Iridology is one method to know the condition of the human body using the iris of the eye. One of the use of iridology is to know the cholesterol in the body is characterized by the ring cholesterol. This study aims to make an application to identify cholesterol levels using iris image with Hough transformation and Daugman’s Rubber Sheet Model. The system is built using only the iris of the image so that there is a separate process to separate the iris of the eye with the pupil and cornea. Separate iris parts are then processed using discrete Wavelet transforms and Square Shape Matrix to extract the features and produce an iris feature. The iris feature is processed using the Support Vector Machine as a training and testing algorithm. The built application has four main processes: data storage, training, classification, and system testing. The results of the implementation of an application that can identify four types of classification are “Normal”, “Cholesterol Symptoms”, “Sub Cholesterol Acute”, and “Cholesterol Acute”. The test used 40 images as data with data sharing using 10-Fold Cross Validation. The results of cholesterol level identification testing of the train data and test data resulted in an average accuracy of 90% and an average sensitivity of 80%.

Mubarok, Indra Maulana Husni and Wibawa, Helmie Arif (2015) IDENTIFIKASI TINGKAT KOLESTEROL MENGGUNAKAN IRIS MATA DENGAN METODE TRANSFORMASI HOUGH DAN DAUGMAN’S RUBBER SHEET MODEL. Undergraduate thesis, Universitas Diponegoro.

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