Mahsyari, Zumarsiyah (2018) Market Basket Analysis Menggunakan Algoritma Apriori, Fuzzy c-Covering, dan Association Rules Networks di K1 Mart ITS. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Memasuki masa transisi dari PTN BLU menjadi PTN BH, melalui KPRI ITS, ITS membuka minimarket yang mengusung nama K1 Mart ITS pada tahun 2015. Sebagai bisnis baru tentunya K1 Mart ITS membutuhkan strategi pemasaran yang tepat untuk dapat menarik banyak konsumen, salah satunya dengan memperhatikan pola barang yang dibeli oleh konsumen yang dapat diketahui dengan market basket analysis. Market basket analysis merupakan salah satu penggunaan teknik asosiasi yang digunakan untuk menemukan kelompok-kelompok barang yang terjadi secara bersamaan dalam suatu transaksi. Algoritma yang digunakan pada penelitian ini adalah Apriori, Fuzzy c-Covering, dan Association Rules Networks. Apriori menggunakan frequent itemsets dalam keseluruhan transaksi untuk menemukan pola pembelian konsumen tanpa memperhatikan hubungan tiap item dalam tiap transaksi, berbeda dengan algoritma Fuzzy c-Covering yang bekerja berdasarkan persepsi bahwa semakin banyak item yang dibeli dalam suatu transaksi, maka hubungan antar item dalam transaksi itu semakin lemah. Association Rules Networks (ARN) merupakan metode yang dapat memvisualisasikan hubungan antar item ke dalam bentuk network. Dari hasil ini, dapat dilihat hubungan langsung dan tidak langsung antar item. Penelitian ini menggunakan data transaksi K1 Mart ITS bulan Maret 2018. Hasil yang didapat adalah bahwa kelompok air mineral merupakan jenis barang yang paling berpengaruh dalam keseluruhan transaksi selama Maret 2018 berdasarkan ketiga metode tersebut menggunakan berbagai ukuran (support, confidence, dan lift untuk Apriori; support dan confidence untuk Fuzzy c-Covering; serta centrality dan page rank untuk ARN).
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Entering the transition period from PTN BLU to PTN BH, through KPRI ITS, ITS opened a minimarket that carries the name of K1 Mart ITS in 2015. As a new business, K1 Mart ITS needs the right marketing strategy to attract many consumers, goods purchased by consumers that can be known by market basketball analysis. Market basketball analysis is one of the uses of association techniques used to find groups of items that occur simultaneously in a transaction. Algorithm used in this research is Apriori, Fuzzy c-Covering, and Association Rules Networks. Apriori uses frequent itemsets in the overall transaction to find consumer purchase patterns regardless of the relationship of each item in each transaction, in contrast to the Fuzzy c-Covering algorithm that works based on the perception that the more items purchased in a transaction, the relationship between items in the transaction is increasingly weak. Association Rules Networks (ARN) is a method that can visualize the relationship between items into a network. From these results, we can see the direct and indirect relationships between items. This study used K1 Mart ITS transaction data in March 2018. The results obtained are that the mineral water group is the most influential type of goods in the overall transaction during March 2018 based on the three methods using various sizes (support, confidence, and elevator for Apriori; support and confidence for Fuzzy c-Covering, as well as centrality and page rank for ARN).
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 006.32 Mah m-1 2019 |
| Uncontrolled Keywords: | Apriori, Association Rule Networks, Fuzzy c-Covering, Market Basket Analysis |
| Subjects: | H Social Sciences > HF Commerce > HF5415.127 Market segmentation. Target marketing H Social Sciences > HF Commerce > HF5415.5 Customer services. Customer relations H Social Sciences > HF Commerce > HF5438.35 Data Processing (selling) Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) Q Science > QA Mathematics > QA76.9.D343 Data mining. Querying (Computer science) |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Zumarsiyah Mahsyari |
| Date Deposited: | 05 Jul 2021 09:09 |
| Last Modified: | 05 Jul 2021 09:09 |
| URI: | http://repository.its.ac.id/id/eprint/60778 |
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