SISTEM INFORMASI KPI UNTUK ANALISIS KINERJA KARYAWAN MENGGUNAKAN NAIVE BAYES DI PT JEMBATAN DATA PANGRANGO

This study developed a KPI (Key Performance Indicator)-based information system to analyze employee performance as HRD support at PT Jembatan Data Pangrango, an internet service provider in Sukabumi. The system is designed to replace inefficient manual methods for monitoring and evaluating employee performance.
The system was built using Django, a Python-based framework that supports rapid, scalable, and efficient web application development. Using the Software Development Life Cycle (SDLC) approach, the system enables KPI value recording from attendance and work activity data, anomaly detection, and performance pattern analysis based on predefined indicators. The system also classifies employee performance and assists HRD in evaluating and planning employee development.
The Naive Bayes algorithm was integrated to classify employee performance probabilistically based on historical data, such as attendance records, work results, and activity logs. The combination of Python and Django simplifies the implementation of this algorithm, which is reliable for handling large datasets in predictive analysis.
Testing results show that the system achieves a high level of accuracy based on Naive Bayes algorithm tests and functional testing using the black-box method. The system can detect patterns of attendance, tardiness, and productivity, supporting HRD in data-driven decision-making.
Keywords: KPI-Based Information System, Employee Performance, HRD, Performance Evaluation, Naive Bayes, Django, Python.