Analysis of Sentiment of Moving a National Capital with Feature Selection Naive Bayes Algorithm and Support Vector Machine
Analisis Sentimen Pemindahan Ibu Kota Negara dengan Feature Selection Algoritma Naive Bayes dan Support Vector Machine
Abstract
The decision to move Indonesia's capital city to East Kalimantan received mixed responses on social media. When the poverty rate is still high and the country's finances are difficult to be a factor in disapproval of the relocation of the national capital. Twitter as one of the popular social media, is used by the public to express these opinions. How is the tendency of community responses related to the move of the National Capital and how to do public opinion sentiment analysis related to the move of the National Capital with Feature Selection Naive Bayes Algorithm and Support Vector Machine to get the highest accuracy value is the goal in this study. Sentiment analysis data will take from public opinion using Indonesian from Twitter social media tweets in a crawling manner. Search words used are #IbuKotaBaru and #PindahIbuKota. The stages of the research consisted of collecting data through social media Twitter, polarity, preprocessing consisting of the process of transform case, cleansing, tokenizing, filtering and stemming. The use of feature selection to increase the accuracy value will then enter the ratio that has been determined to be used by data testing and training. The next step is the comparison between the Support Vector Machine and Naive Bayes methods to determine which method is more accurate. In the data period above it was found 24.26% positive sentiment 75.74% negative sentiment related to the move of a new capital city. Accuracy results using Rapid Miner software, the best accuracy value of Naive Bayes with Feature Selection is at a ratio of 9:1 with an accuracy of 88.24% while the best accuracy results Support Vector Machine with Feature Selection is at a ratio of 5:5 with an accuracy of 78.77%.
Downloads
References
Kusuma, Hendra (26 August 2019). "Resmi! Jokowi Putuskan Ibu Kota RI Pindah ke Kaltim". Diakses pada 25 April 2020 dari https://finance.detik.com/properti/d-4681152/resmi-jokowi-putuskan-ibu-kota-ri-pindah-ke-kaltim.
Pratomo, Harwanto Bimo (2019, Mei 5). 5 Pro dan Kontra Rencana Pemindahan Ibu Kota Presiden Jokowi. Diakses pada 18 Juni 2020, dari https://www.merdeka.com/uang/5-pro-dan-kontra-rencana-pemindahan-ibu-kota-presiden-jokowi.html.
Tyagi, P., & Tripathi, R. C., 2019, A Review towards the Sentiment Analysis Techniques for the Analysis of Twitter Data. International Conference on Advanced Computing and Software Engineering 2019, Sultanpur, February 8-9.
Pamungkas, D. S., Setiyanto, N. A., & Dolphina, E., 2015, Analisis Sentiment pada Sosial Media Twitter Menggunakan Naïve Bayes Classifier terhadap Kata Kunci “Kurikulum 2013”. Techno. Com, No.4, Vol.14, 299-314.
Kirilenko, A. P., Stepchenkova, S. O., Kim, H., & Li, X., 2018, Automated sentiment analysis in tourism: Comparison of approaches. Journal of Travel Research, No.8, Vol.57, 1012-1025.
Liu, Y., Huang, X., An, A., & Yu, X., 2007, ARSA: A SentimentAware Model for Predicting Sales Performance Using Blogs. In Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, New York.
Taboada, M., Brooke, J., Tofiloski, M., Voll, K. dan Stede, M. (2011). ‘Lexicon- based methods for sentiment analysis
Hidayat, A. N., 2015, Analisis Sentimen Terhadap Wacana Politik Pada Media Masa Online Menggunakan Algoritma Support Vector Machine Dan Naive Bayes. Jurnal Elektronik Sistem Informasi dan Komputer, No.1, Vol.1, 12-18.
Ahmad Saleh, 2015, "Klasifikasi Gejala Depresi Pada Manusia dengan Metode Naive Bayes Menggunakan Java", Penerbit Andi, Yogyakarta.
