CAR PURCHASE RECOMMENDATION SYSTEM USING C.45 ALGORITHM

Kristianto, Wahyu Jenius (2019) CAR PURCHASE RECOMMENDATION SYSTEM USING C.45 ALGORITHM. Other thesis, UNIKA SOEGIJAPRANATA SEMARANG.

[img] Text (COVER)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf COVER.pdf

Download (514kB)
[img] Text (BAB I)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf BAB I.pdf

Download (69kB)
[img] Text (BAB II)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf BAB II.pdf
Restricted to Registered users only

Download (78kB)
[img] Text (BAB III)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf BAB III.pdf

Download (73kB)
[img] Text (BAB IV)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf BAB IV.pdf

Download (178kB)
[img] Text (BAB V)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf BAB V.pdf

Download (151kB)
[img] Text (BAB VI)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf BAB VI.pdf

Download (68kB)
[img] Text (DAFTAR PUSTAKA)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf DAPUS.pdf

Download (113kB)
[img] Text (LAMPIRAN)
14.K2.0011 WAHYU JENIUS KRISTIANTO (7.63)..pdf LAMP.pdf

Download (67kB)

Abstract

The main difficulty of this research is determining the best selling car. The number of categories / various types of cars sold every month makes it difficult to determine market desires. This makes it difficult for the company to make a stock that best suits the needs of the consumer / target market. C 4.5 algorithm is a calculation to predict the possibilities that occur. The category used comes from the owner of the company, with the contents of the categories as follows: Brand, Type, Model, Year, Color. With a customized category from the owner of the company, it can find out the consumer's interest in a product more specifically. This research produces various kinds of predictions from the calculation of C 4.5, which will be compared with the original sales data for a selected month. And predictions are made using "Tree", making it easier to see the order of decisions taken by the algorithm. Last is testing which contains the results of a comparison between the original data and the results of the algorithm prediction. Keyword: C 4. 5 Algorithm, Showroom, Prediction, Tree, Data Mining

Item Type: Thesis (Other)
Subjects: 000 Computer Science, Information and General Works > 005 Computer programming, programs & data > Information Systems
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: Mr Lucius Oentoeng
Date Deposited: 03 Dec 2019 08:45
Last Modified: 03 Dec 2019 08:45
URI: http://repository.unika.ac.id/id/eprint/20553

Actions (login required)

View Item View Item