Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/552 2018 2018 Department of computer Engineering, Imam Ja’afar Al-Sadiq University, Baghdad, Iraq Shaymaa Shaymaa Department of computer Engineering, Imam Ja’afar Al-Sadiq University, Baghdad, Iraq Rafah Amer Jaafar Alcoholism may be recognized with the use of (EEG) analyzing signals. None-the-less, the analysis of the multi-channel signals of EEG is a complicated issue that usually needs performing complex computation operations and takes quite a long time to execute. The presented research will propose 13 optimal channel to feature extraction. In this research, an innovative horizontal visibility graph entropy (HVGE) method has been proposed for evaluating signals of EEG from controlled drinkers and alcoholic subjects and comparing against an approach of sample entropy (SaE). Values of HVGE and SaE have been obtained from 1200 records of bio-medical signals.  While  in classification step using SVM as classifier. 2020 2020 14 21 10.54216/FPA.020103 https://www.americaspg.com/articleinfo/3/show/552