Analisa Data Mining Terhadap Penjualan Food Dengan Metode Apriori Pada Kopsyahira

Agung - Riyanto, Melan - Susanti

Abstract


Every company engaged in trade must have a strategy to improve service. Some of them regulate the arrangement of goods (display) or make the appearance of a store look attractive and make shopping easier so that consumers are willing to come back to shop. Many transactions every day but are still done manually. So there might be a lot of errors and inaccurate reports. The number of transactions is also only used as a document. It is not possible for many transaction data to be lost or tucked away. Collection of transaction data if left alone for months, then the data will only be meaningless data and will be a limiting factor in improving services. Purchases are often done simultaneously at one time, so there is a queue in the store. In Kopsyahira there were also several obstacles in terms of sales, especially food sales. In this study, researchers will use the Apriori algorithm, the author uses Tanagra's data mining software. The results of this study produce 2 final association rules if using a minimum support of 30% and Confidence of 66%.


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References


Badrul, M. (2016). Algoritma Asosiasi Dengan Algoritma Apriori Untuk Analisa Data Penjualan. Jurnal PILAR Nusa Mandiri, 12(2), 121–129.

Husin, A. I., & Mulyaningsih, F. (2015). Penerapan Metode Data Mining Analisis Terhadap Data Penjualan Pakaian Dengan Algoritma Apriori. Sniptek, 45–56.

Kurniawati, L., Kusuma, A. E., & Dewansyah, B. (2019). Implementasi Algoritma Apriori Untuk Menentukan Persediaan Spare Part Compressor. Journal of Computer Engineering System and Science, 4(1), 6–9. https://doi.org/10.24114/cess.v4i1.11303

Purnia, D. S., & Warnilah, A. I. (2017). Implementasi Data Mining Pada Penjualan Kacamata Menggunakan Algoritma Apriori. Indonesian Journal on Computer and Information Technology, 2(2), 31–39.

Suryabrata, S. (2014). Metodologi Penelitian. Jakarta: PT RajaGrafindo Persada.

Suyanto. (2017). Data Mining Untuk Klasifikasi dan Klasterisasi Data. Bandung: Informatika Bandung.




DOI: https://doi.org/10.31294/bi.v8i1.8148

DOI (PDF): https://doi.org/10.31294/bi.v8i1.8148.g4135

ISSN2338-9761 (media online), 2338-8145 (media cetak)

Dipublikasikan oleh LPPM Universitas Bina Sarana Informatika

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