<![CDATA[Salons face challenges in reservation management, service time estimation, and leveraging transaction data for promotions. Existing studies typically develop information, reservation, and recommendation systems separately, while reservation systems often overlook service combinations, quantities, and the parallel execution of services. This study develops a Salon Information System (SIS) that integrates a bundling recommendation system based on the Apriori algorithm with a reservation system that estimates service duration using a brute-force method. The study's novelty lies in the direct integration of SIS transaction data into the recommendation system (eliminating the need for data re-entry), and the calculation of service times that account for both parallel and sequential service workflows. The system was developed based on case studies of three salons in Surabaya, with a requirements analysis involving 53 respondents. The recommendation system was tested using 64 transaction records, applying a minimum support of 20% and a minimum confidence of 80%. Evaluation was conducted through black-box testing, user validation using a 1–4 Likert scale, and a one-sample t-test. All system functions operated as expected. Average user ratings were 3.71 for administrative staff, 3.50 for therapists, and 3.82 for customers. Statistical test results yielded t-values of 5.83 and 14.94, exceeding the critical values at the 5% significance level. The recommendation system generated bundling rules with confidence levels of up to 100%. In practice, the system supports reservation management, uses transaction data to deliver more relevant promotions, and enables more accurate estimation of service capacity.]]>
