Penerapan Metode Asosiasi Menggunakan Algoritma Apriori pada Penjualan Produk Tenun
- Muhammad Rijalul Abthol Universitas Islam Nahdlatul Ulama, Jepara, Indonesia
- Gentur Wahyu Nyipto Wibowo Universitas Islam Nahdlatul Ulama, Jepara, Indonesia
-
Nadia Annisa Maori
*
Universitas Islam Nahdlatul Ulama, Jepara,
Indonesia
(*) Corresponding Author
Abstract
The development of information technology has led to a significant increase in the volume of sales transaction data stored in business information systems. Such data possess substantial potential to generate strategic insights when properly analyzed. However, in many small and medium-sized enterprises (SMEs), transaction data have not yet been optimally utilized. This study aims to apply association analysis using the Apriori algorithm to sales transaction data of woven products at Sientong Tenun in order to identify consumer purchasing patterns based on support and confidence values. The research adopts a quantitative approach employing data mining methods on sales transaction data that have undergone a data preprocessing stage. The final dataset used in this study consists of 120 sales transactions. The parameters applied in the analysis include a minimum support threshold of 20% and a minimum confidence threshold of 60%. The results indicate that all main products meet the criteria for frequent 1-itemsets, with Woven Fabric and Shawl exhibiting the highest support values, at 65.00% and 58.33%, respectively. The strongest association rule identified is Woven Fabric → Shawl with a confidence value of 70.51%, followed by Woven Fabric and Shawl → Woven Sarong with a confidence value of 63.64%. These findings demonstrate a significant purchasing relationship among woven products. The results of this study can be utilized by business practitioners to support marketing strategies, sales bundle development, product arrangement, and data-driven inventory management. Furthermore, this research contributes academically to the application of the Apriori algorithm within the culturally based creative industry sector.
Downloads
References
Abidin, Z., Amartya, A. K., & Nurdin, A. (2022). Penerapan Algoritma Apriori Pada Penjualan Suku Cadang Kendaraan Roda Dua ( Studi Kasus : Toko Prima Motor Sidomulyo ). Jurnal Teknoinfo.16(2), 225–232. DOI:10.33365/Jti.V16i2.1459
Albab, M. U., & Hidayatullah, D. (2022). Penerapan Algoritma Apriori Pada Sistem Informasi Inventori Toko. Jurnal Media Informatika Budidarma. 6(3), 1321–1328. Https://Doi.Org/10.30865/Mib.V6i3.4160
Anggraini, F. (2025). Implementasi Business Intelligence Pada Rekomendasi Produk Agrowisata Durian. Jurnal Pengabdian Kepada Masyarakat Nusantara. 6(4), 4780–4787. DOI: 10.46576/Djtechno
Anggrawan, A., & Satria, C. (2021). Menentukan Akurasi Tata Letak Barang Dengan Menggunakan Algoritma Apriori Dan Algoritma Fp-Growth Determination Of Item Layout Accuracy Using Apriori Algorithm And Fp-Growth Algorithm. Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer. 21(1), 125–138. Https://Doi.Org/10.30812/Matrik.V21i1.1260
Astuti, T. W., Jagat, L.. (2024). Prosiding Seminar Hasil Penelitian Dan Pengabdian Kepada Masyarakat Pengembangan Produk Umkm Berdasarkan Preferensi Pasar Prosiding Seminar Hasil Penelitian Dan Pengabdian Kepada Masyarakat. Prosiding seminar hasil penelitian dan pengabdian kepada masyarakat. 7(1), 117–124. Https://Doi.Org/10.47767/Sehati_Abdimas.V7i1
Bulu, E., Pati, G. K., & Rato, K. W. (2024). Application Of Data Mining Using Apriory. Journal of electrial and system control engineering. 7(2). Https://Doi.Org/10.31289/Jesce.V6i2.10552
