Suroso Aji, Panji and , Dedi Gunawan, S.T., M.Sc (2015) Penerapan Algoritma Apriori Untuk Menentukan Frekuensi Item Set Sebagai Strategi Penjualan Di Toko Putra Manis Surakarta. Skripsi thesis, Universitas Muhammadiyah Surakarta.
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Abstract
Apriori algorithm is widely used to determine the pattern of relationship between products that are often bought in a store or supermarket. The a priori algorithm would be appropriate to be applied if there is some connection item you want analyzed. One thing that can be applied is in the field of promotion and marketing strategy determination. The aim in this research there are three, namely: (1) want to know the implementation of Data Mining on the sales transaction database of items of goods for the household. (2) wanted to know the implementation of Apriori Algorithm in determining high frequency items are set to predict the inventory in the future. The object of this research is the application of a priori algorithm. Data of this research is in the form of sales receipts obtained from Surakarta Sweet Son store in April and May, and in July and August 2015. The data was collected using interviews and documentation. Data analysis using RapidMiner program Studio 6.4. The conclusion of this study are: (1) Data Mining can be implemented by using a data base selling household goods, as you may find the tendency of pattern combinations of item sets that can be used as valuable information in the decision to prepare a stock of goods what is necessary then. (2) Application of Apriori algorithm in data mining techniques can be more efficient and be able to accelerate the process of forming a pattern tendency combination of items set household results is to support and supreme confidence on the items set glass - plate.
Item Type: | Karya ilmiah (Skripsi) |
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Uncontrolled Keywords: | Algorithm Apriori, Marketing Strategy |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Fakultas Ilmu Komunikasi dan Informatika > Teknik Informatika |
Depositing User: | Unnamed user with username l200080137 |
Date Deposited: | 02 Nov 2015 06:00 |
Last Modified: | 13 Oct 2021 04:49 |
URI: | http://eprints.ums.ac.id/id/eprint/38651 |
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