Open AccessA digital business modelling for post-harvest loses and quality classification of potato agroindustry
Author(s) -
Ririni Regiana Dwi Satya,
Marimin Marimin,
Eriyatno,
Andes Ismayana
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/443/1/012059
Subject(s) - quality (philosophy) , postharvest , product (mathematics) , principal component analysis , process (computing) , computer science , agricultural engineering , mathematics , artificial intelligence , engineering , horticulture , philosophy , geometry , epistemology , biology , operating system
Factors that affect the quality of a product are color and shape. Color and shape factors are used as one of the most noticed parameters in choosing a product. At the level of potato farmers the process of separating the size of potatoes is done this causes the price of potatoes to be low. Separation based on the size of potatoes and broken potatoes was carried out at the farm level and carried out by direct observation. This separation process requires labor in large quantities, relatively large costs and a long enough time. The development of methods for separating potatoes based on quality class can be done with digital technology. The use of color, size and weight parameters in the selection of non-destructive potato quality is urgently needed to overcome the problem of manually separating potatoes for quality loses and weight loses. This study aims to create a business digital model to identify quality losses and weight losses and classification of quality of potatoes based on digital technology by using business process modelling notation combined with a principal component analysis approach. The results showed that the digital business modelling for postharvest losses and quality classification.