Penelitian ini menganalisis data kualitas udara ruangan berdasarkan parameter kecepatan udara (velocity), suhu (temperature), dan kelembapan relatif (RH) menggunakan bahasa pemrograman R. Analisis meliputi statistik deskriptif, pengelompokan kategori, serta visualisasi data untuk menggambarkan kondisi lingkungan ruangan.

This project presents the implementation of various clustering methods for customer segmentation based on spending behavior. The analysis uses a dataset containing customer income, purchasing activity, and product expenditure to identify distinct customer groups. Several clustering algorithms, including K-Means, K-Median, DBSCAN, Mean Shift, and Fuzzy C-Means, are applied and compared to evaluate their performance. The results show that customers can be grouped into low, medium, and high-value segments, with each method producing different clustering characteristics. This study highlights the effectiveness of clustering techniques in understanding customer behavior and supporting data-driven marketing strategies.

Laporan ini berisi analisis multivariat menggunakan dataset Titanic dengan bantuan software R. Analisis yang dilakukan meliputi pembuatan correlation matrix, variance-covariance matrix, serta perhitungan eigen value dan eigen vector untuk memahami hubungan antar variabel dan tingkat keragaman data.