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Journal : JAIS (Journal of Applied Intelligent System)

Color Variation from Vehicle on The Road and Its Environment Through Subtle Motion Study Case Septian Enggar Sukmana; Farah Zakiyah Rahmanti
Journal of Applied Intelligent System Vol 3, No 1 (2018): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v3i1.1835

Abstract

Road accident has been serious case in Indonesia, the big number of the cases is not decreasing for six years. Many ways have been done, one of example is exploiting smart camera or CCTV to observe mocement estimation explicitly or implicitly. One problem is when explicit-based technique is applied, the computation process would take more resource. Implicit-based technique like exploitting processing-based frequency domain must be tried to make a better study and produce more knowledge in this study field. Color magnification can helpful information to support better movement estimation. This eulerian-based technique may be the one useful method to help this study. This paper implements eluerian video magnification to get color magnification on road as observed environment. This technique produces unexpected result that unknown black color appears, it still ambiguous because some scene can be described as black color object magnification result and another is shocking camera effect so that the technique is difficult to obtain color magnfication result. PSNR results quite better value because in spite of color magnification result distraction, the scenery of the road is not covered fully. SSIM shows that some mapping in each video data can not results same pattern, it is suspicious that SSIM mapping is affected by this color magnification result.
Plasmodium Falciparum Identification in Thick Blood Preparations Using GLCM and Support Vector Machine (SVM) Farah Zakiyah Rahmanti; Novita Kurnia Ningrum; Septian Enggar Sukmana; Prajanto Wahyu Adi
Journal of Applied Intelligent System Vol 2, No 1 (2017): April 2017
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 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%.