ANDRIYANI, FITRI (2020) IMPLEMENTASI DATA MINING PENJUALAN PRODUK MINUMAN KEMASAN DENGAN ALGORITMA APRIORI (STUDI KASUS: TOKO RENJI SEMARANG). Undergraduate thesis, Universitas Stikubank.
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Abstract
Toko Renji merupakan toko yang menjual produk minuman kemasan yang ada di Kota Semarang beralamat di Jalan Puspanjolo Selatan RT 7 RW 3, Bojong Salaman, Kota Semarang. Toko ini menjual berbagai macam merek produk minuman kemasan. Namun pemilik toko masih sering mengalami kesulitan dalam mengolah data transaksi penjualan dan mengalami kesulitan dalam mengolah ketersediaan barang, oleh karena itu penjualan tidak maksimal. Maka dari itu pihak Toko Renji membutuhkan informasi pola kombinasi produk minuman kemasan agar dapat memenuhi persediaan produk minuman yang saling berkaitan. Dengan adanya implementasi data mining menggunakan Algoritma Apriori pada Toko Renji dapat membantu pemilik toko dalam mengetahui pola kombinasi produk minuman yang saling berhubungan. Menganalisa transaksi penjualan tersebut dapat menggunakan teknik asosiasi tujuannya agar bisa melihat pola hubungan antar barang yang dibeli konsumen secara bersamaan. Proses ini menggunakan Software Rstudio dengan nilai minimum support 0,01 (1%) dan nilai confidence 0,5 (50%) aturan yang diperoleh dari nilai support dan confidence yaitu 14 aturan asosiasi. Aturan asosiasi tersebut menghasilkan nilai confidence tertinngi 100% pada pembelian Kopi Cup dan Vit 1500ml maka akan membeli Le Minerale 600ml secara bersamaan. Penerapan Algoritma Apriori pada data mining dengan aturan asosiasi dapat menemukan pola kombinasi itemset dari hasil penjualan produk minuman di Toko Renji, sehingga diperoleh informasi yang bermanfaat dalam meningkatkan penjualan dan dapat mengolah persediaan stok produk minuman dengan baik. Kedepannya dapat mengkombinasikan dengan algoritma lain untuk melihat perbandingan analisanya dan dikembangkan lebih luas lagi dalam bentuk aplikasi agar dapat dengan mudah mengaksesnya. Renji Shop is a shop that sells packaged beverage products in the city of Semarang located at Puspanjolo South of RT 7 RW 3, Bojong Salaman, Semarang City. This store sells a variety of brands of bottled beverage products. But shop owners still often experience difficulties in processing sales transaction data and have difficulty in processing the availability of goods, therefore sales are not optimal. Therefore the Renji Shop requires information on the combination pattern of packaged beverage products in order to meet the supply of interconnected beverage products. With the implementation of data mining using the Apriori Algorithm in Renji Stores can help shop owners find out patterns of combinations of beverage products that are interconnected. Analyzing the sales transaction can use the association technique in order to be able to see the pattern of relationships between goods purchased by consumers simultaneously. This process uses Rstudio Software with a minimum support value of 0.01 (1%) and a confidence value of 0.5 (50%) rules obtained from the support and confidence value of 14 association rules. The association rules produce 100% highest confidence value on the purchase of 1500ml Coffee Cup and Vit, so you will buy 600ml Le Minerale simultaneously. The application of Apriori Algorithm to data mining with association rules can find patterns of itemset combinations from the sale of beverage products at Renji Stores, so that useful information is obtained in increasing sales and being able to process inventory stocks of beverage products well. In the future, it can combine with other algorithms to see the comparison of the analysis and be developed more broadly in the form of applications so that they can easily access them.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | NIM.16.01.53.0093 SKR.I.05.01.1917 |
| Uncontrolled Keywords: | Transaksi Penjualan, Data Mining, Algoritma Apriori Sales Transactions, Data Mining, Apriori Algorithms |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Faculty / Institution: | Fakultas Teknologi Informasi > Program Studi Teknik Informatika |
| Depositing User: | H Hayati |
| Date Deposited: | 14 Sep 2020 02:03 |
| Last Modified: | 14 Sep 2020 02:03 |
| URI: | https://eprints.unisbank.ac.id/id/eprint/7088 |
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