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All Journal JURSIMA (Jurnal Sistem Informasi dan Manajemen) JURSIMA Jurnal Sistem Informasi dan Manajemen
Dicky Miftakhul Rizki
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science Social Sciences

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ANALISA PEMBELIAN SEPEDA MENGGUNAKAN ALGORITMA APRIORI PADA TOKO SEPEDA BRADEN BIKE Dicky Miftakhul Rizki; Odi Nurdiawan; Saeful Anwar
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 3 (2022): Jursima Vol.10 No.3 Desember 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.465

Abstract

The store is a place for trading activities that provide all daily necessities with a special type of goods. Braden Bike Shop is a store that sells a variety of bicycle products and accessories, but the data collection of sales transactions for goods that have been sold is usually written on sheets of paper and collected paper that has been sold and rewrites items that have been sold manually to new paper to record sales reports every month with the current system, The purpose of this study is to find the rules of the combination of items by looking at the relationships of two or more variables, The method used is the A priori Algorithm Method in data mining techniques, namely the association rule or association rule used using a minimum support of 10% and a minimum of confidence of 50%, The results obtained are 12 rules 2 itemsets and 2 rules 3 itemssets following sales for 1 year using a priori algorithms, namely categories Aviator_GN, Exotic_GN, Interbike_GN, Fastron_GN, Polygon_GN, Seat Covers, Anti-Slip_AS Grips and Bell_AS. Results obtained based on manual calculations and using Rapid Miner software have results above the minimum support of 10%and confidence of 50%.
ANALISA PEMBELIAN SEPEDA MENGGUNAKAN ALGORITMA APRIORI PADA TOKO SEPEDA BRADEN BIKE Dicky Miftakhul Rizki; Odi Nurdiawan; Saeful Anwar
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 3: Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.465

Abstract

The store is a place for trading activities that provide all daily necessities with a special type of goods. Braden Bike Shop is a store that sells a variety of bicycle products and accessories, but the data collection of sales transactions for goods that have been sold is usually written on sheets of paper and collected paper that has been sold and rewrites items that have been sold manually to new paper to record sales reports every month with the current system, The purpose of this study is to find the rules of the combination of items by looking at the relationships of two or more variables, The method used is the A priori Algorithm Method in data mining techniques, namely the association rule or association rule used using a minimum support of 10% and a minimum of confidence of 50%, The results obtained are 12 rules 2 itemsets and 2 rules 3 itemssets following sales for 1 year using a priori algorithms, namely categories Aviator_GN, Exotic_GN, Interbike_GN, Fastron_GN, Polygon_GN, Seat Covers, Anti-Slip_AS Grips and Bell_AS. Results obtained based on manual calculations and using Rapid Miner software have results above the minimum support of 10%and confidence of 50%.
ANALISA PEMBELIAN SEPEDA MENGGUNAKAN ALGORITMA APRIORI PADA TOKO SEPEDA BRADEN BIKE Dicky Miftakhul Rizki; Odi Nurdiawan; Saeful Anwar
JURSIMA Vol 10 No 3: Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.465

Abstract

Toko merupakan tempat untuk kegiatan perdagangan yang menyediakan segala kebutuhan sehari-hari dengan jenis barang khusus. Toko Sepeda Braden Bike merupakan toko yang menjual berbagai macam produk Sepeda dan aksesoris, namun pendataan transaksi penjualan barang yang sudah dijual biasanya ditulis dalam lembaran kertas dan dikumpulkan kertas yang sudah terjual dan menulis ulang barang yang sudah dijual secara manual ke kertas baru untuk mencatat laporan penjualan setiap bulan dengan sistem yang berjalan saat ini, Tujuan penelitian ini untuk menemukan aturan dari kombinasi item dengan melihat antar hubungan dua variabel atau lebih, Metode yang digunakan adalah Metode Algoritma Apriori dalam Teknik data mining yaitu association rule atau aturan asosisasi yang digunakan dengan menggunakan minimum support 10% dan minimum confidence 50%, Adapun hasil yang diperoleh 12 aturan 2 itemset dan 2 aturan 3 itemset berikut penjualan selama 1 tahun dengan menggunakan algoritma apriori yaitu kategori Aviator_GN, Exotic_GN, Interbike_GN, Fastron_GN, Polygon_GN, Cover Jok, Grip Anti Slip_AS dan Bell_AS. Hasil didapatkan berdasarkan perhitungan manual dan menggunakan software Rapid Miner memiliki hasil diatas minimum support 10%dan confidence 50%.
Co-Authors Odi Nurdiawan Saeful Anwar