IDENTIFIKASI STATUS PERLINDUNGAN ANAK MENGGUNAKAN ALGORITMA KLASIFIKASI K-NEAREST NEIGHBORS
Keywords:knn, child protection, classification, algorithm, NGOs, identification.
The United Nations Children's Fund (UNICEF) has defined the child protection system as “certain formal and informal structures, functions and capacities that have been pooled to prevent and respond to violence, abuse, neglect and exploitation of children”. Problems identified by the Sulawesi Community Foundation group (CSF) is the absence of digital records that accommodate the results of direct interviews with children in terms of measuring experiences or actions that have been experienced by a child as a source of information that can be used for decision-making needs. The KNN algorithm is one of the most popular data mining algorithms. It has been widely and successfully applied to data analysis applications across various research topics in computer science. Based on the value of Classification Y, obtained as much as 1 data Category = Unprotected, and 3 data Category = Protected, then the resulting decision is that the identification of child protection status in an area is based on attribute values X1=5, X2=3, X3=50 and X4 = Does not result in a decision that the majority of children have guaranteed protection status. The decisions made are in accordance with the facts, therefore the Sulawesi Community Foundation NGO can apply the results of analysis and testing into an integrated system so that it can become a valid source of information in digital format.
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