Perancangan sistem analisis data penjualan untuk mendukung pengambilan keputusan pada CV. Harapan Raya menggunakan algoritma apriori

Elvia, Elvia (2021) Perancangan sistem analisis data penjualan untuk mendukung pengambilan keputusan pada CV. Harapan Raya menggunakan algoritma apriori. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

CV. Harapan Raya merupakan salah satu perusahaan yang bergerak di bidang distributor bahan bangunan dengan bahan utama besi. Perusahaan melakukan pencatatan data transaksi penjualan produk yang dilakukan oleh pelanggan melalui software pengolah kata. Perusahaaan tentunya membutuhkan sebuah sistem analisis yang dapat digunakan dalam menunjang proses pengambilan keputusan. Data-data perusahaan yang tercatat setiap bulannya tentunya sangat banyak dan akan menjadi data yang tidak berguna apabila tidak diolah dan dianalisis dengan baik. Salah satu cara untuk melakukan analisis terhadap sekumpulan data menjadi pengetahuan adalah melalui teknik data mining. Algoritma apriori adalah salah satu algoritma data mining yang dapat digunakan pada penerapan market basket analysis (analisis keranjang belanja) untuk mencari aturan-aturan asosiasi yang memenuhi batas support dan confidence. Hasil analisis data penjualan CV. Harapan Raya dengan total data penjualan sebanyak 292 transaksi mendapatkan nilai minimum support tertinggi yaitu 5% dan menghasilkan rule berjumlah dua. Minimum confidence tertinggi yaitu 100% dan menghasilkan rule berjumlah tiga. Panjang itemset yang terbentuk yaitu 2-itemset dan 3-itemset/CV. Harapan Raya is one of the companies engaged in the distribution of building materials with iron as the main ingredient. The company records data on product sales transactions made by customers through word processing software. Companies certainly need an analysis system that can be used to support the decision-making process. The company's data that is recorded every month is certainly very large and will become useless data if it is not processed and analyzed properly. One way to analyze a set of data into knowledge is through data mining techniques. The apriori algorithm is one of the data mining algorithms that can be used in the application of market basket analysis (shopping basket analysis) to find association rules that meet support and confidence limits. The results of sales data analysis CV. Harapan Raya with a total sales data of 292 transactions got the highest minimum support value of 5% and produced 2 rules. The highest minimum confidence was 100% and produced three rules. The length of the itemset formed were 2-itemset and 3-itemset

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