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Penentuan Pola Penjualan Menggunakan Algoritma Apriori

Authors: Sita Muharni; Sigit Andriyanto;

Penentuan Pola Penjualan Menggunakan Algoritma Apriori

Abstract

Dalam menghadapi era teknologi yang semakin berkembang dan berpengaruh sangat besar terhadap persaingan ekonomi, khususnya persaingan dalam dunia bisnis perdagangan barang, seperti minimarket atau toko, maka penggunaan teknik data mining dapat dijadikan acuan dalam mengelola data-data transaksi untuk dijadikan sebuah informasi. Multi Mart merupakan perusahaan yang bergerak di bidang makanan. Multi Mart menjual segala macam barang kebutuhan pokok, makanan, rokok dan lain-lain. Multi Mart memiliki beberapa permasalahan diantaranya adalah jumlah data yang semakin banyak sehingga data menumpuk. Akibat dari permasalahan tersebut, maka diterapkan teknik data mining dengan menggunakan algoritma apriori yang bertujuan untuk mengetahui hasil analisis pola penjualan toko dan menentukan pola asosiatif dari data transaksi yang sering dibeli secara bersamaan. Penelitian ini difokuskan pada penentuan pola penjualan dengan menggunakan metode apriori. Tahap penelitian yang dilakukan memiliki 5 tahapan: Pemilihan Data, Preprocessing Data, Transformasi, Data Mining, dan Evaluasi. Hasil dari penelitian ini menunjukkan bahwa terdapat beberapa barang yang dapat ditempatkan pada rak yang sama seperti telur, rokok (garam) dan coca-cola dengan nilai confidence sebesar 70.2% serta barang lainnya.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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