Prediction of Mobile Phone Ratings with SVM Regression Model

Arya Dwi Ramdhani, Fahri Admana Budi, Rizky Dimulya

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.


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References


Darmawan, A., Kustian, N., & Rahayu, W. (2018). IMPLEMENTASI DATA

MINING MENGGUNAKAN MODEL SVM UNTUK PREDIKSI KEPUASAN

PENGUNJUNG TAMAN TABEBUYA. Jurnal String Vol. 2 No. 3, 299-307.

E. D. Wahyuni, A. A. Arifiyanti, & M. Kustyani. (2019). “Exploratory Data Analysis dalam Konteks Klasifikasi Data Mining,” Pros. Nas. Rekayasa Teknol. Ind. dan Inf. XIV Tahun 2019, vol. 2019, no. November, pp. 263–269.

Feri Prasetyo, RACHMATSYAH, A. D., & Wahyu Tisno Atmojo. (2021). Pemilihan Handphone dengan Analisis Konjoin Berdasarkan Preferensi Siswa SMA di Kabupaten Bekasi untuk Sekolah Online. Teknomatika, 11(02), 137-142.

Ghorakavi, Veena. (2021). ML |Types of Regression Techniques. Url: https://www.geeksforgeeks.org/types-of-regression-techniques

Khasanah, Latifah Uswatun. (2020). Exploratory Data Analysis : Pahami Lebih Dalam untuk siap Hadapi industri data. Url: https://www.dqlab.id/data-analisis-machine-learning-untuk-proses-pengolahan-dat

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DOI: https://doi.org/10.17509/seict.v4i2.64392

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