Clustering Module in OLAP for Horticultural Crops using SpagoBI

3rd International Seminar On Sciences "Sciences On Precision And Sustainable Agriculture"

Putri, D.^1 ; Sitanggang, I.S.^1

Computer Science Department, Faculty of Mathematics and Natural Science, Bogor Agricultural University, Kampus IPB, Jalan Meranti Wing 20 level 5, West Java, Bogor, Indonesia^1

关键词: Clustering results;    Horticultural crops;    HTML pages;    Indonesia;    K-means;    Large datasets;    Medicinal plants;    Ornamental plants;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/58/1/012001/pdf
DOI  :  10.1088/1755-1315/58/1/012001

来源: IOP

【 摘 要 】

Horticultural crops data are organized by the Ministry of Agriculture, Republic of Indonesia. The data are presented annually in a tabular form and result a large data set. This situation makes users difficult to obtain summaries of horticultural crops data. This study aims to develop a clustering module in the SOLAP system for the distribution of horticultural crops in Indonesia and to visualize the results of clustering in a map using SpagoBI. The algorithm used for clustering is K-Means. Horticultural crops data include vegetables, ornamental plants, medicinal plants, and fruits from 2000 to 2013. The clustering module displays clustering results of horticultural crops in the form of text and table on SpagoBI. This module can also visualize the distribution of horticultural crops in the form of map on the HTML page. The application is expected to be useful for users in order to easily obtain summaries of the horticultural crops distribution data and its clusters. The summaries and clusters can be beneficial for the stakeholders to determine potential areas in Indonesia for horticultural crops.