Surakarta Batik is a traditional cloth in Indonesia that has been designated as an intangible cultural heritage by the Ministry of Education and Culture. The Surakarta Batik Pattern has characteristics and has a story in each style. The method used affects the accuracy of each pattern in the Surakarta batik image. Image data used for training data are 100 image data with a size of 256 x 256 pixels, with test image data used as many as 20 image data. Improving the quality of the image using contrast stretching, the output is processed to separate objects with the background using adaptive thresholding. The obtained object is added by the canny process and calculated using the Gray Level Co-Occurrence Matrix to obtain the characteristics of each image. The characteristics used are four variables (energy, contrast, homogeneity, and correlation). The resulting variable is used as input to the classification using backpropagation. The test results obtained an accuracy rate of 95%, with an error rate of 0.05%.
The stage of region of interest (ROI) is the determining part to the next stage in image processing. ROI is a process of taking certain parts or regions in an image. ROI can be done by manual and automatic cropping. Some previous studies still use cropping manually for detection of malaria parasites. This study uses cropping automatically for detection of malaria parasites. The types of malaria parasites used were falciparum, vivax and malariae with ring stages, tropozoite, schizon and gametocytes. Data from malaria parasites were obtained at the North Sumatra Provincial Health Laboratory. The results show that the ROI image can crop the malaria parasite region. Keyword - malaria parasite, ROI.
The use of fingerprints for identification has been done a lot, both in the police for investigations, in government for absences, in population and much more. To identify fingerprints, various methods are widely used which purpose is to produce a better level of accuracy. This is as reference to find out how important the function of the method will be used before the identification process is applied. The renewal of this research prioritizes how far the function of GLCM (GRAY LEVEL CO-OCCURRENCE MATRIX) is useful to improve the accuracy of fingerprint identification using the backpropagation method. The test results showed that GLCM can affect the increase in accuracy to 83%.
The economic conditions during the Covid-19 outbreak had an impact on society globally. The number of people who have experienced layoffs has an impact on the economic conditions of the family. The economic impact that helps the community encourages the government to increase efforts to increase social assistance in the form of BLT. However, the distribution of BLT was not right on target, there were still many people who really could not afford not to receive BLT, while those who were still able to get BLT assistance. Therefore, it is important in this study to use a combination of the K-Means Cluster and Decision Tree methods to be used in BLT recipient decision making, with the aim of increasing BLT recipients as expected. The calculation results were obtained using a combination of the K-Means Cluster and Decision Tree methods referring to the criteria for the community who has the right to receive data with an error level of -2.476190476 <from error tolerance 6.84.
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