Grouping Data of Patients Who Are Conducting Drugs Abuse Rehabilitation Using The Clustering Method (Case Study: BNNK Binjai)

Abstrak

Rehabilitation is an appropriate alternative punishment for drug addicts. By utilizing data mining using input data in the form of rehabilitation patient data at BNNK Binjai, the data will be processed using the clustering method using the k-means algorithm. K-Means is a non-hierarchical data clustering method that seeks to partition existing data into one or more clusters or groups so that data has characteristics. Of the 20 data tested in cluster 1 there are a total of 13 data and are located in the Age group (X) which is 26-35 years old, and for the substance type group (Y) used is methamphetamine and in the Occupational group (Z), namely Self-employed. in cluster 2 there is a total of 5 data and it is located in the Age group (X) which is 26-35 years old, and for the Substance type group (Y) used is Shabu and in the Employment group (Z) namely Not Yet Working. in cluster 3 there is a total of 2 data and it is located in the Age group (X) which is 26-35 years old, and for the Substance type group (Y) used is Shabu and in the Occupational group (Z) namely Private Employees.