Implementasi Machine Learning Untuk Prediksi Harga Laptop Menggunakan Algoritma Regresi Linear Berganda - Sari, Noer Nilam; Anisah, Tiyar Tohirotun; Fitriani, Risma (Jurnal Manajemen Informatika JAMIKA, 2024)
This article discusses the implementation of machine learning using multiple linear regression algorithms to predict laptop prices. The main objective of this research is to design an appropriate predictive model based on various features such as technical specifications and laptop brands. The research stages include literature study, collection of relevant datasets, pre-processing or data cleaning, Exploratory Data Analysis, Feature Engineering, data splitting, model building, and website development. The results show that the proposed model is able to provide price predictions with a high level of accuracy, measured using evaluation metrics such as Mean Absolute Error (MAE) which produces a value of 0.18 and R-squared (R²) which has a value of 0.68. Implementation was done by integrating Jupyter Notebook, Visual Studio Code (VS Code) and Streamlit for interactive web application development. The conclusion of this research is that the multiple linear regression algorithm is effective in predicting laptop prices, and can be used as a tool in making business decisions and pricing strategies.