MODEL PREDIKTIF KEPUASAN PELANGGAN PADA HOTEL PLATINUM MENGGUNAKAN MOTODE K-MEANS CLUSTERING

SITI KHOLIJAH SIREGAR, NPM 2109100076 (2025) MODEL PREDIKTIF KEPUASAN PELANGGAN PADA HOTEL PLATINUM MENGGUNAKAN MOTODE K-MEANS CLUSTERING. Tugas_Akhir(Artikel) Journal of Computer Science and Information Systems (JCoInS), 6 (3). pp. 266-273. ISSN 2747-2221(e-ISSN)

[img] Text
COVER.pdf

Download (1MB)
[img] Text
ARTIKEL.pdf

Download (1MB)

Abstract

Customer satisfaction is a key pillar of success in the competitive hospitality industry, directly impacting loyalty and profitability. Recognizing this, Platinum hotels need the ability to predict guest satisfaction in order to refine their service strategies. This study focuses on the development of predictive models of customer satisfaction at Platinum hotel using the K Means Clustering method. This method was chosen because of its effectiveness in grouping complex data into homogeneous segments based on common characteristics. Customer Data will be grouped by attributes of their stay to identify different segments of customers with unique levels of satisfaction and preferences. It is hoped that this model can provide deep insights into customer profiles, reveal hidden patterns, and predict future guest expectations. The results of this study will contribute to improving the quality of Service and strategic decision-making at Platinum hotels and can be a reference for the hospitality industry in implementing a data-driven approach. Keywords : Customer Satisfaction, K-Means Clustering, predictive models, Hospitality Industry

Item Type: Article
Uncontrolled Keywords: Customer Satisfaction, K-Means Clustering, predictive models, Hospitality Industry
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Divisions: Fakultas Sains Dan Teknologi > Sistem Informasi
Depositing User: Unnamed user with email repository@ulb.ac.id
Date Deposited: 19 Nov 2025 07:44
Last Modified: 19 Nov 2025 07:44
URI: http://repository.ulb.ac.id/id/eprint/1981

Actions (login required)

View Item View Item