Salafiyah Hudatul Muna Islamic Boarding School Ponorogo faces challenges in grouping new students due to the ambiguity of the selection criteria. This study aims to develop a system based on the Apriori method to overcome this problem. The Apriori method is applied to analyze patterns and relationships between student data, using the Laravel framework and SQLite database. This system is designed with an intuitive and responsive interface, facilitating student data management.
Min-Max normalization is used to transform data into a consistent range (0-1), increasing the accuracy of the analysis. The test results show a high level of support and confidence in the tested itemset, and ensure the reliability of the function through white box testing. Grouping is done proportionally for 44 students into three classes: Class A, B, and C, with a proportion of 33% each. If test score data is available in the range 0-100, the grouping criteria can be determined based on the value, namely Class A (80-100), Class B (60-79), and Class C (0-59).
This research provides a significant contribution in improving the efficiency and clarity of grouping new students at the Salafiyah Hudatul Muna Islamic Boarding School.