Article Per Year (5 Year)
p-Index From 2019 - 2024
1.235
P-Index
This Author published in this journals
All Journal Panrita Abdi - Jurnal Pengabdian pada Masyarakat Jurnal Mantik Penusa IJISTECH (International Journal Of Information System & Technology) IJISTECH Information System Journal (INFOS) Jurnal Abdi Masyarakat Indonesia
Erni Seniwati
Universitas AMIKOM Yogyakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Public Health Social Sciences Other

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal Mantik Penusa

 1 
Implementasi Metode Forward Chaining Pada Sistem Pakar Pendiagnosis Gangguan Ansietas (Studi Kasus: Pijar Psikologi) Adhisti Eka Putri; Barka Satya; Erni Seniwati
Jurnal Mantik Penusa Vol. 2 No. 2 (2018): Computer Science
Publisher : Lembaga Penelitian dan Pengabdian (LPPM) STMIK Pelita Nusantara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (315.759 KB)

Abstract

CASE BASED REASONING MENGGUNAKAN ALGORITMA BAYESIAN UNTUK PENENTUAN PEMBERIAN BERAS MISKIN Erni Seniwati
Jurnal Mantik Penusa Vol. 2 No. 2 (2018): Computer Science
Publisher : Lembaga Penelitian dan Pengabdian (LPPM) STMIK Pelita Nusantara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (302.785 KB)

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%.
Co-Authors Achmad Lukman Acihmah Sidauruk Adhisti Eka Putri Andi Sutra Kusumaningrum Banu Santoso Barka Satya Bayu Setiaji Diana Koesuma Dina Maulina Hastari Utama Hery Iswanto Irma Rofni Wulandari La Ode Syafaat Hidayat M.Iqbal Abdullah Sukri Muhammad Iqbal Kusrachmansyah Muhammad Noor Arridho Nila Feby Puspitasari Yuli Astuti Yuli Astuti