facebook, dapat dilakukan ekstraksi informasi menggunakan text mining untuk menganalisis tren lowongan kerja yang ada dan membantu memetakan lowongan pekerjaan. Penggunaan TF-IDF sebagai metode pembobotan dan metode Decision Tree sebagai metode klasifikasi berguna dalam membantu analisa kategori dan tren lowongan pekerjaan yang ada. Penerapan dua metode tersebut berhasil karena telah mengklasifikasikan data dan juga perangkingan data secara aktual sesuai dengan aturan yang ada telah ditentukan pada penelitian ini. Dan juga sistem analisa menyajikan data yang mudah dipahami dan sesuai dengan hasil implementasi metode yang digunakan.
Empowering the Practice-Based Mentoring in Microteaching on Pre-Service ICT Teachers: High and Low Self-Efficacy Analysis Husni Mubarok; Yossiri Yossatorn; Hirnanda Dimas Pradana; Syaiputra Wahyuda Meisa Diningrat; Arqoma Nurveda Carreza; Favian Avila Syahmi
International Journal of Research and Community Empowerment Vol. 4 No. 1 (2026): February 2026
Publisher : Mitra Edukasi dan Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58706/ijorce.v4n1.p14-21

Abstract

Practice-based microteaching is now an important method in pre-service teacher education, particularly in ICT, as it creates a forum to practice teaching skills in a structured setting. However, the success of this depends greatly on the quality of guidance, which has the capacity to deliver timely and critical feedback. Self-efficacy, being the belief that an individual is capable of completing tasks, has been a significant predictor of learning achievement and motivation. The present research aims to examine the pre-service ICT teachers' learning achievement and the learning motivation of high and low self-efficacy individuals within a practice-based microteaching environment supported by mentoring. In experimental design, the subjects (N = 82) were divided into high and low self-efficacy according to a standardized self-efficacy scale. The data analysis in this study employed the t-test and Analysis of Covariance (ANCOVA). The findings of this study indicated there was no difference in learning achievement between the two groups on practice-based mentoring in microteaching for pre-service ICT teachers. Moreover, in intrinsic motivation, it was found that high self-efficacy practice-based mentoring microteaching students have significantly higher intrinsic motivation than low self-efficacy students. In the present study, however, low self-efficacy students for practice-based mentoring microteaching show significantly greater extrinsic motivation than high self-efficacy students. This research offers additional reference to scholars, teachers, and policymakers in investigating the role of self-efficacy in learning activity, learners' accomplishment in learning, and to supporting SDGs 4 and 5 in promoting the quality of education as well as gender equality.
OBE-Oriented Teaching Material for Visual Media Development: Supporting the Internationalization of the Educational Technology Study Program Utari Dewi; Andi Kristanto; Husni Mubarok; Kifle Kassaw Mulatu
International Journal of Research and Community Empowerment Vol. 4 No. 1 (2026): February 2026
Publisher : Mitra Edukasi dan Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58706/ijorce.v4n1.p42-49

Abstract

Globalization in higher education demands innovative learning resources that support international collaboration and digital-based instruction. Responding to this need, this study develops Outcome-Based Education (OBE)-based visual media lesson plans to strengthen the internationalization of the Educational Technology Study Program. This study used the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. A research and development approach was employed, involving expert validation and limited field trials with students in an Educational Technology program. The developed materials include OBE-aligned digital modules, instructional videos, worksheets, and project-based assessments integrated into an online learning management system. Validation results indicate a high level of feasibility in terms of content relevance, media quality, and visual design, while student trials suggest that the materials are practical and supportive of independent and collaborative learning. This study contributes a practical model for integrating OBE principles into digitally mediated courses that support international collaboration in higher education. The impact of this study lies in its contribution to improving students' global competencies, encouraging inter-institutional collaboration, and accelerating the internationalization of the Educational Technology Study Program. In addition, this study contributes to improving the quality of education in alignment with SDG 4 on Quality Education and strengthening internationalization efforts through global partnerships consistent with SDG 17 on Partnerships for the Goals.
The Potential of E-Learning in Understanding Concepts in Science and Physics Education: A Bibliometric Analysis Adrian Bagas Damarsha; Nadi Suprapto; Elvia Reza Lutfiani; Siti Nur Aisah; Husni Mubarok; Alif Syaiful Adam
Journal of Digitalization in Physics Education Vol. 2 No. 1 (2026): April
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jdpe.v2i1.52130

