PENERAPAN DATA MINING MENGGUNAKAN ALGORITMA APRIORI DAN TIME SERIES UNTUK MENGETAHUI POLA PEMBELIAN KONSUMEN TERHADAP DATA TRANSAKSI PENJUALAN (STUDI KASUS TOKO BUSANA LEVISYA)

Ambar Arum Juliyanti, NIM.:16650052 (2020) PENERAPAN DATA MINING MENGGUNAKAN ALGORITMA APRIORI DAN TIME SERIES UNTUK MENGETAHUI POLA PEMBELIAN KONSUMEN TERHADAP DATA TRANSAKSI PENJUALAN (STUDI KASUS TOKO BUSANA LEVISYA). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Levisya Fashion Store is a clothing store that provides a variety of clothing needs such as dresses, robes, bags, pants, skirts, which are very complete. This store uses the cashier system in daily registration. In a day, sales transaction data in this store can reach dozens of buyers, so that resulting in large and useless data piles. Therefore, in this research, the researcher will carry out data mining techniques to manage sales transaction data from February to August 2019. Transaction data will be processed first and grouped into 15 groups. The algorithm used is apriori and time series algorithms with the Python programming language. The algorithms is suitable to be applied in this study because it’s to can identify consumer purchase patterns and to know demand for goods, so that the store owner can make a decision making policy according to the results of data processing. This research has succeeded in implementing data mining techniques with apriori and time series algorithms using the Python programming language. From the results of the analysis, it is known that the best-selling rule with the highest support is 15,398 % (Shirt,Robe,Pants), while the highest confidence is 96,004%, which is the rule (Plisket,Shirt=>Pants). The results of the time series algorithm are known to predict the demand is robes 130, accessories 110, pants 101, shirts 53, tops 47, and skirts 27. The results of each algorithm are analyzed and interpreted into information for businesses in improving their business strategies.

Item Type: Thesis (Skripsi)
Additional Information: Pembimbing: Rahmat Hidayat, S.Kom.,M.Cs
Uncontrolled Keywords: pencatatan; algoritma apriori; python; data time series
Subjects: Tehnik Informatika
Sains
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika (S1)
Depositing User: Muchti Nurhidaya edt
Date Deposited: 19 Apr 2022 11:15
Last Modified: 19 Apr 2022 11:15
URI: http://digilib.uin-suka.ac.id/id/eprint/50295

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