Analisis Sentimen Terhadap Pemindahan Ibu Kota Negara Menggunakan Algoritma Naive Bayes Classifier dan K-Nearest Neightbors

Dedi Pramana, M Afdal, Mustakim Mustakim, Inggih Permana

Abstract


The relocation of Indonesia's capital city is a hot topic of discussion at the moment. So that this government policy reaps a lot of reactions from various parties, especially the general public in Indonesia. Various reactions were shown with various expressions on various social media. One of the social media that has become a place for people to express themselves in responding to this government policy is Instagram. The comments poured by the community on posts on Instagram are very diverse ranging from positive, negative, and neutral comments. If these comments are processed properly, they can be used as evaluation material for the relocation of the State capital. Seeing this, a sentiment analysis is needed which is intended to classify the various comments so that they can be presented into information which will be intended to help the government make considerations in carrying out policies towards moving the national capital. In this study, data processing was carried out with the Naive Bayes Classifier and K-Nearest Neightbors algorithms with Instagram comment data on posts related to moving the national capital. Where the amount of data used is 2,404 comments. It was found that the accuracy of the NBC algorithm was 63.09% and K-Nearest Neightbors was 69.23% so it can be concluded that KNN is better than NBC. In addition, the popularity of public sentiment towards the relocation of the National Capital was also obtained with a positive sentiment of 28% totaling 643 comments, a neutral sentiment of 42% totaling 1025 comments, and a negative sentiment of 30% totaling 730 comments.

Keywords


Capital City, Instagram, K-Nearest Neighbors, Naive Bayes Classifier

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References


V. B. Anwari, F. T. Informasi, S. Informasi, and U. B. Luhur, “Implementasi Algoritma K-Nearest Neighbors Pada Analisis Sentimen Masyarakat Terhadap Penerapan Pemberlakuan Pembatasan Kegiatan Masyarakat,†vol. 5, 2022.

G. P. Jemparu, “Analisis Sentimen Publik Terhadap Isu Pemindahan Ibukota Negara Indonesia Pada Media Twitter,†2020, [Online]. Available: http://e-journal.uajy.ac.id/id/eprint/22262%0Ahttp://e-journal.uajy.ac.id/22262/1/07079600.pdf

bps.go.id, “BPS Product Search,†BPS id, 2022. https://www.bps.go.id/searchengine/ (accessed Dec. 05, 2022).

M. K. Saraswati, E. Ariananto, and W. Adi, “Pemindahan Ibu Kota Negara Ke Provinsi Kalimantan Timur Berdasarkan Analisis Swot,†vol. 6, no. 2, pp. 4042–4052, 2022.

D. Herdiana, “Pemindahan Ibukota Negara: Upaya Pemerataan Pembangunan ataukah Mewujudkan Tata Pemerintahan yang Baik,†J. Transform., vol. 8, no. 1, pp. 1–30, 2022, doi: 10.21776/ub.transformative.2022.008.01.1.

M. I. Ramadhon, “Analisis Sentimen Terhadap Pemindahan Ibu Kota Indonesia Pada Media Sosial Twitter Menggunakan Metode Algoritma K-Nearest Neighbor (K-Nn),†2020.

M. Al Karim, G. J. Utomo, and B. Fauziah, “Kualitas Hidup Dan Pertumbuhan Ekonomi, Studi Kasus Dki Jakarta Dan Daerah Penyangganya,†J. Pembang. Wil. Kota, vol. 15, no. 3, pp. 227–247, 2019, doi: 10.14710/pwk.v15i3.22287.

F. Hadi and R. Rosa, “Pemindahan ibu kota Indonesia dan kekuasaan presiden dalam perspektif konstitusi The relocation of Indonesia ’ s capital city and the presidential powers in constitutional perspective,†J. Konstitusi, vol. 17, no. 3, pp. 530–537, 2020, [Online]. Available: https://jurnalkonstitusi.mkri.id/index.php/jk/article/view/1734/pdf

D. S. Pribadi and S. Utomo, “Dampak Perpindahan Ibu Kota Negara terhadap Pemulihan Ekonomi dalam Perspektif Persaingan Usaha,†J. Persaingan Usaha, vol. 2, pp. 27–42, 2021, doi: 10.55869/kppu.v2i.28.

2019. Alasan Pemindahan Ibukota CNBC, “Terungkap! Alasan Khusus Jokowi Pindahkan Ibu Kota Negara,†2019. https://www.cnbcindonesia.com/news/20190826133550-4-94659/terungkap-alasan-khusus-jokowi-pindahkan-ibu-kota-negara (accessed Dec. 05, 2022).

S. Jaya, “Analisis Kebijakan Publik Pemindahan Ibu Kota Negara,†vol. 13, no. 2, pp. 155–168, 2022, doi: 10.22212/jekp.v13i1.2155.

L. A. Andika, P. A. N. Azizah, and R. Respatiwulan, “Analisis Sentimen Masyarakat terhadap Hasil Quick Count Pemilihan Presiden Indonesia 2019 pada Media Sosial Twitter Menggunakan Metode Naive Bayes Classifier,†Indones. J. Appl. Stat., vol. 2, no. 1, p. 34, 2019, doi: 10.13057/ijas.v2i1.29998.

