Implementation of the Logic Model in the Evaluation of New Student Admissions Online
This article aims to describe the application of the Logic Model in the Evaluation of New Student Admissions (PPDB) Online. The research used is field research using a quantitative descriptive approach and evaluation methods. To describe the evaluation of PPDB used, a logic model (logic model). The...
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Veröffentlicht in: | Nidhomul haq 2022-10, Vol.7 (2), p.307-317 |
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Format: | Artikel |
Sprache: | ara ; eng |
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Zusammenfassung: | This article aims to describe the application of the Logic Model in the Evaluation of New Student Admissions (PPDB) Online. The research used is field research using a quantitative descriptive approach and evaluation methods. To describe the evaluation of PPDB used, a logic model (logic model). The components to be evaluated include input, activity, and output components. The research was conducted at a public high school in the Dharmasraya district. The data source for this research is the PPDB committee consisting of principals, teachers, and education staff, totaling 140 people. The data collection technique used an instrument in the form of a questionnaire with the content validity test using the Aiken test and the construct validity test applying the Confirmatory Factor Analysis (CFA). After that, the reliability test was carried out, and continued to analyze the data using descriptive statistics with central tendency. The results were obtained in evaluating the PPDB program at SMA Negeri in Dharmasraya Regency with a logic model covering input, activity, and output components. Achievement of quality on the input component with good category. Achievement of quality in the activity component with a good class. In contrast, the achievement of quality in the output component is categorized as good. Overall, the three branches of online PPDB quality achievement at SMA Negeri in Dharmasraya district are classified as good, with an average of 82.10. This condition must be maintained and evaluated periodically to improve the following year's PPDB. |
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ISSN: | 2503-1481 2503-1481 |
DOI: | 10.31538/ndh.v7i2.2178 |