Fiarni, C., Maharani, H., & Pratama, R., 2016, Sentiment analysis system for Indonesia online retail shop review using hierarchy Naive Bayes technique. In 2016 4th international conference on information and communication Technology, Bandung, May 25-27.
Buntoro, G.A., 2017, Analisis Sentimen Calon Gubernur DKI Jakarta 2017 Di Twitter. INTEGER: Journal of Information Technology, No.1, Vol.2.
Anto Satriyo Nugroho, A. B. (2003). Support Vector Machine. Application of Support Vector Machine in Bioinformatics.
William S. Sanders, 2011. "Prediction of Cell Penetrating Peptides by Support Vector Machines", doi: 10.1371/journal.pcbi.1002101.
Indrayuni, Elly. 2016. Analisa Sentimen Review Hotel Menggunakan Algoritma Support Vector Machine Berbasis Particle Swarm Optimization, ISSN: 2338 – 8161.Pontianak : Jurnal Evolusi Volume 4 Nomor 2 – 2016.
Achyani, Yuni Eka. 2018, Penerapan Metode Particle Swarm Optimization Pada Optimasi Prediksi Pemasaran Langsung, Jurnal Informatika, Vol.5 No.1 April 2018, pp. 1~11
Pamungkas, D. S., Setiyanto, N. A., & Dolphina, E., 2015, Analisis Sentimen pada Sosial Media Twitter Menggunakan Naïve Bayes Classifier terhadap Kata Kunci “Kurikulum 2013”. Techno. Com, No.4, Vol.14, 299-314.
Priyono, F., Kanti, S., Dzulfiqar, I., Amirulloh, I., Alvi, A., & Rosiyadi, D., 2016, Analisis Sentimen Media Sosial Opini Ujian Nasional Berbasis Komputer menggunakan Metoda Naive Bayes. Journal of Electrical And Electronics Engineering, No.2, Vol.1.
Mihuandayani, M., Feriyanto, E., Syarham, S., & Kusrini, K., 2018, Opinion Mining pada Komentas Twitter E-KTP Menggunakan Naïve Bayes Classier. Semnasteknomedia Online, No.1, Vol.6, 1-2.
Anggelina, Shella Yuni (2020) Analisis Sentimen Dan Klasifikasi Respon Masyarakat Terhadap Pemindahan Ibu Kota Negara Ke Kalimantan Timur Pada Twitter. S1 Sistem Informasi thesis, STMIK Widya Cipta Dharma.
Amar P. Natasuwarna, 2019, Analisis Sentimen Keputusan Pemindahan Ibukota Negara Menggunakan Klasifikasi Naive Bayes, Seminar Nasional Sistem Informasi dan Tehnik Informasika (2019).
Santoso, Imam., Gata, Windu., Paryanti, Atik Budi, 2019, Penggunaan Feature Selection di Algoritma Support Vector Machine untuk Sentimen Analisis Komisi Pemilihan Umum, Jurnal Resti (Rekayasa Sistem dan Teknologi Informasi) Vol. 3 No. 3 (2019) 364 – 370.
Saputra, Suwanda Aditya., Rosiyadi, Didi., Gata, Windu., Husain, Syepry Maulana., 2019, Analisis Sentimen E-Wallet Pada Google Play Menggunakan Algoritma Naive Bayes Berbasis Particle Swarm Optimization, Jurnal Resti (Rekayasa Sistem dan Teknologi Informasi) Vol. 3 No. 3 (2019) 377 – 382.
Copyright (c) 2020 Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright in each article belongs to the author
- The author acknowledges that the RESTI Journal (System Engineering and Information Technology) is the first publisher to publish with a license Creative Commons Attribution 4.0 International License.
- Authors can enter writing separately, arrange the non-exclusive distribution of manuscripts that have been published in this journal into other versions (eg sent to the author's institutional repository, publication in a book, etc.), by acknowledging that the manuscript has been published for the first time in the RESTI (Rekayasa Sistem dan Teknologi Informasi) journal ;
