Plasmodium Falciparum Identification in Thick Blood Preparations Using GLCM and Support Vector Machine (SVM)

Authors

  • Farah Zakiyah Rahmanti Universitas Dian Nuswantoro
  • Novita Kurnia Ningrum Universitas Dian Nuswantoro
  • Septian Enggar Sukmana Universitas Dian Nuswantoro
  • Prajanto Wahyu Adi Universitas Dian Nuswantoro

DOI:

https://doi.org/10.33633/jais.v2i1.1388

Abstract

Malaria is one of the serious diseases that require rapid handling, otherwise it can lead to death. One of the causes of malaria parasites is plasmodium falciparum which can cause severe or fatal malaria. Handling a medical late can increase the risk of death. Therefore, it takes a rapid identification system with a high percentage of accuracy to reduce the risk of death. This research aims to build an identification system of plasmodium falciparum in thick blood film using Gray Level Co-occurrence Matrix (GLCM) and Support Vector Machine (SVM). The GLCM is used to get texture feature values such as contrast, correlations, energy, and homogeneity from images. Those values is processed and as an input of classification using SVM. The research result using SVM for accuracy value of  plasmodium falciparum identification can reach 93.33%.

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Published

2017-04-21

Issue

Vol. 2 No. 1 (2017): April 2017

Section

Articles

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