Implementasi Metode CHAID (Chi-Squared Automatic Interaction Detection) pada Segmentasi Trend Penjualan Minuman Ringan di Indonesia
Author(s) -
Via Sulviana,
Aji Hamim Wigena,
Indahwati
Publication year - 2018
Publication title -
xplore journal of statistics
Language(s) - English
Resource type - Journals
eISSN - 2655-2744
pISSN - 2302-5751
DOI - 10.29244/xplore.v2i2.91
Subject(s) - chaid , physics , humanities , forestry , computer science , artificial intelligence , geography , art , decision tree
Currently some outlet sells their products by looking at sales trends over a period of time to continue developing their business and devising effective marketing strategies. CHAID (Chi-Squared Automatic Interaction Detection) method is one of the efficient non-parametric statistical methods to classify any aspects that can increase the sales of soft drinks. CHAID selects significant variables based on the Chi-Square test between categories of explanatory variables with response categories. The CHAID method is used if the response variable is nominal or ordinal. This research aims to classify characteristics that characterize diversity and determine the target market that is able to maximize profits on the sales trend of various types of soft drinks by using CHAID method. Results from CHAID are tree diagrams that divide categories of response variables by segments from explanatory variables packaged into more easily understood information. CHAID method produces 11 of 20 segments that affect the trend of soft drink sales spread across big cities of Indonesia. There are 4 independent variable from segment that form, there are city, type of outlet, source of buying and payment method which accuracy that form from segmentation are 71.4%.
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