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All Journal Jumat Informatika: Jurnal Pengabdian Masyarakat Newton : Networking And Information Technology
Cahyaningtyas, Dhita
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Computer Science & IT Education Other

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Implementation of Apriori and Fp-Growth Algorithms In Forming Association Patterns Based On Unwaha Cooperative Sales Transactions Cahyaningtyas, Dhita; Miftachuddin, Achmad Agus Athok
NEWTON: Networking and Information Technology Vol. 4 No. 2 (2024): October
Publisher : LPPM Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/newton.v4i2.5085

Abstract

This study implements the Apriori and FP-Growth algorithms to identify association rules in sales transaction data from the UNWAHA Multi-Purpose Cooperative. Both algorithms successfully discovered product relationships, with similarities in rules for items like MAKARONI ASEP, KRUPUK PAK JONO, and KRUPUK 500. The FP-Growth algorithm, implemented using RapidMiner, outperformed Apriori in processing speed by 11 seconds and demonstrated higher accuracy in rule generation. Optimal results were achieved with minimum support and confidence values of 0.3 and 0.9 for Apriori (generating 5 rules), and 0.52 and 0.9 for FP-Growth (generating 6 rules). These settings balanced between generating too many rules, which could complicate interpretation, and too few, which might miss important patterns. Based on the analysis, strategic recommendations for the cooperative include implementing product bundling and discounts for frequently co-purchased items nearing expiration, optimizing product placement by grouping commonly associated items (e.g., MAKARONI ASEP, KRUPUK PAK JONO, KRUPUK 500, SOSIS SO NICE, and YUPI ALL VARIAN 5G) in easily accessible locations, and increasing stock for high-demand products like LE MINERALE. This research demonstrates the practical application of association rule mining in retail, offering data-driven insights to enhance sales strategies and inventory management for the UNWAHA Cooperative.
Sosialisasi Program Penyiraman Tanaman Hias Secara Otomatis Berbasis Arduino Sufaidah, Siti; Lilawati, Emi; Arya Dinta, Firda; Khofifah, Khofifah; Wijanarko, Eko Bayu; Cahyaningtyas, Dhita
Jumat Informatika: Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2024): April
Publisher : LPPM Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/abdimasif.v5i1.4243

Abstract

Janti Village is a village in Mojoagung sub-district with a population of around 3,570 people. The Janti village community has a variety of potential, especially in the agricultural and crafts sectors. The women in Janti village have an interest and hobby in planting ornamental plants in front of the house. These ornamental plants are an important part of the beauty and aesthetics of their environment. Even though they have a great love and interest in ornamental plants, they often face several obstacles in caring for these plants. One of the main obstacles is their busy daily lives. The community service team consisting of lecturers and students offers collaboration on developing an automatic watering tool, namely an Adruino-based ornamental plant watering tool. The method used is socialization and practicing how to use automatic watering tools. With this system, we hope to provide concrete benefits to the people of Janti Village, improve their quality of life, and utilize technology to support daily activities
Implementation of Apriori and Fp-Growth Algorithms In Forming Association Patterns Based On Unwaha Cooperative Sales Transactions Cahyaningtyas, Dhita; Miftachuddin, Achmad Agus Athok
NEWTON: Networking and Information Technology Vol. 4 No. 2 (2024): October
Publisher : LPPM Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/newton.v4i2.5085

Abstract

This study implements the Apriori and FP-Growth algorithms to identify association rules in sales transaction data from the UNWAHA Multi-Purpose Cooperative. Both algorithms successfully discovered product relationships, with similarities in rules for items like MAKARONI ASEP, KRUPUK PAK JONO, and KRUPUK 500. The FP-Growth algorithm, implemented using RapidMiner, outperformed Apriori in processing speed by 11 seconds and demonstrated higher accuracy in rule generation. Optimal results were achieved with minimum support and confidence values of 0.3 and 0.9 for Apriori (generating 5 rules), and 0.52 and 0.9 for FP-Growth (generating 6 rules). These settings balanced between generating too many rules, which could complicate interpretation, and too few, which might miss important patterns. Based on the analysis, strategic recommendations for the cooperative include implementing product bundling and discounts for frequently co-purchased items nearing expiration, optimizing product placement by grouping commonly associated items (e.g., MAKARONI ASEP, KRUPUK PAK JONO, KRUPUK 500, SOSIS SO NICE, and YUPI ALL VARIAN 5G) in easily accessible locations, and increasing stock for high-demand products like LE MINERALE. This research demonstrates the practical application of association rule mining in retail, offering data-driven insights to enhance sales strategies and inventory management for the UNWAHA Cooperative.
Co-Authors Arya Dinta, Firda Khofifah Khofifah Lilawati, Emi Miftachuddin, Achmad Agus Athok Sufaidah, Siti Wijanarko, Eko Bayu