Decoding Programming Language Trends in Indonesia: Insights from Clustering and Predictive Analysis

Programming languages play a significant role in technological growth, enabling people to create applications and analyze data. In recent years, programming languages have evolved rapidly, including in Indonesia, where there are fluctuations in the popularity of programming languages. This study aims to explore the programming language trends in Indonesia, examine the interrelationship between the components, and determine the most popular programming languages in Indonesia using machine learning and statistical analysis. Our unsupervised clustering methods with silhouette scores greater than 0.7 reveal a clear boundary between popular and unpopular languages, where popular programming languages tend to have higher job numbers, GitHub users, Wikipedia views, and so on. Our research also identifies Java, Javascript, PHP, Python, SQL, C, and C++ as the most popular languages in Indonesia. Classification models are applied to predict the TIOBE Index using Wikipedia views and Google Trends as the features. However, the model’s accuracy is only favorable for Python and Java with the best model for Python being MLP with the accuracy of 0.831 and for Java being Random Forest with the accuracy of 0.812.