Data Analytics
Indonesia Tourism Data Analytics.
Exploratory analysis of tourism data to uncover patterns in visitor satisfaction, pricing, and destination characteristics.
Project Information
Project Details
Overview
This project analyzes monthly production data to understand production patterns and develop a prediction model for future production values.
Process
The analysis began with data quality assessment and preprocessing, including removing irrelevant columns, handling missing values, removing 79 duplicate rating records, and categorizing ticket prices into four groups. The tourism and rating datasets were then merged using Place_Id, producing an integrated dataset for exploratory analysis. The analysis included descriptive statistics, segmented analysis by tourism category, subgroup comparison by city, price-category analysis, correlation analysis, and One-Way ANOVA. Advanced analysis was also performed by combining City and Category to identify more specific patterns in average destination ratings.
Insights
The analysis identified Category, City, and Price_Category as the variables showing the clearest variation in average destination ratings.
Taman Hiburan recorded the highest average rating among the tourism categories analyzed.
Yogyakarta recorded the highest average destination rating among the cities analyzed, while Jakarta had a relatively lower average rating.
More affordable destinations tended to have slightly higher average ratings, although the analysis was exploratory and did not establish a causal relationship.
The combined City and Category analysis revealed more specific patterns, with Bandung's Pusat Perbelanjaan category recording an average rating of 3.29 and Surabaya's Tempat Ibadah category recording 3.28.
Correlation analysis showed a very weak relationship between ticket price and average rating (r = -0.01), suggesting that ticket price was not a major factor associated with satisfaction in this dataset.
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