Abstract

Objective: The objective of this study is to describe trends, contributions, developments, and research opportunities in e-learning for conceptual understanding in physics and science education. Method: The research method employed was bibliometric analysis using the Scopus database. Data were obtained from the Scopus database using the search terms “E-Learning” AND “Physics Education” OR “Science Education” AND “Conceptual Understanding,” yielding 2,735 documents. The Scopus database was filtered by year, document type, and language, resulting in 2,363 documents for analysis. Results:  The results indicate that research on e-learning’s impact on conceptual understanding in physics or science education has been a trend over the past ten years. The top contributing authors are H, Gwo-Jen; S, Niwat; K, Heru; and S, Andi, while the top affiliations are Indonesia University of Education, Padang State University, and Malang State University. Current developments in e-learning have been categorized as artificial intelligence, so the opportunity for data-driven research lies in developing artificial intelligence for learning.  Novelty: Technological transformation has impacted the world of education, particularly in strategies to improve students’ conceptual understanding. This study presents a bibliometric mapping of e-learning research related to conceptual understanding in physics and science education. This study differs from previous research, which has not presented a thematic evolution to guide future research.
AI-Driven Adaptive Online Digital Modules for Communication Courses Using Learning Analytics and Natural Language Processing Utari Dewi; Andi Kristanto; Atan Pramana; Husni Mubarok; Rizki Fitri Rahima Uulaa; Arqoma Nurveda Carreza; Favian Avila Syahmi; Makibane Daniel Ntlhane
International Journal of Advances in Artificial Intelligence and Machine Learning Vol. 3 No. 2 (2026): International Journal of Advances in Artificial Intelligence and Machine Learni
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijaaiml.v3i2.689

Abstract

Background: The rapid growth of online learning in higher education requires innovative solutions that support independent, scalable, and standardized learning experiences. Artificial Intelligence (AI), particularly Learning Analytics (LA) and Natural Language Processing (NLP), offers opportunities to enhance digital learning through adaptive content delivery, personalized learning pathways, and automated formative feedback.Aims: This study aimed to develop and evaluate an AI-driven adaptive online digital module for Communication courses that supports personalized learning and standardized instruction across higher education institutions using Gemini.Methods: This study employed the ADDIE development model, comprising Analysis, Design, Development, Implementation, and Evaluation. Learning Analytics was used to monitor student engagement and learning progress, while NLP analyzed students' written responses to generate automated formative feedback. The module was validated by instructional design, subject matter, and media experts, followed by individual and small-group trials. Its effectiveness was evaluated using normalized gain (N-Gain) analysis.Results: Expert validation, individual trials, and small-group evaluations indicated that the developed module achieved a "very good" level of feasibility. The effectiveness evaluation produced a high N-Gain score (0.7), indicating a substantial improvement in student learning outcomes. The integration of Learning Analytics and NLP supported adaptive learning, timely feedback, and increased student engagement.Conclusion: The AI-driven adaptive digital module is feasible and effective for supporting online learning in Communication courses. Integrating Learning Analytics and Natural Language Processing enables personalized instruction and data-informed learning support, making the module a promising approach for improving learning quality in higher education.
Co-Authors Adrian Bagas Damarsha Alif Syaiful Adam Andi Kristanto Arqoma Nurveda Carreza Dedy Rahman Prehanto Elvia Reza Lutfiani Favian Avila Syahmi Kifle Kassaw Mulatu Makibane Daniel Ntlhane Nadi Suprapto Pramana, Atan Rizki Fitri Rahima Uulaa Siti Nur Aisah Syaiputra Wahyuda Meisa Diningrat Utari Dewi Yossiri Yossatorn