Analisis hubungan antara Classroom Environment dan Physics Identity siswa menggunakan metode Structural Equation Modeling (SEM) dengan pendekatan CB-SEM dan estimator Maximum Likelihood Robust (MLR) pada dataset SPHERE.

Machine learning and statistical classification analysis for obesity level prediction using Multinomial Logistic Regression and Quadratic Discriminant Analysis with multivariate assumption testing and model comparison.

Implementasi MANOVA, ANCOVA, dan MANCOVA pada Dataset Manufacturing Quality Decisions Penelitian ini bertujuan untuk menganalisis pengaruh faktor operasional terhadap kualitas produk pada proses manufaktur berbasis Internet of Things (IoT).

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.