Implementasi Data Mining Untuk Mengetahui Pola Pembelian Pelanggan Pada Produk Vin’s Cafe Dengan Algoritma Apriori Dan Pengujian Kualitas Melalui Metode ISO 9126
IF 0.9 3区 数学Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
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引用次数: 0
Abstract
Vin's Cafe is a bistro that sells food and drinks whose customers are generally children. The presence of deals consistently at Vin's Bistro, makes the information exchange deals continue to grow and makes the information capacity increase. The motivation behind this review is to decide on an example of a client's purchase based on the consequences of handling the inferred calculations and to test and implement the side effects of various information in the web structure. The technique used is the calculation of the deduction, the calculation of the deduction is a calculation that works by looking for affiliation rules without stopping among the advertised items. The affiliate rules in question are brought out through the system to work out help and trust relationships something. Affiliate rules should be attractive assuming the price of favor is more prominent than the base favor and the price of certainty is more important than the basic certainty. The result of this review is that Vin's Bistro can monitor the future offering system with 4 standards obtained from the exchange of information using inferred calculations and experimental results using ISO 9126 can be considered in the Generally very good Model with the side effect of the Usability variable being 85%, the result of Dependency angle 74.5%, Consequence of Ease of use section 88%, Consequence of Proficiency section 76%, Side effect of Practicality section of 75% and Side effect of Compactness section of 85%.
期刊介绍:
It is the aim of this journal to meet two main objectives: to cover the latest research on discrete random structures, and to present applications of such research to problems in combinatorics and computer science. The goal is to provide a natural home for a significant body of current research, and a useful forum for ideas on future studies in randomness.
Results concerning random graphs, hypergraphs, matroids, trees, mappings, permutations, matrices, sets and orders, as well as stochastic graph processes and networks are presented with particular emphasis on the use of probabilistic methods in combinatorics as developed by Paul Erdõs. The journal focuses on probabilistic algorithms, average case analysis of deterministic algorithms, and applications of probabilistic methods to cryptography, data structures, searching and sorting. The journal also devotes space to such areas of probability theory as percolation, random walks and combinatorial aspects of probability.