IMPLEMENTASI DATA MINING MENGGUNAKAN
ALGORITMA APRIORI PADA TOKO MARINA MART
UNTUK MENENTUKAN TREN PENJUALAN
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Institusion
INSTITUT TEKNOLOGI DIRGANTARA ADISUTJIPTO
Author
HANIF FANDIKA ARGA SAGARA, RADEN
Subject
Q Science (General)
Datestamp
2024-04-01 02:55:54
Abstract :
The retail business is one of the business sectors that has been hit the hardest by the COVID-19 pandemic. Several retail companies suffered losses. One way to increase sales is to implement a promotional program. There are many types of promotions that can be offered, one of which is by applying sales trends such as product bundling or other promotions in stores. This demands innovation from seller in setting sales trends in this case is product bundling to ensure business continuity. The sales strategy is to determine the sales trend of the right kind of product bundling, which is expected to increase turnover and be able to anticipate the competition that occurs. One effort that can be done is to carry out data mining processes on sales transaction data. Therefore, this study aims to build a data mining system for the formation of itemset combinations by applying the Apriori Algorithm. The flow of making this system includes planning, data collection, system design, system implementation and testing. The system was tested using two tests, namely the manual calculation test and the suitability test of the results. In the manual calculation test, the calculation is carried out using the Algorithm equation, while the result conformity test is carried out by comparing the data that appears on the system with manual calculation data using Microsoft excel, in testing the suitability of the results, the system gets a percentage of conformity of 100%.
The retail business is one of the business sectors that has been hit the hardest by the COVID-19 pandemic. Several retail companies suffered losses. One way to increase sales is to implement a promotional program. There are many types of promotions that can be offered, one of which is by applying sales trends such as product bundling or other promotions in stores. This demands innovation from seller in setting sales trends in this case is product bundling to ensure business continuity. The sales strategy is to determine the sales trend of the right kind of product bundling, which is expected to increase turnover and be able to anticipate the competition that occurs. One effort that can be done is to carry out data mining processes on sales transaction data. Therefore, this study aims to build a data mining system for the formation of itemset combinations by applying the Apriori Algorithm. The flow of making this system includes planning, data collection, system design, system implementation and testing. The system was tested using two tests, namely the manual calculation test and the suitability test of the results. In the manual calculation test, the calculation is carried out using the Algorithm equation, while the result conformity test is carried out by comparing the data that appears on the system with manual calculation data using Microsoft excel, in testing the suitability of the results, the system gets a percentage of conformity of 100%.
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