IMPLEMENTASI ALGORITMA APRIORI PADA PENENTUAN KOMBINASI MENU UMKM TOCIN CORNER SUKOHARJO

Fadel Thoriq Nur Muhammad, Retno Tri Vulandari, Paulus Harsadi

Abstract


The thesis report for the April algorithm application of the menu sales in the TOCIN CORNER sukoharjo bar has been conducted on July 1, 2019-31, 2019. In view of the condition of sales in the TOCIN CORNER, there is still a problem in menu and raw materials stocks. Among other things, there is still a steady buildup of preordained menu supplies. This leads to the possibility of consumer disappointment even turning to other wedgies, as the availability of preferred menu has been exhausted. The objective of this thesis is to build a system that can be useful in locating and compiling the appropriate combination of the menu by using the apricot method on the menu sales in the TOCIN CORNER in order to increase the sales of the menu. The research methods used in this study include data collection methods and data analysis methods. Data collection methods include observation, interviews and library studies. While the data analysis method is done by means of data obtained will be described according to actual circumstances, researched, studied and processed as a material to create the program. In this study a design model system development life cycle (SDLC). The system development life cycle isa gradual approach to analyzing and building the design system using a specific cycle of user activities as for the SDLC stages are analysis, design, construction/coding, implementation, and testing. The results of the data analysis on the implementation of the menu selling system in TOCIN CORNER are using apricot method with system design usecase, output input design, database design, technology design, instructions to run the program. The implementation of the menu of TOCIN CORNER USES the apriestary method that has been created has transaction data facilities, daily data input, accounting processes, data reports. From this data the launch will produce results reports.

Keywords


Data Mining, Association Rule, Aprior Algorithm, Confidence.

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DOI: http://dx.doi.org/10.30646/tikomsin.v10i2.644

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