Febryan, F. (N.D.). Implementasi Data Mining Pada Produk Fashion Baju Etnic Tenun Di Cv Assojar Dengan Metode Algoritma Apriori. Jurnal Media Informatika Budidarma. 4(1), 50-56. DOI:10.30865/Jurikom.V10i2.5795
Saputra, A., Sari, H. L., & Sartika, D. (2023). Implementasi Metode Association Rule Mining Pada Penjualan.Jurnal Multi Disiplin Dehasen. 2(4), 709–718. DOI:10.47065/Josyc.V4i4.4043
Fernando, D. (2020). Penerapan Data Mining Rekomendasi Buku Menggunakan Algoritma Apriori.Jurnal Sistem Informasi (JSil). 7(1), 50–56. DOI:10.30656/Jsii.V7i1.1899
Gunawan, C. E., Purwani, F., & Jannah, A. M. (2025). Pola Peminjaman Buku Di Perpustakaan Daerah : Pendekatan Algoritma Apriori.Journal of software engineering and computational intelligence. 2(2), 66–74. DOI: Https://Doi.Org/10.36982/Jseci.V2i02.4839
Jessfry, V., Siddik, M., (2024). Penerapan Data Mining Menggunakan Algortima Apriori Dalam. Journal Of Information systems and informatics 8(1), 187–199. DOI:10.35959/Jik.V10i2.385
H, Kusumo. (2019). Analisis Algoritma Apriori Untuk Mendukung Strategi Promosi Perguruan Tinggi. Walisongo Journal of information technology. 1(1), 49–60. DOI:10.21580/Wjit.2019.1.1.4000
Junaidi, A. (2019). Implementasi algoritma apriori dan fp growth untuk persediaan barang. Jurnal Sisfokom. 08, 61–67. DOI:10.32736/Sisfokom.V8i1.604
Luhur, J. (2020). Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Meningkatkan Pola Penjualan Obat.Jurnal teknik informatika dan sistem informasi. 7(2). DOI:10.35957/Jatisi.V7i2.195
Mai, P., Tarigan, S., & Hardinata, J. T. (2022). Implementasi Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Persediaan Barang ( Studi Kasus : Toko Sinar Harahap ) Implementation Of Data Mining Using Apriori Algorithm In Determining Inventory ( Case Study : Sinar Harahap Store ). Jurnal Janitra informatika dan sistem informasi. 2(1), 9–19. Https://Doi.Org/10.25008/Janitra.V2i1.142
Jaya, S. (2023). Implementasi Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Persediaan Barang (Studi Kasus: Toko Swapen Jaya Manokwari). G-Tech : Jurnal teknologi terapan. 7(1), 119–126. DOI:10.33379/Gtech.V7i1.1938
Prasetya, T., Yanti, J. E., Purnamasari, A. I., & Dikananda, A. R. (2021). Analisis Data Transaksi Terhadap Pola Pembelian Konsumen Menggunakan Metode Algoritma Apriori. Journal Informatic for education and professionals. 6(1), 43–52. DOI: 10.51211/Itbi.V6i1.1688
Prasetyo, A., Musyaffa, N., & Sastra, R. (2020). Implementasi Data Mining Untuk Analisis Data Penjualan Dengan Menggunakan Algoritma Apriori ( Studi Kasus Dapoerin ’ S ). Jurnal Khatulistiwa informatika. Viii(2). DOI: Https://Doi.Org/10.31294/Jki.V8i2.8994.G4535
Rosmayati, I., Wahyuningsih, W., Harahap, E. F., Hanifah, (2018). Implementasi Data Mining Pada Penjualan Kopi Menggunakan Algoritma Apriori. Jurnal Algoritma Institute teknologi garut. 52, 99–107. DOI: Https://Doi.Org/10.31539/Intecoms.V7i5.11644
Takdirillah, R. (2020).Penerapan data mining menggunakan algoritma apriori terhadap data transaksi sebagai pendukung informasi strategi penjualan. Edumatic : Jurnal Pendidikan Informatika. 4(1), 37–46. Https://Doi.Org/10.29408/Edumatic.V4i1.2081
Violita. (2025). Integrasi Algoritma Apriori Dan K-Means Dalam Analisis Pola Pembelian Untuk Meningkatkan Strategi Pemasaran. Jurnal Ilmiah penelitian dan pembelajaran informatika. 10(1), 409–423. DOI:10.29100/Jipi.V10i1.5768
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Penerapan Metode Asosiasi Menggunakan Algoritma Apriori pada Penjualan Produk Tenun
Pages: 1331-1339
Copyright (c) 2026 Muhammad Rijalul Abthol, Gentur Wahyu Nyipto Wibowo, Nadia Annisa Maori
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
