ANALISIS SENTIMEN OPINI PUBLIK BERITA KEBAKARAN HUTAN MELALUI KOMPARASI ALGORITMA SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBOR BERBASIS PARTICLE SWARM OPTIMIZATION

Authors

  • Lilyani Asri Utami Sistem Informasi STMIK Nusa Mandiri

DOI:

https://doi.org/10.33480/pilar.v13i1.153

Keywords:

PARTICLE SWARM OPTIMIZATION, Data Mining, Support Vector Machine, K-Nearest Neighbor (K-NN), Sentiment analysis

Abstract

Sentiment analysis is a process to determine the content of text-based datasets which are positive or negative. At present, public opinion be an important resource in the decision of a person in finding a solution. Classification algorithms such as Support Vector Machine (SVM) and K-Nearest Neighbor (K-NN) is proposed by many researchers to be used in sentiment analysis for review opinion. The problem in this research is the selection of feature selection to improve accuracy values Support Vector Machine (SVM) and K-Nearest Neighbor (K-NN) and compare the highest accuracy for sentiment analysis review public opinion about the news of forest fires. The comparison algorithms, SVM produces an accuracy of 80.83% and AUC 0.947, then compared with SVM based on PSO with an accuracy of 87.11% and AUC 0.922. The test result data for K-NN algorithm accuracy was 85.00% and the AUC 0.918, then compared for accuracy by k-NN-based PSO amounted to 73.06% and the AUC 0.500. The results of the testing of the PSO algorithm can improve the accuracy of SVM, but are not able to improve the accuracy of the algorithm K-NN. SVM algorithm based on PSO proven to provide solutions to the problems of classification review news opinion forest fires in order to more accurately and optimally.

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Author Biography

Lilyani Asri Utami, Sistem Informasi STMIK Nusa Mandiri

Lilyani Asri Utami, M.Kom.  Lahir di Bogor pada tanggal 15 November 1991, lulusan pendidikan Program S2 jurusan Ilmu Komputer – Pasca Sarjana STMIK Nusa Mandiri Jakarta tahun 2016. Bekerja sebagai instruktur di STMIK Nusa Mandiri Jakarta sejak tahun 2014. Sampai saat ini telah mengikuti beberapa kegiatan seminar nasional untuk menambah pengetahuan tentang menulis untuk menuangkan pemikiran dalam rangka melaksanakan Tri Dharma Perguruan Tinggi. Sebuah prociding berjudul “Sistem Informasi Administrasi Pasien Pada Klinik Keluarga Depok” pernah dimuat pada Konferensi Nasional Ilmu Pengetahuan dan Teknologi (KNIT) Nusa Mandiri pada tahun 2015. Semoga penelitian ini dapat memberikan manfaat bagi para pembacanya. 

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Published

2017-03-15

How to Cite

Utami, L. A. (2017). ANALISIS SENTIMEN OPINI PUBLIK BERITA KEBAKARAN HUTAN MELALUI KOMPARASI ALGORITMA SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBOR BERBASIS PARTICLE SWARM OPTIMIZATION. Jurnal Pilar Nusa Mandiri, 13(1), 103–112. https://doi.org/10.33480/pilar.v13i1.153

Issue

Vol. 13 No. 1 (2017): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2017

Section

Articles

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