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All Journal International Journal of Electrical and Computer Engineering CALYPTRA : Jurnal Ilmiah Mahasiswa Universitas Surabaya Jurnal GEMATIKA Seminar Nasional Informatika (SEMNASIF) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputer Terapan Applied Information System and Management MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JAST : Jurnal Aplikasi Sains dan Teknologi Jurnal Bisnis Terapan Community Development Journal Jurnal Informatika dan Sistem Informasi (JUISI) Keluwih: Jurnal Sains dan Teknologi Teknika Warta LPM
Susana Limanto
Universitas Surabaya
Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

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Integration of a Salon Information System with the Apriori-Based Recommendation System and Reservation Optimization Liliana Liliana; Susana Limanto; Kenny Reandy Kwando; Gede Darma
Applied Information System and Management (AISM) Vol. 9 No. 2 (2026): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v9i2.50530

Abstract

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.
Co-Authors Andre Andre Arie Indrawan Asmawati, Endah Daniel Soesanto Dhiani Tresna Absari Dionisius Dwi Putra Ellysa Tjandra Endah Asmawati Febriyanti, Anastasya Fenny Cahyawati Gede Darma Gitaputri, Ni Wayan Handani, Felix Hendra Dinata Heru Arwoko Heru Arwoko Heru Arwoko Jason Austin Juwono Kenny Reandy Kwando Liliana Liliana Liliana Liliana Louk, Maya Hilda Lestari Mahendra Saputra Setiaadi Mario Matthew Cardinal Vincent Maya Hilda Lestari Louk Maya Hilda Louk Mirella Mercifia Ni Wayan Gitaputri Pramono, Richard Prijambodo, Bambang Purba, Surono Ristiyana, Amelia Winda Soesanto, Daniel Steven Ming Tyrza Adelia Vincentius Riandaru Prasetyo vincentius Riandaru Prasetyo