Analysis of Sales Prediction Using Linear Regression as a Data Analytics Learning Media for Students
DOI:
https://doi.org/10.56480/jln.v6i1.34Keywords:
Linear Regression, Data Analytics, Sales Prediction, Learning, Real DatasetAbstract
This research aims to analyze the application of the linear regression method in sales prediction and evaluate its use as a data analytics learning media for students. The method used is a quantitative descriptive approach with two main stages: sales data analysis using linear regression and collecting student perception data through Likert scale-based questionnaires. The dataset used consists of simple sales data that is easy for students to process and understand. The analysis results show that the linear regression method can be used to predict sales effectively and provides a clear overview of the relationships between variables. Furthermore, the questionnaire results indicate that students responded positively to the use of real datasets in learning, particularly in improving material comprehension, engagement in the learning process, and ease of data analysis. Thus, the use of linear regression with real datasets can serve as an effective alternative learning media to enhance student data literacy. This research is expected to be a reference for developing data-based learning methods in the field of data analytics.
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Copyright (c) 2026 Agus Nugroho, Tyasmiarni Citrawati, Agung Setyawan (Author)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
