Open AccessSimulasi Monte Carlo dalam Memprediksi Penerimaan Peserta Pelatihan Dasar CPNS
Author(s) -
Faisal Roza,
Sarjon Defit,
Gunadi Widi Nurcahyo
Publication year - 2021
Publication title -
jurnal informasi dan teknologi
Language(s) - English
Resource type - Journals
ISSN - 2714-9730
DOI - 10.37034/jidt.v3i3.140
Subject(s) - christian ministry , civil servant , monte carlo method , scope (computer science) , computer science , value (mathematics) , operations research , statistics , politics , mathematics , political science , machine learning , law , programming language
The implementation of basic training recruit (latsar) of civil servant (CPNS) at Pusat Pengembangan Sumber Daya Manusia (PPSDM) Ministry of Internal Affairs regional Bukittinggi. The leader takes decision in doing the implementation of latsar CPNS recruit in PPSDM scope regional Bukittinggi. Latsar CPNS is one of requirements to be civil servant. Therefore, it is necessary to collect data by doing observation, interview questionings with related party in the implementation of latsar CPNS recruit from 2018 to 2020. It can be predicted for the next recruit. After doing library references by reading some books and journals, the basic training recruit of CPNS sources from PPSDM regional Bukittinggi, and Monte Carlo simulation. By using Monte Carlo simulation in predicting data, it can get closer value of actual value. Based on distribution of sampling data, the method is by choosing random numbers from probability distribution to do simulation. The Monte Carlo result’s examination has got 173 participants for year 2019, 158 participants for year 2020, and 157 participants for year 2021 clearly. Although the rate of the accurate just reaches 81%, but it has been able to be recommended to help PPSDM regional Bukittinggi, Ministry of Internal Affairs in taking decision and planning for basic training recruit of CPNS for the next.