Local Wisdom (Loka Tua Mata Api) and Technology: A Health Tracking Application for Early Detection of Student Health
DOI:
https://doi.org/10.70716/mohr.v4i2.468Keywords:
Student health, Health tracking, Local wisdom, Early detection, Mobile Health ApplicationAbstract
This study was motivated by the still-limited monitoring of student health, which is carried out manually, not systematically documented, and not yet supported by contextual, user-friendly digital media. This study aimed to develop an application that is valid, practical, and user-friendly to help students monitor their health conditions independently. The method used was Research and Development, using the ADDIE model through the stages of Analysis, Design, Development, Implementation, and Evaluation, while also applying a mixed-methods approach. The research subjects included needs analysis informants, three expert validators, and students involved in one-to-one testing, small-group testing, and field testing. The results showed that the application obtained an average Aiken's V validity score of 0.92, practicality levels of 84.67% in the small-group test and 88.40% in the field test, and a System Usability Scale score of 81.3. The average pretest score of 62.80 increased to 81.47 in the posttest, with a significant difference. Therefore, the developed application shows potential as a contextual, adaptive, and feasible medium for health recording, education, and early detection of student health, and warrants further development.
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