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Acceptance and Success Model for AI Use in Higher Education: Development, Instrument Decomposition, and Its Triangulation Testing Subiyakto, Aang; Huda, Muhammad Q; Hakiem, Nashrul; Suseno, Hendra B; Arifin, Viva; Azmi, Agus N; Sani, Asrul; Yuniarto, Dwi; Hartawan, Muhammad S; Suryatno, Agung; Muji, Muji; Kurniawan, Fachrul; Kusumawati, Ririen; Balogun, Naeem A; Ahlan, Abd. Rahman
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.619

Abstract

Prior social computing studies described that the performance of technology products is about how the product use benefits the users, including Artificial Intelligence (AI). To have an impact, ensuring how AI is used is a prerequisite after the development. Furthermore, its use is also influenced by how users accept AI. This study aimed to develop an acceptance and success model of AI use in the higher education world from the user perspective, to decompose the model into its instrument level, and to test the validity and reliability of the research instrument. The researchers developed the model by adopting and combining the Technology Acceptance Model (TAM) and the Information System Success Model (ISSM) and adapting the proposed model in the context of AI use in higher education learning. The measurement items were derived from definitions of the variables and indicators of the model. The instrument was tested sequentially using triangulation methods. The quantitative testing was online survey with about 51 respondents and the qualitative one was interview involving five experts. This study may contribute methodologically as one of the guidance for novice scholars in similar works. It may relate to the clarity of the research procedure and the implementation of the mixed testing methods. Of course, the assumptions, samples, and data used in the study cannot be generalized for the other studies. Referring to the model development, the proposed model may not cover the other factors related to the ethical, cultural, and organizational barriers for adopting AI. These barriers may also affect its acceptance and success. Thus, the adoption of the factors related the barriers may also be interesting to study further.
Enhancing Student Engagement in Islamic Religious Education Through a Finite-State Machine and Guided Inquiry-Based Serious Game Marandy, Yuniar Setyo; Nugroho, Fresy; Kusumawati, Ririen; Handayani, Tuti; Marudin, Marudin
Didaktika Religia Vol. 13 No. 2 (2025): December
Publisher : Postgraduate Program, Institut Agama Islam Negeri (IAIN) Kediri, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/didaktika.v13i2.3611

Abstract

This study aims to develop interactive learning media in the form of a serious game based on Finite State Machine (FSM) and guided inquiry approach to improve student engagement and understanding of Islamic Education material, especially the exemplary story of Ashabul Kahfi. The research method used is Research and Development (R&D) with the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) development model. The game was developed with enemy characters based on Finite State Machine (FSM), consisting of three main conditions: patrol, pursuit, and return to the path, to create dynamics and challenges in educational games. Fourth-grade elementary school students were the main subjects in testing the effectiveness of the media, which involved pre-tests and post-tests to measure learning outcome improvement, as well as validation by subject matter and media experts. The results showed that the developed media met the feasibility criteria with a subject matter expert validation score of 3.5 and a media expert validation score of 4.0, as well as an N-Gain value of 0.53, which is in the moderate category. These findings indicate that the combination of FSM and guided inquiry methods in serious games can create an interactive, enjoyable, and effective learning experience that increases student engagement and critical thinking skills in PAI material. The research results recommend this media as an alternative for interactive digital learning at the elementary school level.
Development of Academic Community Recommendation System Using Content-Based Filtering at UIN Malang Informatics Engineering Study Program Abdurrozzaaq Ashshiddiqi Zuhri; Ririen Kusumawati; Muhammad Ainul Yaqin; Aldian Faizzul Anwar; Achmad Fahreza Alif Pahlevi
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1916

Abstract

The mismatch between the number and quality of Information and Communication Technology (ICT) talents and industry needs in Indonesia creates significant challenges, especially for Informatics Engineering students who often experience difficulties in determining the appropriate professional field. This research aims to develop a content-based filtering-based academic community recommendation system to help students choose communities that are relevant to their interests, skills and experience. The system uses TF-IDF and cosine similarity methods to match student profiles with community descriptions. Data was collected from 48 students and 10 academic communities in the Informatics Engineering Study Program of UIN Malang, and processed through preprocessing stages before modeling. Evaluation results using the System Usability Scale (SUS) resulted in a score of 76, which is categorized in the “good” level, However, users indicated the need for improved guidance in navigating the system. This system is expected to be an innovative solution to increase student participation in appropriate academic communities, as well as support the development of their potential and readiness for the world of work