Project completed as part of a Data Camp course.

Analisis ini bertujuan untuk mengevaluasi hubungan antar variabel menggunakan metode Structural Equation Modeling–Partial Least Square (SEM-PLS). Tahapan analisis meliputi pre-processing data, pengujian reliabilitas dan validitas, evaluasi outer model dan inner model, hingga bootstrapping untuk menguji signifikansi hubungan antar konstruk. Hasil penelitian menunjukkan bahwa sebagian besar konstruk memiliki validitas dan reliabilitas yang baik serta hubungan antar variabel yang signifikan, sehingga model mampu menjelaskan pengaruh faktor teknologi, organisasi, dan lingkungan terhadap intention, performance, dan customer outcome.

Data Visualization and Exploratory Data Analysis in R with GWalkR

Every summer, Hollywood bets big on blockbusters. But which genres dominate? Do longer movies actually score better with audiences? Has “summer movie” quality improved over the decades or are we drowning in nostalgia? This report analyzes the TidyTuesday Summer Movies dataset (Week 31, 2024), sourced from IMDb via the TidyTuesday project. It consists of two tables from the same release: summer_movies — one row per movie, with title, year, runtime, average rating, and vote count. summer_movie_genres — one row per movie-genre pair (movies can belong to multiple genres), used to examine what kinds of films dominate the season. I merge these two tables to explore the intersection of genre, ratings, runtime, and era.

Workshop 3 - Data Structures Alberto Dorantes, Ph.D. Tec de Monterrey