Penerapan Fitur Warna Untuk Identifikasi Plasmodium Falciparum pada Sediaan Apus Darah Menggunakan MK-Means dan Jaringan Backpropagation

mustamin hamid


Abstract - This research proposed a system to identify Plasmodium falciparum on blood smear  using the neural network  backpropagation. Modified K-Means (MK-Means) is used to separate between the object with the background image because that method was able to equalize the value of fitness at all Center cluster so there is no dead center and can also cope with the local minimum value. The extraction of the features used in this study consists of color features i.e. calculation of the mean, standard deviation, skewness, curtosis and entropy of co-occurent matrix with the purpose to get the values of all the trait value image, obtained are then used to train a neural network with the backpropagation training algorithm. Method of backpropagation networks capable of acquiring knowledge even though there is no certainty, able to perform a generalization and extraction of a specific data pattern.

                        The image of  the preparations  blood smear  are classified using the method of  neural network Backpropagation. The test results obtained from Tropozoit with the accuracy 100%, scizon 80% and gametocytes 80%. Identification is then obtained outcomes the introduction with an average accuracy of 86,66%.

Full Text:




  • There are currently no refbacks.

Copyright (c) 2016 mustamin hamid

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.


Editorial Office:
Jurusan Teknik Informatika
Fakultas Sains dan Teknologi
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Jalan Gajayana 50 Malang, Jawa Timur, Indonesia 65144

Creative Commons License
This work is licensed under a CC-BY-NC-SA.
© All rights reserved 2015. MATICS , ISSN : 1978-161X | e-ISSN :  2477-2550