The Effectiveness of Big Data Utilization in Recruiting New Students at SDN 4 Ciawi, Tasikmalaya Regency

Abstract

This study aims to describe the use of big data, analyze its effectiveness, and identify supporting and inhibiting factors in the process of New Student Admissions (PPDB) at SDN 4 Ciawi, Tasikmalaya Regency. The research uses a descriptive qualitative approach with data collection techniques in the form of observation, school profile documentation (Dapodik), student data, study group data, infrastructure data, student attendance lists for the current month, and PPDB policy documents. The data analysis refers to the Miles and Huberman model, including reduction, presentation, and drawing conclusions accompanied by triangulation of sources. The results of the study show that SDN 4 Ciawi already has a fairly complete digitized database, covering 211 students in six study groups, nine educators and education staff, as well as adequate facilities, but the use is still administrative. There was a discrepancy between the data of the study group on Dapodik (215 students) and the real data on the class attendance list (211 students) on four of the six groups, as well as a number of infrastructure used that has not been formally recorded in the school database. The PPDB process for the 2025/2026 Academic Year has been running transparently according to schedule, but has not utilized historical registration data for predictive analysis. Supporting factors include the completeness of data and the availability of school operators, while inhibiting factors include suboptimal data synchronization and limitations in analytical competence.