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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) International Journal of Community Service (IJCS)
Rizkia Shaulita
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Integrasi Big Data dan AI untuk Pengambilan Keputusan dalam Smart City T. Irfan Fajri; Novi Rahayu; Handry Eldo; Giatika Chrisnawati; Rizkia Shaulita
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3860

Abstract

This research explores the integration of Big Data technology and Artificial Intelligence (AI) in decision-making in the context of Smart City. With the massive growth of data from various sources such as IoT, sensors, and information systems, Big Data is becoming an important foundation for in-depth analysis. Meanwhile, AI provides the ability to process data in real-time, identify patterns, and generate accurate recommendations. This research aims to analyze how the combination of these two technologies can improve efficiency, sustainability, and quality of life in cities. The methods used include literature review and case analysis in several smart cities. The results show that the integration of Big Data and AI can support faster, more precise, and data-driven decision-making, thus encouraging the creation of a smarter and more responsive city.
Strengthening Elementary School Teachers’ Digital Competence through AI-Based Instructional Design Training in Indonesia’s 3T Regions Hanafiah Hanafiah; Didi Sudrajat; Shaumiwaty Shaumiwaty; Rizkia Shaulita; Pascalian Hadi Pradana
International Journal of Community Service (IJCS) Vol. 5 No. 1 (2026): January-June
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijcs.v5i1.1852

Abstract

This quantitative study investigates the effectiveness of an artificial intelligence (AI)-based instructional design training program in strengthening the digital competence of elementary school teachers in Indonesia’s frontier, outermost, and underdeveloped (3T) regions. Education quality and access in 3T regions remain constrained by geographical isolation, limited infrastructure, and uneven professional development opportunities for teachers. Building on the European Digital Competence Framework for Educators (DigCompEdu) and its six areas of educator digital competence, the study designed a structured training program that introduced teachers to generative AI tools for lesson planning, resource development, and assessment. A one-group pretest–posttest design was implemented with 120 elementary school teachers from several 3T districts. Data were collected using a Likert-scale digital competence questionnaire adapted from DigCompEdu and analyzed with descriptive statistics and paired-sample t-tests. Findings show statistically significant improvements in teachers’ overall digital competence scores across all six DigCompEdu areas, with the largest gains in “Teaching and learning” and “Facilitating learners’ digital competence.” The results indicate that contextually grounded AI-based instructional design training can be an effective strategy to narrow digital competence gaps between teachers in peripheral and non-peripheral regions. Implications for policy, teacher professional development, and further research on AI-supported pedagogy in disadvantaged contexts are discussed.
Co-Authors Didi Sudrajat Giatika Chrisnawati Hanafiah Hanafiah Handry Eldo Novi Rahayu Pascalian Hadi Pradana Shaumiwaty Shaumiwaty Siswahyudianto