IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 10, No 2: June 2021

Pancreatic cancer classification using logistic regression and random forest

Zuherman Rustam (University of Indonesia)
Fildzah Zhafarina (University of Indonesia)
Glori Stephani Saragih (University of Indonesia)
Sri Hartini (University of Indonesia)



Article Info

Publish Date
01 Jun 2021

Abstract

In the medical field, technology machinery is needed to solve several classification problems. Therefore, this research is useful to solve the problem of the medical field by using machine learning. This study discusses the classification of pancreatic cancer by using regression logistics and random forest. By comparing the accuracy, precision, recall (sensitivity), and F1-score of both methods, then we will know which method is better in classifying the pancreatic cancer dataset that we get from Al-Islam Hospital, Bandung, Indonesia. The results showed that random forest has better accuracy than logistic regressions. It can be seen with maximum accuracy of logistic regressions 96.48 with 30% data training and random forest 99.38% with 20% of data training.

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Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...