Jurnal Teknologi Industri Pertanian
Vol. 32 No. 2 (2022): Jurnal Teknologi Industri Pertanian

PENERAPAN SISTEM INTELIJENSIA BISNIS DAN K-MEANS CLUSTERING UNTUK MEMANTAU PRODUKSI TANAMAN OBAT

Miwan Kurniawan Hidayat (Prodi Teknik Industri Universitas Bina Sarana Informatika, Magister Teknik Industri Universitas Trisakti)
Rina Fitriana (Magister Teknik Industri Universitas Trisakti)



Article Info

Publish Date
22 Sep 2022

Abstract

Indonesia has biodiversity including medicinal plants. The medicinal plant business can be a profitable business prospect because it has high export opportunities. Based on the benefits obtained, the production of medicinal plants needs to be considered by monitoring and evaluating production results to increase productivity, especially for areas with low production levels. The Department of Food Crops and Horticulture of West Java Province through the website https://opendata.jabarprov.go.id has provided production datasets for each type of medicinal plant, but it has not yet become a dataset with various types of medicinal plants. The purpose of this study was to design an integrated data storage model in the form of a data warehouse, grouping medicinal plant production areas using data mining and designing data visualization in business intelligence systems. Business intelligence system design was carried out through several stages, namely system requirements analysis, identification of data and information needs, data warehouse design, data warehouse filling, data mining processes, data visualization, and system performance evaluation. The results of the research were the application of a data warehouse using a dimensional model with a star schema; a grouping of production areas using the KMeans algorithm with optimal k=3 and the number of elements produced in each cluster is 24 regions in cluster 0, 1 region in cluster 1, and 2 regions in cluster 2; a business intelligence system is implemented using a dashboard to show information on the amount of production and display the results of grouping potential areas for producing medicinal plants.Keywords: business intelligence, data warehouse, dimensional models, visualization, medicinal plants

Copyrights © 2022






Journal Info

Abbrev

jurnaltin

Publisher

Subject

Agriculture, Biological Sciences & Forestry Engineering Industrial & Manufacturing Engineering

Description

The development of science and technology in agriculture, has been instrumental in increasing the production of various agricultural commodities. But climate change is also uncertain world led to decreased agricultural productivity. World energy crisis resulted in higher prices of agricultural ...