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Analisis dan Penerapan Algoritma Apriori Terhadap Penempatan Barang Pada Minimarket Surya Jambi
ANALYSIS AND APPLICATION OF APRIORI ALGORITHM ON PLACEMENT OF GOODS IN THE SURYA JAMBI MINI MARKET
Undergraduate Theses from gdlhub / 2019-05-16 15:30:28By : Muhammad Zuhdi, STIKOM Dinamika Bangsa Jambi
Created : 2019-05-16, with 7 files
Keyword : Data Mining, Asosiasi, Algoritma Apriori, Penempatan Barang
Minimarket Surya Jambi merupakan sebuah minimarket yang menjual berbagai macam makanan pokok atau sembako dan jajanan. Setiap harinya Minimarket Surya memiliki banyak transaksi penjualan, sehingga menjadi kendala bagi pemilik dalam mengelola data transaksi penjualan tersebut. Oleh karena itu, penulis melakukan analisis data mining pada data transaksi tersebut agar menjadi informasi yang sangat berharga bagi pemilik. Penulis menggunakan data transaksi bulan Oktober, November dan Desember 2018 sebanyak 750 data yang kemudian disajikan ke dalam format arff. Dalam melakukan analisis penulis menggunakan alat bantu Tools WEKA dan RapidMiner. Metode yang digunakan adalah Asosiasi Algoritma Apriori dengan 38 attribut. Analisis tersebut menghasilkan 6 Rule yaitu jika membeli tepung maka membeli minyak sayur dengan nilai confidence 58%, jika membeli roti maka membeli mie dengan nilai confidence 57%, jika membeli sabun maka membeli mie dengan nilai confidence 56%, jika membeli tepung maka membeli gula dengan nilai confidence 54%, jika membeli bumbu maka membeli minyak sayur dengan nilai confidence 53%, dan jika membeli roti maka membeli susu dengan nilai confidence 50%. Rule tersebut dihasilkan dari nilai support tertinggi sebesar 0,08 dan nilai confidence tertinggi sebesar 0,58.
Description Alternative :Surya Jambi Minimarket is a minimarket that sells various kinds of staple foods or groceries and snacks. Every day Minimarket Surya has many sales transactions, so that it becomes an obstacle for the owner in managing the sales transaction data. Therefore, the author analyzes data mining on the transaction data so that it becomes very valuable information for the owner. The author uses transaction data in October, November and December 2018 as many as 750 data which are then presented in arff format. In analyzing the author using WEKA and RapidMiner Tools. The method used is the Association of Priori Algorithms with 38 attributes. The analysis produced 6 Rule, namely if buying flour then buying vegetable oil with a value of 58% confidence, if buying bread then buying noodles with confidence value 57%, if buying soap then buying noodles with confidence value 56%, if buying flour then buy sugar with confidence value 54%, if you buy seasoning, buy vegetable oil with 53% confidence value, and if you buy bread, buy milk with 50% confidence value. The rule is generated from the highest support value of 0.08 and the highest confidence value of 0.58.
| Property | Value |
|---|---|
| Publisher ID | gdlhub |
| Organization | STIKOM Dinamika Bangsa Jambi |
| Contact Name | Herti Yani, S.Kom |
| Address | Jln. Jenderal Sudirman |
| City | Jambi |
| Region | Jambi |
| Country | Indonesia |
| Phone | 0741-35095 |
| Fax | 0741-35093 |
| Administrator E-mail | elibrarystikom@gmail.com |
| CKO E-mail | elibrarystikom@gmail.com |
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- Pembimbing : Pareza Alam Jusia, S.Kom, M.Kom dan Kurniabudi, S.Kom, M.Kom, Editor: Calvin
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