Construction of business intelligence in dadih product affective design

International Conference on Green Agro-industry and Bioeconomy

农业科学;工业技术（总论）;经济学

Delfitriani^1 ; Djatna, T.^2

Study Program of Agro-industrial Technology, Bogor Djuanda University, Bogor, Indonesia^1

Department of Agro-industrial Technology, Bogor Agricultural University, Bogor, Indonesia^2

关键词: Analysis techniques;    Association rules mining;    Business decisions;    Commercialisation;    Consumer purchase;    Market expansions;    Naive Bayes classifiers;    Strategy formulations;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/230/1/012053/pdf
DOI  :  10.1088/1755-1315/230/1/012053

来源: IOP

【 摘 要 】

Business intelligence is a primary system for almost all conditions that involve business decision making and strategy formulation. Manufacturers usually want to collect more information about the product before being traded. They consider the opinions of consumers in making decisions on consumer purchases. Among the entire spectrum of consumer needs, functional and affective needs have been recognised as of primary importance. In this study, we focused on the affective design of the dadih product. Dadih is one of the typical fermented milk products from West Sumatera and potentially develops as the functional food. However, the obstacle of the dadih product today is not yet in the modern mass commercialisation way due to less attractive packaging that makes it difficult for marketing and market expansion. The main challenges are to understand consumers' affective needs accurately and then design a dadih product by consumers' needs. The objectives of this research are to identify the construction of business intelligence architecture, to identify consumers' affective needs for dadih products and to map the need for the affective design of dadih products based on consumer opinion. The architecture of business intelligence was compiled from data sources, data warehousing, analytical techniques, subject analysis, and decision making. The analysis techniques used to map consumer affective needs were Naive Bayes Classifier and Association Rules Mining. The results of the analysis shown the orientation of consumer opinion and the rules of affective design of dadih products.