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All Journal Journal of Software Engineering, Information and Communication Technology
Ramdhani, Arya Dwi
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Prediction of Mobile Phone Ratings with SVM Regression Model Ramdhani, Arya Dwi; Budi, Fahri Admana; Dimulya, Rizky
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 2: Desember 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v4i2.64392

Abstract

Mobile is a communication tool that has capabilities such as computers that are easy to carry anywhere with various functions for human life. Mobile phones certainly have quite interesting trends, such as the emergence of models, types, and brands which of course vary. The purpose of this study was to determine the prediction of mobile phone ratings based on various criteria using the SVM method. These criteria include price, camera, internal memory, storage, color and so on. From the SVM model, the regression type gets predictive results, where there are values that are adjusted to the model. Although the accuracy is not good, in the prediction process the difference is not too far, but slightly different. The more you add related features, the the training accuracy will be better.
Co-Authors Budi, Fahri Admana Dimulya, Rizky