Jurnal Mantik Penusa
Vol. 2 No. 2 (2018): Computer Science

CASE BASED REASONING MENGGUNAKAN ALGORITMA BAYESIAN UNTUK PENENTUAN PEMBERIAN BERAS MISKIN

Erni Seniwati (Universitas AMIKOM Yogyakarta)



Article Info

Publish Date
20 Mar 2019

Abstract

Poor rice (Raskin) badly needed by families who are poor or less capable. Rice is a staple food for most humans. Granting Raskin still found still less on target due to the measurement data of each poor family or less capable in the selection with no maximum. In order for data selection can be done properly so that the granting of Raskin can be right on target so this research will use the concept of CBR. Case Based Reasoning (CBR) or also called Case-based Reasoning with (CPB) is a concept that can provide the output based on the happenings in the present compared with the incidence in the past in the form of a case. Bayes algorithm can be used on the concept of CBR on the process of retrieval and similarity. The process of retrieval and similarity using Bayes algorithm based on data the parameters of assessment (PP) and the data class eligibility. This research uses data parameters 9 assessment (PP) with code PP1 to PP9 and use 2 class class i.e. feasibility "decent" (C1) and the class "not worthy" (C2). From 9 PP and 2 class has 15 sample data case that happened in the past. Fifteen cases of tested data with data input new cases and generate value for the probability of bayes of 0.000045655 i.e. the class "Worthy" and accuracy results from 15 case data that is 80%.

Copyrights © 2018