D. Asriyadi, “Praktek Demokratisasi Oleh Pengusaha Dalam Perspektif Rent-Seeking Behaviour,†Mimb. Adm., vol. 15, no. 19, 2019.

P. Arsi and R. Waluyo, “Analisis Sentimen Wacana Pemindahan Ibu Kota Indonesia Menggunakan Algoritma Support Vector Machine (SVM),†J. Teknol. Inf. dan Ilmu Komput., vol. 8, no. 1, p. 147, 2021, doi: 10.25126/jtiik.0813944.

P. Arsi, B. A. Kusuma, and A. Nurhakim, “Analisis Sentimen Pindah Ibu Kota Berbasis Naive Bayes Classifier,†J. Inform. Upgris, vol. 7, no. 1, pp. 1–6, 2021, doi: 10.26877/jiu.v7i1.7636.

A. Kurniawan and S. Waluyo, “Penerapan Algoritma Naive Bayes Dalam Analisis Sentimen Pemindahan Ibukota Pada Twitter Application Of Naive Bayes Algorithm In Capital Movement Sentiment Analysis On Twitter,†no. September, pp. 35–41, 2022.

A. Z. Malik, E. Utami, and S. Raharjo, “Analisis Sentiment Twitter Terhadap Capres Indonesia 2019 dengan Metode K-NN,†J. Inf. Politek. Indones. Surakarta, vol. 5, no. 2, pp. 1–7, 2019.

M. I. Mazdadi, I. Budiman, and R. Herteno, “Implementation Of Information Gain And Particle Swarm Optimization On Sentiment Analysis Of Covid-19 Handling Using K-NN,†vol. 6, no. 1, pp. 7–12, 2023, doi: 10.33387/jiko.v6i1.5260.

R. W. Samsir, Ambiyar, Unung Verawardina, Firman Edi, “Analisis Sentimen Pembelajaran Daring Pada Twitter di Masa Pandemi,†J. Media Inform. Budidarma, vol. 5, no. 1, p. 149, 2021, doi: 10.30865/mib.v5i1.2604.

aristin chusnul khotimah and E. Utami, “Comparison Naïve Bayes Classifier, K-Nearest Neighbor and Support Vector Machine in the Classification of Individual on Twitter Account,†J. Tek. Inform., vol. 3, no. 3, pp. 673–680, 2022, [Online]. Available: http://jutif.if.unsoed.ac.id/index.php/jurnal/article/view/254

N. Silalahi and G. L. Ginting, “Analisa Sentimen Masyarakat Dalam Penggunaan Vaksin Sinovac Dengan Menerapkan Algoritma Term Frequence – Inverse Document Frequence ( TF-IDF ) dan Metode Deskripsi,†vol. 3, no. 3, pp. 206–217, 2022, doi: 10.47065/josh.v3i3.1441.

N. Hayatin, G. I. Marthasari, and L. Nuraini, “Optimization of Sentiment Analysis for Indonesian Presidential Election using Naïve Bayes and Particle Swarm Optimization,†J. Online Inform., vol. 5, no. 1, pp. 81–88, 2020, doi: 10.15575/join.v5i1.558.

T. Astuti and Y. Astuti, “Analisis Sentimen Review Produk Skincare Dengan Naïve Bayes Classifier Berbasis Particle Swarm Optimization ( PSO ),†vol. 6, pp. 1806–1815, 2022, doi: 10.30865/mib.v6i4.4119.

M. F. El Firdaus, N. Nurfaizah, and S. Sarmini, “Analisis Sentimen Tokopedia Pada Ulasan di Google Playstore Menggunakan Algoritma Naïve Bayes Classifier dan K-Nearest Neighbor,†JURIKOM (Jurnal Ris. Komputer), vol. 9, no. 5, p. 1329, 2022, doi: 10.30865/jurikom.v9i5.4774.

M. Al Khadafi et al., “Penerapan Metode Naïve Bayes Classifier Dan Lexicon Based Untuk Analisis Sentimen Cyberbullying Pada Bpjs,†J. Mhs. Tek. Inform., vol. 6, no. 2, pp. 725–733, 2022.

J. S. Komputer, N. Ajijah, A. Kurniawan, S. T. Informatika, F. I. Komputer, and U. Singaperbangsa, “Klasifikasi Teks Mining Terhadap Analisa Isu Kegiatan Tenaga Lapangan Menggunakan Algoritma K-Nearest Neighbor ( KNN ),†vol. 7, pp. 254–262, 2023.

Louis Madaerdo Sotarjua and Dian Budhi Santoso, “Perbandingan Algoritma Knn, Decision Tree,*Dan Random*Forest Pada Data Imbalanced Class Untuk Klasifikasi Promosi Karyawan,†J. INSTEK (Informatika Sains dan Teknol., vol. 7, no. 2, pp. 192–200, 2022, doi: 10.24252/instek.v7i2.31385.

M. N. Maskuri, K. Sukerti, and R. M. Herdian Bhakti, “Penerapan Algoritma K-Nearest Neighbor (KNN) untuk Memprediksi Penyakit Stroke Stroke Desease Predict Using KNN Algorithm,†J. Ilm. Intech Inf. Technol. J. UMUS, vol. 4, no. 1, pp. 130–140, 2022.




DOI: https://doi.org/10.30865/mib.v7i3.6523

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