DEVELOPMENT OF A PERSONNEL INFORMATION SYSTEM FOR EDUCATIONAL STAFF AT HALU OLEO UNIVERSITY (UHO) USING B+ TREE AND FULL-TEXT SEARCH ALGORITHMS

Abstract

The management of educational staff personnel data at the Personnel Division of the Rectorate of Halu Oleo University still relies on spreadsheets and physical archives, resulting in slow data retrieval and a high risk of inconsistencies. This study develops a web-based personnel information system that integrates the B+ Tree algorithm for structured employee data searches based on employee identification numbers and names, and Full-Text Search for retrieving information from administrative documents processed using Optical Character Recognition (OCR). The system was developed using the Waterfall methodology, with Python, Django, and MySQL as the primary technologies. Black-box functional testing involving 38 scenarios across three user access levels demonstrated that all system features functioned correctly. The B+ Tree search achieved 100% accuracy with an average response time of 3.338 seconds, while Full-Text Search achieved a 100% search success rate with an average response time of 0.0914 seconds and a text extraction success rate of 96.88%. User Acceptance Testing (UAT) produced an average score of 4.09, corresponding to the "Agree" category, indicating that the developed system is suitable for replacing manual personnel data management processes.