UGC Ba Mathematics: Data Analytics with Asst. Prof. Krit Sittivangkul

The UNDIP Bachelor of Mathematics Study Program successfully held a series of Undip Global Classroom (UGC) lectures on May 22 and May 29, 2026. The event, which took place in a hybrid format, featured a data science expert from Mae Fah Luang University, Thailand, Asst. Prof. Krit Sittivangkul, as the keynote speaker.

Centering on the grand theme of the modern data world, this lecture series aimed to equip students with a practical understanding of how mathematics is utilized to process digital information.

Session 1 (May 22, 2026): Introduction to Data Analytics
In the first meeting, Asst. Prof. Krit took the participants on a deep dive into Introduction to Data Analytics. He emphasized that data without analysis is nothing more than a lifeless stack of numbers. In today’s Big Data era, the ability to translate data into strategic decisions is absolutely crucial. Students were guided to understand how mathematical foundations—such as statistics and linear algebra—serve as the driving engine behind modern predictive technology.

Session 2 (May 29, 2026): Association Analysis and Clustering
Building on the enthusiasm of the previous week, the second session focused on two advanced techniques in data mining: Association Analysis and Clustering.

Association Analysis: Prof. Krit explained how algorithms (such as Apriori) are used to uncover hidden patterns between variables, one example being the prediction of consumer shopping behavior in the retail industry (market basket analysis).

Clustering: The session concluded with an in-depth breakdown of unlabeled data grouping. He demonstrated how the K-Means algorithm works to group data based on characteristic similarities, which is highly useful for everything from market segmentation to medical analysis.

The Head of the Bachelor of Mathematics Study Program hopes that this international collaboration will continue to thrive. Through UGC 2026, students are expected not only to master theories on paper but also to stand ready to meet industry demands as competent, global data scientists.