Clustering Level of Cigarettes Addiction Among Malikussaleh University Students Using K-Means Method

Abstract

Cigarettes are a form of tobacco product produced by rolling dried tobacco leaves into small cylindrical sticks. Cigarettes are usually used for smoking, namely smoking and inhaling the smoke produced when tobacco leaves are burned. Cigarettes generally contain ingredients such as tobacco leaves, which can contain nicotine, an addictive substance that causes dependence. Apart from that, cigarettes also contain various other dangerous chemicals such as tar, carbon monoxide and formaldehyde. The smoke produced when a cigarette is burned creates more than 4,000 chemicals, of which about 70 are known to cause cancer. This research aims to help students at the Faculty of Engineering, Malikussaleh University to help students find out the level of their addiction to cigarettes. This research also gave birth to a grouping system that uses the Python programming language and MySQL as the database. The K-Means Clustering algorithm used in this grouping system states that out of 200 students at the Faculty of Engineering, Malikussaleh University, 28 people are smokers who have a low level of addiction (C1), 77 people have a moderate level of addiction (C2), 55 people have a heavy level of addiction. (C3), 40 people had a very severe level of addiction (C4). This system can be used to determine the level of cigarette addiction among students at the Faculty of Engineering, Malikussaleh University in the future.