Penerapan Data Mining Pada Transaksi Penjualan Selama Bulan Ramadhan Untuk Menentukan Market Basket Analysis Menggunakan Algoritma Eclat (Equivalence Class Transformation)

Bramantyo, Adam Putra (2024) Penerapan Data Mining Pada Transaksi Penjualan Selama Bulan Ramadhan Untuk Menentukan Market Basket Analysis Menggunakan Algoritma Eclat (Equivalence Class Transformation). Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

The increasing number and proliferation of various shops for daily necessities in Indonesia has made business competition in this field even tighter. In almost every area there are shops for daily necessities, ranging from grocery stores, Madura stalls, minimarkets, to supermarkets. The large and intense competition in this business encourages the need for innovation and new strategies in order to survive and grow to become more developed. Increasing sales at various major annual events could be an option. To develop this MSME business, one of them is during the month of Ramadan. In these conditions, techniques are needed that can process data into useful information. One example of a technique that can be used is data mining which can function to find out what products are often purchased together. The analysis method used is a data mining technique with the Eclat algorithm, where this algorithm functions to determine the data sets that appear most frequently. The results of the research showed that there were 6 association rules that met the minimum support and confidence values, with the highest support and confidence values namely Sariwangi30 with EnervonCMtv4 with a Support value of 0.82% and Confidence 48% as a strong rule. These results can become new knowledge and product evaluations, which are expected to increase sales in stores in the month of Ramadan and can grow more rapidly.

Item Type:

Thesis (Undergraduate)

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