Building of Informatics, Technology and Science
Vol 3 No 3 (2021): December 2021

Application of Support Vector Machine (SVM) Algorithm in Classification of Low-Cape Communities in Lampung Timur

Aldino, Ahmad Ari (Unknown)
Saputra, Alvin (Unknown)
Nurkholis, Andi (Unknown)
Setiawansyah, Setiawansyah (Unknown)



Article Info

Publish Date
31 Dec 2021

Abstract

Classification is a technique for grouping and categorizing specific standards as material for compiling information, making conclusions, or making decisions. This paper discusses data classification for underprivileged communities in Tanjung Inten, Purbolinggo, East Lampung using the Support Vector Machine (SVM) algorithm, then grouped into two label classes, namely the less fortunate and capable label classes. From the data that has been collected, 1154 data. The data goes through processing, scoring, labeling, and testing, producing two classes of results, namely less fortunate and capable. From the test data using the Support Vector Machine (SVM) method, the accuracy score is 97%, the precision score is 97%, the Recall score is 100%, and the F1-Score is 98%. This test resulted in a proportion of classification with the capable label is 87% and less fortunate label is 13%

Copyrights © 2021






Journal Info

Abbrev

bits

Publisher

Subject

Computer Science & IT

Description

Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. ...