Ibrahim, Arraafi' (2019) Analisis Simulasi Penjualan Barang dengan Menggunakan Algoritma Apriori pada Mini Market Kirana Berbasis Web. Tugas Akhir thesis, University of Technology Yogyakarta.
|
Text
Naskah Publikasi-Arraafi' Rasyiid Ibrahim-5130411489.pdf Download (822kB) | Preview |
Abstract
Data mining is a new correlation, pattern and trend by sorting through large amounts of data stored in the repository, using patterns of technology recognition and statistical and mathematical techniques. Data mining needs to be done if there is useful data from database storage in the form of science. This research analyzes data using apriori data mining algorithm. The system that was built was shown to fulfill the determination of the purchase pattern of goods at the Kirana mart, to determine unexpected relationships and to summarize data with new methods or methods that are understandable and useful to data owners. The required data are taken from sales transaction data for a certain period and processed so as to produce frequent items, then 2 itemset is determined by giving a limit on the value of support that will affect the accuracy of the system in determining the pattern of interrelationship between goods. This system was built based on user needs obtained through interview methods and field studies. The system development methodology used is the waterfall method which consists of analysis, design, implementation, testing, and implementation. The test results with a priori algorithms and systems that are built show the results that have met the needs in determining the pattern of purchasing goods based on the tendency of purchasing goods by customers. Compared to the current system, the performance is shown in the effectiveness of information from the system about determining the pattern of purchasing goods. From this information it can be used in considering the types of goods to be sold with more quantities in the following month The results of determining the pattern can also be used for the availability of goods and the layout of the goods to make it easier to know the existence of goods seen from the 2 itemset items Keywords: data mining, association rules, apriori algorithm.
Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
---|---|
Subjects: | T Technology > T Technology (General) |
Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
Depositing User: | Kaprodi S1 Informatika UTY |
Date Deposited: | 05 Apr 2019 06:57 |
Last Modified: | 05 Apr 2019 06:57 |
URI: | http://eprints.uty.ac.id/id/eprint/2702 |
Actions (login required)
View Item |