PENGEMBANGAN E-MODUL BERBASIS ARTIFICIAL INTELIGENCE YANG TERINTEGRASI AJARAN TRI-NGA DALAM MENINGKATAN KEMANDIRIAN SISWA DI SEKOLAH DASAR

Abstract

The aims of this research are (1) to produce an Artificial Intelligence-based E-module integrated with Tri-Nga to Improve Independence in elementary schools. (2). testing the feasibility of Artificial Intelligence-based E-modules integrated with Tri-Nga to increase Independence in elementary schools. (3). testing the effectiveness of Artificial Intelligence-based E-modules integrated with Tri-Nga to increase Independence in elementary schools. This research uses R&D method. Data collection techniques use interviews, observation sheets, questionnaires and tests. Data analysis techniques use qualitative and quantitative data analysis techniques. The research subjects were 11 students at SDN Tambakromo III Ponjong. This research methodology is based on the ADDIE (Analyze, Design, Development, Implementation, Evaluation) development model. The results of this study are (1) the product produced is an Artificial Intelligence-based E-module integrated with Tri-Nga (2) The validation results of 3 experts with a result of 92.67% and the validation results of 4 stakeholders of 83.5% indicate that the E-module based on Artificial Intelligence integrated with Tri-Nga is suitable for use in learning, and (3) Based on the results of observations in trials using a Likert scale, there was an increase in the average initial independence score, namely 2.4 increasing to 3.45 in limited trials and increasing to 3.6 in extensive trials. The results of the effectiveness test with SPSS measured an increase in the average post-test results from from 44,500 to 89,000 or 44,500. This is also reinforced by the results of the T-Test based on the "Independent Samples Test" output table. It is known that based on the t table value (0.05/2);38, it is obtained as 19.043 > dari T-table 2.024. Apart from that, based on the "Independent Samples Test" output table, the Sig value is known. (2-tailed) is 0.001 < 0.05, so Ho is rejected and Ha is accepted. Thus, it can be concluded that  the artificial intelligence-based E-module integrated with Tri-Nga is effective in improving independence students' in elementary school.