PENERAPAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) UNTUK KLASIFIKASI PENGADUAN MASYARAKAT PADA DPR RI
Total View This Week0
Total View This Week0
Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Shodikin, Nanda Irvan
Kuswardani, Dwina
Siregar, Riki Ruli Affandi
Kuswardani, Dwina
Siregar, Riki Ruli Affandi
Subject
Teknik Informatika
Datestamp
2022-09-27 04:11:05
Abstract :
The House of Representatives of the Republic of Indonesia (DPR RI) is one of the high-state institutions in the Indonesian constitutional system which is a representative institution. One of the duties of DPR RI is to absorb, compile, accommodate and follow up on people's aspirations and complaints. Currently, classification process of community complaints is often misgrouping according to the problems field due to the number of complaints data and limited working time and the number of officers, So that community complaints are not up to the related commissions which resulted in the public not getting replies and community complaints can?t be follow up. Support Vector Machine (SVM) algorithm can be used to classify complaint data based on problem field with the similarity text approach using cosine similarity. The results of this reseach conducted the first test with a total of 20 test data, obtained an accuracy value = 65% and conducted a second test with the total test data of 120, obtaining an accuracy value = 55.8%.
The House of Representatives of the Republic of Indonesia (DPR RI) is one of the high-state institutions in the Indonesian constitutional system which is a representative institution. One of the duties of DPR RI is to absorb, compile, accommodate and follow up on people's aspirations and complaints. Currently, classification process of community complaints is often misgrouping according to the problems field due to the number of complaints data and limited working time and the number of officers, So that community complaints are not up to the related commissions which resulted in the public not getting replies and community complaints can?t be follow up. Support Vector Machine (SVM) algorithm can be used to classify complaint data based on problem field with the similarity text approach using cosine similarity. The results of this reseach conducted the first test with a total of 20 test data, obtained an accuracy value = 65% and conducted a second test with the total test data of 120, obtaining an accuracy value = 55.8%.
Download
book
BibTex
Latex, Jabref
cloud_download
Original Resource
url resource Institution
