Sentiment Analysis to Improve the Quality of Public Transportation Services "Suroboyo Bus"
Abstract
Public transportation is a very important tool in improving and developing the economy of an area. The role of public transportation is very important in supporting mobility or community movement. Increased community mobility at the same time can have an impact on congestion. Congestion still occurs a lot and is a fairly complex problem in big cities, one of which is in Surabaya. The government is trying to reduce congestion in Surabaya by creating a safe and comfortable service innovation in the world of transportation, one of which is the Suroboyo Bus. This research is descriptive quantitative research. the method used is the random forest method. The tool used for data analysis is Rapidminer 10.3.1. The results of data analysis found several things that need to be improved by Suroboyo Bus to improve the quality of its services, namely those related to the words bus stops, routes, hours, applications, buses, etc. These words need to be considered to improve the quality of Suroboyo Bus services.
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References
Arista, A. (2023). Sentiment Analysis of Gobis Suroboyo Bus Application Feature Using Support Vector Machinery (SVM) Algorithm. IJCONSIST, 4(2). https://doi.org/https://doi.org/10.33005/ijconsist.v4i2.96
Armayani, R. R., Chintiya Tambunan, L., Siregar, R. M., Lubis, N. R., & Azahra, A. (2021). Analisis Peran Media Sosial Instagram dalam Meningkatkan Penjualan Online. Jurnal Pendidikan Tambusai, 5(3), 8920–8928.
Feroza, C. S., & Misnawati, D. (2020). Penggunaan Media Sosial Instagram Pada Akun @Yhoophii_Official Sebagai Media Komunikasi Dengan Pelanggan. Jurnal Inovasi, 14(1), 31–41.
Ginting, D. C. A., Rezeki, S. G., Siregar, A. A., & Nurbaiti, N. (2024). Analisis Pengaruh Jejaring Sosial Terhadap Interaksi Sosial di Era Digital. PPIMAN : Pusat Publikasi Ilmu Manajemen, 2(1), 22–29. https://doi.org/https://doi.org/10.59603/ppiman.v2i1.280
Haqie, Z. A., Nadiah, R. E., & Ariyani, O. P. (2020). Inovasi Pelayanan Publik Suroboyo Bis Di Kota Surabaya. Journal of Public Sector Innovations, 5(1), 25–30. https://doi.org/https://doi.org/10.26740/jpsi.v5n1.p23-30
Jihad, M. A. A., Adiwijaya, A., & Astuti, W. (2021). Analisis Sentimen Terhadap Ulasan Film Menggunakan Algoritma Random Forest. E-Proceeding of Engineering, 8(5), 10153–10165.
Kibthiah, M., Chamida, R. N., Surabaya, U. N., & Khotimah, K. (2023). Suroboyo Bus Sebagai Sistem Transportasi Berkelanjutan Di Kota Surabaya (Vol. 23, Issue 1). https://doi.org/https://doi.org/10.26593/jtrans.v23i1.6643.11-18
Kotler, P., & Armstrong, G. (2021). Principles of Marketing (18th ed.). Pearson Education Limited.
