Implementasi Sistem Informasi Produksi Berbasis Website Menggunakan Algoritma Apriori pada Toko Kue Nona Cookies Pamulang

Nona Cookies Pamulang requires an integrated system to manage production records and present product association information. This study developed a web-based production information system using Python, Flask, and MySQL within the CRISP-DM framework. The documented dataset comprises 120 transactions involving eight products from January to March 2025. Apriori analysis uses support, confidence, and lift ratio. Arithmetic reconstruction of the reported Forrero Chocolate → Ring Cheese rule yields support of 19/120 (15.83%), confidence of 19/30 (63.33%), and lift of 1.900. These calculations confirm consistency among the reported aggregate values but do not independently validate the transaction data. The parameter comparison contains an inconsistency: three frequent itemsets at 5% support versus 38 at 10%, which violates support monotonicity for a fixed dataset and configuration. Therefore, the reported itemset and rule totals require verification against the original transaction-level output. Existing black-box documentation reports conformity at module level; additional test scenarios are specified separately and are not claimed as executed tests. The system provides integrated record management and information that may support raw material planning. Effects on stock availability, costs, and processing time have not been directly evaluated. Findings are limited to the observed transactions and period.