School Profile Website using the K-Means Algorithm at the Minahasa Regency Education Office

Abstract

Background: The Education Office often manages school profiling with minimal and fragmented data, such as school name, district, level, total students, and total teachers. This situation makes planning reactive and error-prone, highlighting the need for a lightweight yet reliable workflow to transform aggregated data into actionable evidence. Method: This study developed a web-based profiling tool that integrates a user interface designed using a User-Centered Design (UCD) approach with a transparent K-Means clustering algorithm. Development was carried out through iterative prototyping, with features standardized using z-scores and cluster validity assessed using the silhouette method along with other internal validity indices. Results: Data entry features with header previews and numeric checks effectively reduced rework. The silhouette value peaked at $k=2$, producing two interpretable segments (moderate vs. high staffing load), with an optional $k=3$ for exploratory purposes. Usability evaluation using the System Usability Scale (SUS) yielded a score of approximately 82, indicating good user acceptance, with system response times measured in seconds.
Conclusion: The system provides a streamlined and sufficient workflow for routine planning and establishes a foundation for future longitudinal developments, such as tracking the number of study groups and accreditation per period.