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All Journal Algoritme Jurnal Mahasiswa Teknik Informatika
Wulandari, A’isyah
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Computer Science & IT

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Identifikasi Penyakit Anemia menggunakan Metode Support Vector Machine (SVM) Berdasarkan Hemoglobin Darah Wulandari, A’isyah; Wahyuni, Sri; Haq, Dina Zatusiva; Novitasari, Dian C Rini
Jurnal Algoritme Vol 5 No 2 (2025): Jurnal Algoritme
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v5i2.8767

Abstract

In the world, the number of people infected with anemia is still very high, especially in the Asian region, reaching 48.7 percent. Anemia or anemia occurs due to a lack of blood pressure below normal values. If many people experience blood shortages, there will be many people who suffer from anemia. So it can be seen that variable Then the variable Y shows that the anemia class can be grouped into two parts, namely class 1 which states that they are infected with anemia and class 0 which states that they are not infected with anemia. This research aims to identify anemia using the Support Vector Machine (SVM) method which can be used in the analysis process with approaches from various types of kernels including; Linear, Radial Basis Function (RBF), Polynomial, and Sigomid to determine the level of accuracy, sensitivity and specificity in anemia. This research can show that the best classification of anemia using a linear kernel produces an accuracy value of 99.3 percent. The results obtained from this study indicate that the SVM method with a linear kernel is highly effective in identifying and classifying cases of anemia.
Co-Authors Haq, Dina Zatusiva Novitasari, Dian C Rini Sri Wahyuni