GAMA CUTE - Development of a Web-based for Gadjah Mada Caring University for Thalassemia Exit Prediction Tool by Applying Machine Learning

Aug 5, 2026

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Blood disorders affect blood structure and function and can be acute or chronic, with anemia being one of the most common conditions. Anemia reduces red blood cells or hemoglobin, lowering the body’s oxygen-carrying ability. The number of anemic patients in Indonesia has increased among people aged 15–24 years. This study develops a machine-learning screening approach for anemia classification into four classes: Beta Thalassemia Trait, Iron Deficiency Anemia, Hemoglobin E, and a combination class.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages16

Reading Time40 min

AccessFree to download

Abstract

Anemia Background and Motivation

Machine Learning Approach and Classes

Model Building and Evaluation

GUI Implementation and Results

GAMA CUTE: Development of a Web-based for Gadjah Mada Caring University for Thalassemia Exit Prediction Tool by Applying Machine Learning Dimas Chaerul Ekty Saputra 1,2,3, Afiahayati4, Tri Ratnaningsih5 1Department of Biomedical Engineering, Graduate School, Gadjah Mada University, Yogyakarta 55284, Indonesia 2Department of Computer Science, College of Computing, Khon Kaen University, Khon Kaen 40002, Thailand 3Department of Informatics, School of Computing, Telkom University Surabaya, Surabaya 60231, Indonesia 4Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Gadjah Mada University, Yogyakarta 55281, Indonesia 5Department of Clinical Pathology and Laboratory Medicine, Faculty of Medicine, Public Health and Nursing, Gadjah Mada University, Yogyakarta 55281, Indonesia ARTICLE INFO Article history: Received July 03, 2024 Revised November 19, 2024 Published September 28, 2021 Keywords: Anemia; Classification; Machine Learning; Random Forest; K-Nearest Neighbor; GUI Corresponding Author: ABSTRACT Blood disorders occur in one or several parts of the blood that affect the nature and function, and blood disorders can be acute or chronic. Blood disease consists of several types, such as anemia. Anemia is the most common hematologic disorder associated with a decrease in the number of red blood cells or hemoglobin, causing a decrease in the ability of the blood to carry oxygen throughout the body. Patients with anemia in Indonesia have increased for the age of 15-24 years. This study aimed to conduct a screening test for anemia using machine learning. It is expected to know the process of knowing the type of anemia suffered. The machine learning technique used to identify the cause of anemia is divided into four classes, namely Beta Thalassemia Trait, Iron Deficiency Anemia, Hemoglobin E, and Combination (Beta Thalassemia Trait and Iron Deficiency Anemia or Hemoglobin E and Iron Deficiency Anemia) . This study would apply the K-Nearest Neighbor (KNN) and Random Forest (RF) methods to build a model on the data collected. The evaluation results using a confusion matrix in the form of accuracy, precision, recall, and f1-score against the KNN and RF methods are 79.36%, 59.40%, 62.80%, and 62.80% . In comparison, the RF is 87.30%, 90.89%, 78.40%, and 81.00% . From the results of comparing the two methods, the Graphic User Interface (GUI) implementation using python applies the RF method. The classifier that gets the highest value among all these parameters is called the best machine learning algorithm to perform screening tests for anemia. This work is licensed under a Creative Commons Attribution-Share Alike 4.0 Afiahayati, Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Gadjah Mada University, Yogyakarta 55281, Indonesia Email: [afia@ugm.ac.id](afia@ugm.ac.id) 1. INTRODUCTION Blood cells in the human body influence the health of the human body [1] . Human blood cells are generally divided into three types, namely red blood cells, white blood cells and platelets [2] . The three types certainly have their respective functions and duties in the human body ’s blood circulation system [3] . A blood disorder is a disorder that occurs in one or several parts of the blood so that it affects the amount and function, and blood disorders can be acute or chronic [3], [4]. There are several types of blood disorders, such as anemia. Anemia is a disease associated with a decrease in the total number of red blood cells or haemoglobin in the blood or a decrease in the ability of the blood to carry oxygen throughout the body [5] . When anemia comes on slowly, the symptoms are often vague, and you will feel weak, tired, lethargic, limp, and tired [6] . This condition can occur because the blood cells in the body do not get enough oxygen, or the blood cells in the body experience a lack of oxygen supply. Anemia can occur temporar

FAQs

What problem does the study address?

The study targets anemia screening by recognizing anemia types from clinical data using machine learning, aiming to support accurate identification of the condition.

Which anemia categories are used in the classification model?

The model classifies into four classes: Beta Thalassemia Trait, Iron Deficiency Anemia, Hemoglobin E, and a combination class (Beta Thalassemia Trait and Iron Deficiency Anemia or Hemoglobin E and Iron Deficiency Anemia).

Why was Random Forest selected for the GUI implementation?

The results from accuracy, precision, recall, and F1-score comparisons show Random Forest achieved higher performance overall, so it is used in the Python-based GUI for screening.

Aug 5, 2026

Upload by Asher