I collaborated with Shofi on this project, along with the Data Warehouse project that I will tell after this post. As the title said, it’s about “Prostate Cancer Risk Diagnosis Using Evolving Fuzzy Systems”. The method that we used, evolving fuzzy systems or EFS, was chosen by Mrs. Intan as the lecturer.
To be honest, Mrs. Intan explained a lot about soft computing. I liked how she lectured. It was super detailed and challenging at the same time. What I didn’t like was the speed of how she lectured. She talked too fast 😭 I couldn’t follow her pace so I usually didn’t take a very well written note of her lectures. Most of the soft computing lectures she gave to the students were in English since there were very few Indonesian researchers who focused on soft computing. She told us she wasn’t good in English but she proved to us that if we wanted to learn, there’s the way.
Soft computing is the door of real artificial intelligence. If we want to learn how AI thinks, then we should learn soft computing. In this subject, Mrs. Intan was too good to be a lecturer because we didn’t have to chunk all of the methods that we’ve learned but she would choose one method to each team. My team got EFS.
It’s hard to find an EFS project because this method was too old and almost nobody would use it. In the end, we decided to make it by ourselves but using EFSLab as the supporting software. You can download EFSLab here. We used Prostate Cancer Diagnosis as our topic because we were inspired by a paper that wasn’t explained well (that’s why we couldn’t use it as our project). The dataset was downloaded from Kaggle, here’s the link.
The trials and errors were done mostly by Shofi while I was focused on the paper writing. The paper was completed enough to describe how our project was made and how to use the program so go take a look on my Github to see my repository.
Today was the day of the paper submission but we were surprised to see that we had to take a final exam too! Luckily, the exam wasn’t too hard. It’s harder to do this project rather than the exam though.