Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)

Application of Clustering Algorithm and Spatial Analysis for Industrial Optimization

Authors
Achmad Fauzan, Ginanjar Wiro Sasmito, Sekti Kartika Dini
Corresponding Author
Achmad Fauzan
Available Online 11 October 2020.
DOI
https://doi.org/10.2991/assehr.k.201010.024How to use a DOI?
Keywords
K-Means Clustering, Silhouette, Spatial Autocorrelation
Abstract

Technological advances and increasingly diverse human needs, making one of the challenges for policymakers in planning future design. One of them is the determination of policies in industrial equality. The even distribution of the industry itself is in line with the objectives of the country’s first field of Development Goals, namely, to end poverty in all forms. Based on this, this study aims to analyze industrial clusterings and continue with spatial analysis of each region and its visualization with the R programming language. The case study of this uses data from the Department of Industry and Trade in Tegal City; this is because Tegal City is one of the tourist destinations and industrial centers that are developing, especially in the field of food or drink in Central Java Province. K-Means cluster method is used in clustering, as well as spatial autocorrelation, to determine whether there is influence from each region. Based on the research results, obtained two optimal groups in the food industry grouping. The determination of the optimal number of groups is based on the Within-Cluster-Sum of Squared Errors (WSS) and Silhouette evaluation methods. The two food industry producer groups formed have the characteristics of the first group consisting of twenty-three food industry producers with average investment value and production value relatively lower compared to the second group consisting of two food industry producers. Moran’s index is used to check spatial autocorrelation where the results obtained will be visualized in the form of a geographic information system which is expected to facilitate future policy makers.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
11 October 2020
ISBN
978-94-6239-168-0
ISSN
2352-5398
DOI
https://doi.org/10.2991/assehr.k.201010.024How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Achmad Fauzan
AU  - Ginanjar Wiro Sasmito
AU  - Sekti Kartika Dini
PY  - 2020
DA  - 2020/10/11
TI  - Application of Clustering Algorithm and Spatial Analysis for Industrial Optimization
BT  - Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)
PB  - Atlantis Press
SP  - 165
EP  - 171
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201010.024
DO  - https://doi.org/10.2991/assehr.k.201010.024
ID  - Fauzan2020
ER  -