Making a simple linear regression to help students understand the fundamentals of data analytics, such as data reading, model selection, and validation with R² scoring.

Kelompok 14

Tugas Data Mining Library Occupancy & Energy Consumption versi R

Kelompok 9 Muhammad Irfan Kurniawan 5003231194 Tugas Datmin K

A Data Mining Lecture Assignment for wifi and Electricity data from Lanchester University Library

TUGASSS

This project explores the relationship between library occupancy (estimated through WiFi connection counts) and electricity consumption (measured from three energy meters in the library). The datasets are processed through data cleaning, timestamp synchronization, missing value imputation, and integration across sources. The analysis is presented using time series plots, scatter plots, and 24-hour daily profiles, with additional comparisons between weekdays and weekends. The goal is to understand library usage patterns, identify peak hours of occupancy, and examine how these patterns align with energy demand.