PREDIKSI HARGA SMARTPHONE MENGGUNAKAN ALGORITMA MULTIPLE LINEAR REGRESSION

• Main Author: Toni Muhayat, (Author)
• Format: Book
• Published: 2022-07-21.
• Subjects: Thesis; NonPeerReviewed
• Online Access: Link Metadata
• Notes: http://repository.upnvj.ac.id/19675/17/ABSTRAK.pdf; http://repository.upnvj.ac.id/19675/21/AWAL.pdf; http://repository.upnvj.ac.id/19675/4/BAB%201.pdf; http://repository.upnvj.ac.id/19675/5/BAB%202.pdf; http://repository.upnvj.ac.id/19675/6/BAB%203.pdf; http://repository.upnvj.ac.id/19675/16/BAB%204.pdf; http://repository.upnvj.ac.id/19675/19/BAB%205.pdf; http://repository.upnvj.ac.id/19675/9/DAFTAR%20PUSTAKA.pdf; http://repository.upnvj.ac.id/19675/10/RIWAYAT%20HIDUP.pdf; http://repository.upnvj.ac.id/19675/11/LAMPIRAN.pdf; http://repository.upnvj.ac.id/19675/12/HASIL%20PLAGIARISME.pdf; http://repository.upnvj.ac.id/19675/13/ARTIKEL%20KI.pdf
• Keywords: QA75 Electronic computers. Computer science; QA76 Computer software

A cell phone or cell phone is one of the evidences of a product of increasingly advanced technological sophistication, because of its general function. Mobile is a long distance communication tool. But now cellphones can be multifunctional and change all aspects of human life, from reading the news, playing games, shooting, and so on. The cell phone is getting more sophisticated so that people call the new term "Smartphone". More than 50% of the people in the world have a smartphone, because the smartphone is one of the main needs of each individual due to its efficient use. Seeing how many consumers use smartphones, this study aims to predict the price (dependent variable) of a smartphone. This prediction test is based on the specifications of the components (independent variables) on the smartphone. From these independent variables, it is one of the things that prospective smartphone buyers pay close attention to in choosing smartphone products. The technique for predicting the price of a smartphone is using the multiple linear regression algorithm in the machine learning concept. The results obtained in this study are found that the correlation test between the independent variables that affect the dependent variable (price) which is 0.80 in R squared can be said to be a "strong" correlation. Meanwhile, the achievement of forecasting between prediction results and price data is 23.9%, which can be said to be a "Reasonable" forecast achievement according to MAPE calculations.