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Journal : Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)

GAMA CUTE: Development of a Web-based for Gadjah Mada Caring University for Thalassemia Exit Prediction Tool by Applying Machine Learning Saputra, Dimas Chaerul Ekty; Afiahayati, Afiahayati; Ratnaningsih, Tri
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i3.29301

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.
Co-Authors ADAM FERDIANSYAH Adnan, Muhammad Luthfi Afiahayati Afiahayati, Afiahayati AGUS AGUS Amar Akbar Ambarwati, Tri Juningaju Andini, Yusria Annis Catur Adi Arijadi, Desi Arista, Desi Astutik, Widya Ayu Sari Ning Ati Br. Karo, Dina Andriani Budi Mulyono Caibigan, Ritchie Natuan Chatarina Umbul Wahyuni Dian Nugraheni Diannisa Ikarumi Dimas Chaerul Ekty Saputra Donytra Arby Wardhana Dyah Aruming Tyas Ellsyana Erdyan Romadeni putri Elna, Nandara Priyanti Faisal Ibnu Fardhiasih Dwi Astuti Fatimah, Bunga Futri, Irianna Hadi Prayitno, Hadi Harahap, Nur Imma Hari Basuki Notobroto Harmaniati, Harmaniati Heriyanto Putri, Rona Hafida Heriyanto, Moch Junaidy Ibnu, Faizal Ifa Roifah Ima Rahmawati Imam Zainuri Indah Lestari, Indah Indra Lesmana Indra Yulianti Iwan Dwiprahasto Lutfi Wahyuni Mahardika Agus Wijayanti Mariadi, M. Meilinawati, Elies Meilinawati, Elies Miftahurrahmi, Rofifah Muhammad Sajidin Muliasih, Mulat Mulyadi Mulyadi Mulyati Mulyati Muryadi, Elvaro Islami Niken Satuti Nur Handayani Nilam Purwa Seven, Nilam Nina Widyaningrum Nisa, Afifah Khairu Pagan, Muasir Phann, Raksmey Prajna Paramita, Prajna Putri, Rona Hafida Heriyanto Retnowati, Jajuk Rina Nur Hidayati, Rina Nur Ristya Widi Endah Yani Riza Anama, Riza Rizki A. Gumilang Rodhi Hartono Rodhi Hartono Rosalia, Sabella Rahmawati, Rhea Santoso, Griselda Elisse Sasangka, Bambang Sismindari . siti indatul laili, siti indatul Siti Mas Miranda Soewono Soewono Soewono, Soewono Sunat, Khamron Supargiyono - Supatmini, Erna Suryono Yudha Patria Sutaryo Sutaryo Titis Murti Utami, Titis Tri Peni Tri Peni, Tri Tria Wahyu Ningrum Tristifany, Annisa Tun, Su Sandi Hla Usi Sukorini Usman, Muhammad Alvin Ramadhan Widiyanti, Ayu Tri Widya Asmara Widyasari, Vita Wijayanti, Lumastari Ajeng Win, Thinzar Aung Windarwati, Windarwati Windu Santoso, Windu Yanasta Yudo Pratama Yusnaini Yusnaini Zakiyah, Nurul Zakiyah, Nurul Zamroni, Asroful Hulam