INHAS: An AI-Driven Solution to Enhance SPSS Data Interpretation among Religious Higher Education Students

Abstrak

Many students at religious higher education institutions experience difficulties in interpreting statistical outputs generated by SPSS, which often leads to errors in data analysis and a decreased interest in conducting quantitative research. This study addresses this issue by developing an artificial intelligence–based application named INHAS (Interpretation of SPSS Analysis Results), designed to assist students in accurately interpreting SPSS output. The development of the application followed the ADDIE development model within a Research and Development (R&D) framework. The study involved one statistics expert, 15 students in the limited trial phase, and 50 students from religious higher education institutions in the broader implementation phase. Data were collected using expert validation sheets, student response questionnaires, and observation guidelines. The results of expert validation indicated a high level of accuracy (86.84%), while user evaluations in both the limited and extended trial phases demonstrated high levels of practicality (81.45% and 86.43%, respectively). These findings indicate that the INHAS application meets the criteria for a valid and practical learning medium. In conclusion, the development of INHAS effectively addresses the initial problem by enhancing students’ ability to interpret statistical data and fostering greater engagement in quantitative research.