Implementation of Artificial Neural Network Method in Application Development to Measuring the Severity of Narcotics Substances in Blood

There are various ways to detect the presence of compound drugs, such as heroin, cocaine, morphine in the human body. Either through a urine sample or blood sample. This study was undertaken with the aim to create a system that can detect the severity level of the effects of illegal drugs (narcotics) uses from the blood, with three different level ie minimal, moderate, and severe of the five compounds drugs and hemoglobin levels which contained from each blood sample. The fifth compound including diacetylemorphine, morphine, benzoylecgonine, amphetamine, and phencyclidine. The working system that is in this software includes three essential processing, ie the normalization process of compound levels value in blood samples, training and testing process of Perceptron Neural Network. Initially each value of the five compounds level and level of hemoglobin which contained in blood transformation values to the interval [0, 1], then used as input values in the training process which will give the weights. These weights is then used in the testing process of new blood samples (non-learning data) to provide a prediction of the severity levels of narcotics. From the test results with learning rate 0.3, threshold value 0.5, 2 units of output units and 6 units of input units, this system has a success rate of 60% 100% from the test of a new blood sample data (non-learning data) and 100% for the training sample data (learning data). General Terms Artificial Neural Network, Pattern Recognition