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Implementation of Interactive Digital Media: A Case Study of Articulate Storyline in Indonesian Language Learning Nisa, Khoirin; Ansori, Isa
Journal of Practice Learning and Educational Development Vol. 5 No. 4 (2025): Journal of Practice Learning and Educational Development (JPLED)
Publisher : Global Action and Education for Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58737/jpled.v5i4.755

Abstract

The limited active participation of students in Indonesian language learning at the elementary school level remains a pedagogical challenge that has not been effectively addressed. Conventional teacher-centered practices tend to create passive learning environments and diminish students’ enthusiasm for learning. To address this issue, the present study aims to examine the effectiveness of the Articulate Storyline platform in enhancing fourth-grade elementary students’ engagement in Indonesian language learning. Employing a qualitative case study design, the research involved 25 students and one teacher from SDN Jekulo 02 Kudus. Data were collected through participant observation, in-depth interviews, and documentation, and were analyzed using the Miles and Huberman interactive model. The findings reveal that the implementation of Articulate Storyline significantly increased students’ activeness in asking questions (from 32% to 84%), participation in discussions (40% to 92%), concentration in learning (48% to 96%), and enthusiasm in completing assignments (36% to 88%). The media also facilitated spontaneous collaboration, independent learning, and the development of listening, speaking, reading, and writing skills. Its interactive and contextually relevant multimedia features proved to be the primary drivers of increased student motivation. Nevertheless, limitations in device availability and digital literacy emerged as technical barriers that need to be addressed. The study recommends the sustainable integration of interactive digital media, accompanied by teacher training and the development of adaptive local content, as a strategy for transforming Indonesian language learning in elementary schools.
PELATIHAN STATISTIKA DESKRIPTIF UNTUK DATA ADMINISTRATIF DESA DI KECAMATAN TANJUNG RAJA KABUPATEN LAMPUNG UTARA saidi, subian; Netti Herawat; Misgiyati; Khoirin Nisa; Agus Sutrisno
BUGUH: JURNAL PENGABDIAN KEPADA MASYARAKAT Vol. 6 No. 1 (2026): Maret 2026
Publisher : Badan Pelaksana Kuliah Kerja Nyata Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/buguh.v6n1.3385

Abstract

Data administratif merupakan kumpulan data yang memiliki sifat nyata tentang sesuatu yang dianggap penting dan disimpan secara sistematis dalam sebuah sistem untuk mendapatkan suatu informasi tentang suatu hal yang berhubungan dalam ruang lingkup tertentu. Catatan administrasi Desa yang dikumpulkan mempunyai tujuan pengambilan keputusan tertentu, sehingga adanya satuan identitas yang memiliki kesesuaian dengan catatan tertentu sangat penting. Perlu dilakukan analisis terhadap data yang sudah diperoleh. Tujuannya adalah agar masyarakat dapat melihat gambaran jelas terkait data yang diperoleh dan juga memudahkan perangkat Desa untuk mengambil keputusan terkait kebijakan yang akan diambil. Oleh karena itu akan dilakukan pelatihan dan sosialisasi terkait pelatihan analisis data deskriptif bagi perangkat desa di kecamatan Tanjung Raja kabupaten Lampung Utara. Sehingga diharapkan kedepannya gambaran terkait data dapat dipublikasikan dalam bentuk yang mudah untuk dipahami yaitu dengan statistika deskrptif.
A Hybrid AI–SEMPLS Model for Digital Visualization Acceptance in Blue Tourism: Evidence from Lampung Province Alita, Debby; Nisa, Khoirin; Styawati; Amelia, Dina
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i2.2909

Abstract

Blue tourism destinations often lack advanced digital tools capable of providing real-time, AI-driven visualization and user-centered information services. This study addresses this gap by developing JELAMBU, an AI-enabled digital visualization platform, and by evaluating user acceptance through a hybrid SEMPLS models. The research aims to: (i) design and implement an AI-based system that combines chatbot interaction, realtime sentiment analytics, and digital visualization; and (ii) examine the determinants of tourists’ intention to adopt AI-enabled e-tourism technologies. A structured questionnaire was administered to 467 visitors of destinations, and 16 hypotheses were tested. The results show that platform design, facilitating conditions, AI technology, perceived ease of use, perceived usefulness, social influence, service quality, trust, and risk perception significantly shape intention to use, whereas information quality, perceived benefits, and performance expectancy do not show significant effects. The model demonstrates substantial predictive power (R² = 0.703), strong effect sizes (f² > 0.225), and acceptable fit (SRMR = 0.084). These findings highlight the pivotal role of design and system conditions in AI-driven tourism platforms and provide practical guidance for developers and policymakers in strengthening digital visualization, personalization features, and sustainable blue tourism management. Future studies may extend this framework to multi-regional settings or longitudinal adoption scenarios.