Analisis Pemodelan Topik Saran Pengguna Jalan Tol dengan Latent Dirichlet Allocation (LDA)

Ashrul Khair(1*), A. N. Hidayanto(2),

(1) Universitas Indonesia, Indonesia
(2) Universitas Indonesia, Indonesia
(*) Corresponding Author

Abstract


Service and safety for toll road users are two crucial aspects in the operation of toll roads. This research aims to evaluate and analyze toll road users feedback after receiving assistance by officers and determine the dimensions of Service Quality that have been fulfilled from the distribution of topics obtained. The method applied is Latent Dirichlet Allocation (LDA), a topic modeling technique that can analyze thematic patterns in text collections. By applying LDA to the dataset of toll road user suggestions, this research seeks to uncover the main topics related to improving service quality in toll road operations. Through this analysis process, the company can recognize common problems that are often emphasized by toll road users and understand their needs and expectations for improving toll road service quality. This research shows that the company has fulfilled four service-related dimensions namely reliability, assurance, responsiveness, and tangibles. This shows that the company has carried out the duties and responsibilities of service to road users well. With this research, the company is expected to be able to improve service-related performance in order to maintain positive sentiment for the company's performance in the eyes of the community.

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References


H. T. Zuna, S. P. Hadiwardoyo, and H. Rahadian, “Analyzing Service Quality of Toll Road and Its Relation with Customer Satisfaction in Indonesia using Multivariate Analysis Ministry of Public Works and Housing, Indonesia a.”

R. Siti, N. Cahyati Hidayat, and M. Setiawardani, “Service Quality dan Implikasinya Terhadap Kepuasan Pelanggan,” Jurnal Riset Bisnis & Investasi, vol. 3, no. 2, 2017.

C. Saricam, “Analysing Service Quality and Its Relation to Customer Satisfaction and Loyalty in Sportswear Retail Market,” Autex Research Journal, vol. 22, no. 2, pp. 184–193, Jun. 2022, doi: 10.2478/aut-2021-0014.

B. A. Tondang, Muhammad Rizqan Fadhil, Muhammad Nugraha Perdana, Akhmad Fauzi, and Ugra Syahda Janitra, “Analisis pemodelan topik ulasan aplikasi BNI, BCA, dan BRI menggunakan latent dirichlet allocation,” INFOTECH : Jurnal Informatika & Teknologi, vol. 4, no. 1, pp. 114–127, Jun. 2023, doi: 10.37373/infotech.v4i1.601.

O. Oshriyeh, “Applied data science in tourism (Interdisciplinary approaches, methodologies, and applications,” Information Technology & Tourism, vol. 25, no. 1, pp. 133–136, Mar. 2023, doi: 10.1007/s40558-023-00243-2.

H. Nabli, R. Ben Djemaa, and I. A. Ben Amor, “Efficient cloud service discovery approach based on LDA topic modeling,” Journal of Systems and Software, vol. 146, pp. 233–248, Dec. 2018, doi: 10.1016/j.jss.2018.09.069.

I. Sutherland and K. Kiatkawsin, “Determinants of guest experience in Airbnb: A topic modeling approach using LDA,” Sustainability (Switzerland), vol. 12, no. 8, Apr. 2020, doi: 10.3390/SU12083402.

N. Korfiatis, P. Stamolampros, P. Kourouthanassis, and V. Sagiadinos, “Measuring service quality from unstructured data: A topic modeling application on airline passengers’ online reviews,” Expert Syst Appl, vol. 116, pp. 472–486, Feb. 2019, doi: 10.1016/j.eswa.2018.09.037.

M. Mujahid, F. Rustam, F. Alasim, M. A. Siddique, and I. Ashraf, “What people think about fast food: opinions analysis and LDA modeling on fast food restaurants using unstructured tweets,” PeerJ Comput Sci, vol. 9, 2023, doi: 10.7717/peerj-cs.1193.

K. Bastani, H. Namavari, and J. Shaffer, “Latent Dirichlet allocation (LDA) for topic modeling of the CFPB consumer complaints,” Expert Syst Appl, vol. 127, pp. 256–271, Aug. 2019, doi: 10.1016/j.eswa.2019.03.001.

Q. Meng and H. Xiong, “A doctor recommendation based on graph computing and lda topic model,” International Journal of Computational Intelligence Systems, vol. 14, no. 1, pp. 808–817, 2021, doi: 10.2991/ijcis.d.210205.002.

T. Ali, B. Marc, B. Omar, K. Soulaimane, and S. Larbi, “Exploring destination’s negative e-reputation using aspect based sentiment analysis approach: Case of Marrakech destination on TripAdvisor,” Tour Manag Perspect, vol. 40, Oct. 2021, doi: 10.1016/j.tmp.2021.100892.




DOI: http://dx.doi.org/10.30645/jurasik.v10i1.877

DOI (PDF): http://dx.doi.org/10.30645/jurasik.v10i1.877.g852

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