Penerapan data mining untuk prediksi pembelian barang pada distributor lampu menggunakan metode apriori (studi kasus : PT. Cahaya Prima Lestari Abadi)

Venessa Tanlim, Anastasia (2020) Penerapan data mining untuk prediksi pembelian barang pada distributor lampu menggunakan metode apriori (studi kasus : PT. Cahaya Prima Lestari Abadi). Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Apriori merupakan algoritma yang banyak digunakan untuk menentukan pola hubungan antar produk yang sering dibeli bersamaan dalam suatu toko. Algoritma Apriori ini akan sesuai diterapkan dalam bidang penentuan strategi ataupun promosi. PT. Cahaya Prima Lestari Abadi adalah salah satu Perusahaan Distributor Lampu Philips di kota Medan. Salah satu masalah dari perusahaan adalah ketidakseimbangan stok di gudang. Sehingga tujuan dari penelitian ini adalah untuk mendapatkan prediksi pembelian produk dari supplier untuk menjaga keseimbangan stok dengan produk yang terjual ke konsumen. Objek dalam penelitian ini yaitu penerapan algoritma apriori. Data penelitian ini berupa data transaksi penjualan di PT. CPLA. Analisis data menggunakan Software RapidMiner dengan menentukan nilai support dan confidence. Hasil analisis menunjukkan terdapat 22 aturan asosiasi dengan minimum support 20% dan minimum confidence 50% dari informasi ini diharapkan dapat membantu pihak perusahaan dalam menyusun strategi pembelian produk dari supplier sesuai dengan itemset yang terbentuk./Apriori is an algorithm that is widely used to determine the pattern of relationships between products that are often bought together in a store. This Apriori algorithm will be suitable to be applied in the field of determining strategy or promotion. PT. Cahaya Prima Lestari Abadi is one of the Philips Lighting Distributor Companies in Medan. One of the problem of the company is the imbalance of stock in the warehouse. So the purpose of this research is to obtain product purchase predictions from suppliers to maintain stock balance with product solds to customers. The object of this research is the application of apriori algorithm. This research data is in the form of sales transaction data at PT. CPLA. Data analysis using RapidMiner Software by determining the valure of support and confidence. The analysis shows that there are 22 Association Rules with a minimum support 20% and a minimum confidence 50%. This information is excpected to help the company in developing a product purchasing strategy from the supplier.

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