Pengembangan E-Modul Akuntansi Persediaan Berbasis Pendekatan Deep Learning untuk Meningkatkan Kemandirian dan Hasil Belajar Siswa: Development of an Inventory Accounting E-Module Based on a Deep Learning Approach to Enhance Student Independence and Learning Outcomes - Rakhmayanti Rakhmayanti; Ali Muhtadi (ITScience (Information Technology and Science), 2026)
Issues were identified regarding the suboptimal learning independence of Phase F Vocational High School (SMK) accounting students and their low cognitive learning outcomes. This situation persisted despite the use of learning modules that previous research showed could positively enhance student independence and learning outcomes. Observations revealed that the printed modules used to facilitate learning failed to provide relevant learning experiences; they lacked interactivity, challenge, and contextual relevance. Consequently, this study aimed to develop an inventory accounting e-module based on the deep learning approach—designed to enhance the learning independence and outcomes of Phase F SMK students—and to evaluate the product's practicality and effectiveness. The development procedure followed the ADDIE approach (Branch, 2009): Analyze, Design, Develop, Implement, and Evaluate. The trial employed a quasi-experimental, non-equivalent control group design and took place at SMK Negeri 1 Yogyakarta. The subjects included 21 students in the control group, 21 students in the experimental group, and one teacher who taught both classes in parallel. Data were collected using questionnaires and tests, then analyzed through descriptive quantitative methods and inferential statistics. The results indicate that the deep learning-based inventory accounting e-module is highly suitable for improving student learning independence and outcomes; users deemed it practical, and it proved effective in enhancing the learning independence and outcomes of Phase F SMK students.