Manullang, O., Prianto, C., & Harani, N. H. (2023). Analisis Sentimen Untuk Memprediksi Hasil Calon Pemilu Presiden Menggunakan Lexicon Based Dan Random Forest. Jurnal Ilmiah Informatika, 11(02), 159–169. https://doi.org/10.33884/jif.v11i02.7987
Maulana, I., Manulang, J. M. br., & Salsabila, O. (2020). Pengaruh Social Media Influencer Terhadap Perilaku Konsumtif di Era Ekonomi Digital. Majalah Ilmiah Bijak, 17(1), 28–34. https://doi.org/10.31334/bijak.v17i1.823
Nurriqli, A., & Risanta, M. (2021). Pemanfaatan Instagram bagi Pengembangan Pemasaran Usaha Mikro Kecil dan Menengah di Banjarbaru. Jurnal Riset Inspirasi Manajemen Dan Kewirausahaan, 5(1), 50–57. https://doi.org/10.35130/jrimk
Permatasari, P. A., Linawati, L., & Jasa, L. (2021). Survei Tentang Analisis Sentimen Pada Media Sosial. Majalah Ilmiah Teknologi Elektro, 20(2), 177–186. https://doi.org/10.24843/MITE.2021.v20i02.P01
Pradana, M. G. (2020). Penggunaan Fitur Wordcloud Dan Document Term Matrix Dalam Text Mining. Jurnal Ilmiah Informatika, 8(1). https://doi.org/https://doi.org/10.33884/jif.v8i01.1838
Prasetyo, V. R., Lazuardi, H., Mulyono, A. A., & Lauw, C. (2021). Penerapan Aplikasi RapidMiner Untuk Prediksi Nilai Tukar Rupiah Terhadap US Dollar Dengan Metode Linear Regression. Jurnal Nasional Teknologi Dan Sistem Informasi, 7(1), 8–17. https://doi.org/10.25077/teknosi.v7i1.2021.8-17
Putri Watung, M., Ch Rotinsulu, D., & L Tumangkeng, S. Y. (2020). Analisis Perbandingan Pendapatan Ojek Konvensional Dan Ojek Online Di Kota Manado. Jurnal Berkala Ilmiah Efisiensi, 20(3), 126–139. https://ejournal.unsrat.ac.id/v3/index.php/jbie/article/view/30946
Riskania, R., & Thalib, F. (2020). Implementasi Algoritma Naïve Bayes Classifier Dan Confusion Matrix Dalam Analisis Sentimen Terhadap Pelayanan Transportasi Umum Selama Pandemi Covid-19 Pada Media Sosial Twitter. Jurnal Teknologi, 8(1), 64–75. https://doi.org/10.31479/jtek.v1i8.66
Rukmana, S., & Handayani, W. (2023). Analysis of Service Science Design through Customer Experience to Increase PosAja Application User Satisfaction. Kontigensi: Jurnal Ilmiah Manajemen, 11(2), 513–527. https://doi.org/10.56457/jimk.v11i2.402
Rusfiadi, R., Hatani, L., & Suleman, N. R. (2021). Peningkatan Kepuasan Dan Kepercayaan Publik: Berdasarkan Prespektif Kualitas Pelayanan Dan Komitmen (Studi Pada Pemerintahan Desa/Kelurahan Se-Kecamatan Wangi-Wangi Selatan). Jurnal Manajemen, Bisnis Dan Organisasi (JUMBO), 5(2), 281–302. https://doi.org/http://dx.doi.org/10.33772/jumbo.v5i2.20801
Suryantoro, B., & Kusdyana, Y. (2020). Analisis Kualitas Pelayanan Publik Pada Politeknik Pelayaran Surabaya. Jurnal Baruna Horizon, 3(2), 223–229. https://doi.org/https://doi.org/10.52310/jbhorizon.v3i2.42
Syafira, D., & Harianto, S. (2020). Pilihan Rasional Masyarakat Surabaya Dalam Menggunakan Suroboyo Bus. Paradigma, 9(1). https://ejournal.unesa.ac.id/index.php/paradigma/article/view/36838
Toha, Mohamad & Habibah, N.J. (2023). MSME Empowerment and Development Program to Increase Consumer Satisfaction. Sahwahita: Community Engagement Journal, 1(1), 26-39. https://e-journal.bustanul-ulum.id/index.php/Sahwahita/article/view/24
Tupari, T., Abdullah, S., & Chairani, C. (2023). Visualisasi Data Analisa Sentimen RUU Omnibus Law Kesehatan Menggunakan KNN dengan Software RapidMiner. Jurnal Informatika: Jurnal Pengembangan IT, 8(3), 261–268. https://doi.org/10.30591/jpit.v8i3.5641
Valdis Tjahjadi, E., & Santoso, B. (2023). Klasifikasi Malware Menggunakan Teknik Machine Learning. Copyright @BALOK, 2(1). https://doi.org/https://doi.org/10.37195/balok.v2i1.525
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