Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro
Vol 11 No 1 (2024): DIELEKTRIKA

Studi Literatur Mengenai Prediksi Kepuasan GrabFood Menggunakan Machine Learning

Martiani, Evi (Unknown)
Setyanto, Arief (Unknown)
Nasiri, Asro (Unknown)



Article Info

Publish Date
29 Feb 2024

Abstract

The rapid growth of food delivery applications, such as GrabFood, has revolutionized the way consumers access and enjoy their favorite meals. Ensuring customer satisfaction is crucial for these platforms to maintain their competitive edge and foster customer loyalty. If many customers are not satisfied with the service or anything provided by GrabFood, it is possible that they will leave the application soon or later. This research is aimed to review some literature related to customer satisfaction of the food delivery application with the use of machine learning. From this review, one can have more information and insight on how machine learning can help to find the satisfaction level of the customers. The method which is used in this research is literature review which reviews the collection of literature. Varied literature with different variables has been resulted from this research. Many of them use different methods of machine learning.

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Journal Info

Abbrev

dielektrika

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering Energy

Description

The Aims and scope of the Dielektrika are Power System, Telecommunication, electronics and computer of informatics, including: Electrical Power Systems, High Voltage Technology, Renewable Energy, Power Electronics, Sensing and Automation, Telecommunication system and technique, Signal Processing, ...