GAUSSIAN PROCESS REGRESSOR DENGAN KOMBINASI KERNEL DALAM PREDIKSI LOYALITAS PADA STUDI KASUS OJEK ONLINE DENGAN GUI STREAMLIT

Aziziyah, Luqna (2025) GAUSSIAN PROCESS REGRESSOR DENGAN KOMBINASI KERNEL DALAM PREDIKSI LOYALITAS PADA STUDI KASUS OJEK ONLINE DENGAN GUI STREAMLIT. Undergraduate thesis, Universitas Pembangunan Nasional Veteran Jawa Timur.

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Abstract

This research aims to predict customer loyalty of online motorcycle taxi services in Surabaya using the Gaussian Process Regressor (GPR) method that combines several kernels. In the context of intense competition in the application-based transportation industry, understanding the factors that influence customer loyalty is crucial. Data was collected through a survey involving 467 students from public universities in Surabaya, focusing on service quality, price, and innovation. The analysis was conducted using a systematic approach that included data collection, validation, cleaning, and modeling. The results show that the combination of GPR kernels can capture non-linear patterns in survey data that often contain high Noise. The evaluation model shows good performance with low RMSE and MAPE values and R² close to 1. This research makes an important contribution to the development of strategies for online motorcycle taxi service providers to improve customer experience and maintain market share.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Prasetya, Dwi Arman	NIDN0005128001	arman.prasetya.sada@upnjatim.ac.id
Thesis advisor	Trimono, Trimono	NIDN0008099501	trimono.stat@upnjatim.ac.id

Subjects:

H Social Sciences > HA Statistics
H Social Sciences > HE Transportation and Communications
Q Science > QA Mathematics
Q Science > QA Mathematics > QA76.6 Computer Programming

Divisions:

Faculty of Computer Science > Departemen of Data Science

Depositing User:

Luqna Aziziyah

Date Deposited:

17 Mar 2025 04:57

Last Modified:

17 Mar 2025 04:57

URI:

https://repository.upnjatim.ac.id/id/eprint/35576