Harfu Jar Detection System In Al-Quran Using Pierce Similarity Algorithm as a Basic Learning Media of Arabic Language

Arabic language has a very broad language structure, we need to know the most dominant Arabic language found in the Al-Quran, so to know the interpretation (Tafsir) of the Al-Quran, we must learn Arabic language. One of the basic parts of Arabic language is nahwu science, nahwu is the study of laying row in Arabic such as the kasra, dhamma and fatta. Jar letters is one of basic part in nahwu science. In this research, a detection system about Jar patterns will be developed with image processing approach. This system was built using Delphi XE with 7 sample of Jar letters where it will be used in the training process. The process of detecting Jar patterns is using a method that will find the distance value from training and testing process on the Al-Quran image. Training process stage begins with the bitmap extension file of the original image,then change the size to gray scale level and convolution edge detection so that it will produce a vector value for each Jar pattern. Testing process will be use the Pierce Similarity Algorithm to measure the distance value of the Jar pattern to be recognized. The percentage of system detection results obtained, the pierce similarity method is able to recognize a Jar pattern of 60-80%.