PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN

Time series model is the model used to predict the future using past data, one example of a time series model is exponential smoothing. Exponential smoothing method is a repair procedure performed continuously at forecasting the most recent data. In this study the exponential smoothing method is app...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Faisol Faisol, Sitti Aisah
Formato:	article
Lenguaje:	EN
Publicado:	Department of Mathematics, UIN Sunan Ampel Surabaya 2016
Materias:	double exponential smoothing BPJS kesehatan Pamekasan Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/7766e024fdf543039003655e8977f0e4
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:7766e024fdf543039003655e8977f0e4
record_format	dspace
spelling	oai:doaj.org-article:7766e024fdf543039003655e8977f0e42021-12-02T17:17:10ZPENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN2527-31592527-3167https://doaj.org/article/7766e024fdf543039003655e8977f0e42016-10-01T00:00:00Zhttp://jurnalsaintek.uinsby.ac.id/index.php/mantik/article/view/68https://doaj.org/toc/2527-3159https://doaj.org/toc/2527-3167Time series model is the model used to predict the future using past data, one example of a time series model is exponential smoothing. Exponential smoothing method is a repair procedure performed continuously at forecasting the most recent data. In this study the exponential smoothing method is applied to predict the number of claims in the health BPJS Pamekasan using data from the period January 2014 to December 2015, the measures used to obtain the output of this research there are four stages, namely 1) the identification of data, 2) Modeling, 3) forecasting, 4) Evaluation of forecasting results with RMSE and MAPE. Based on the research methodology, the result for the period 25 = 833.828, the 26 = 800.256, period 27 = 766.684, a period of 28 = 733.113, period 29 = 699.541, and the period of 30 = 655, 970. Value for RMSE = 98.865 and MAPE = 7.002, In this case the moving average method is also used to compare the results of forecasting with double exponential smoothing method. Forecasting results for the period 25 = 899.208, the 26 = 885, 792, 27 = 872.375 period, a period of 28 = 858.958, period 29 = 845.542, and the period of 30 = 832.125. Value for RMSE = 101.131 and MAPE = 7.756. Both methods together - both have very good performance because the value of MAPE is below 10%, but the method of exponential smoothing has a value of RMSE and MAPE are smaller than the moving average method.Faisol FaisolSitti AisahDepartment of Mathematics, UIN Sunan Ampel Surabayaarticledouble exponential smoothingBPJS kesehatan PamekasanMathematicsQA1-939ENMantik: Jurnal Matematika, Vol 2, Iss 1, Pp 46-51 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	double exponential smoothing BPJS kesehatan Pamekasan Mathematics QA1-939
spellingShingle	double exponential smoothing BPJS kesehatan Pamekasan Mathematics QA1-939 Faisol Faisol Sitti Aisah PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN
description	Time series model is the model used to predict the future using past data, one example of a time series model is exponential smoothing. Exponential smoothing method is a repair procedure performed continuously at forecasting the most recent data. In this study the exponential smoothing method is applied to predict the number of claims in the health BPJS Pamekasan using data from the period January 2014 to December 2015, the measures used to obtain the output of this research there are four stages, namely 1) the identification of data, 2) Modeling, 3) forecasting, 4) Evaluation of forecasting results with RMSE and MAPE. Based on the research methodology, the result for the period 25 = 833.828, the 26 = 800.256, period 27 = 766.684, a period of 28 = 733.113, period 29 = 699.541, and the period of 30 = 655, 970. Value for RMSE = 98.865 and MAPE = 7.002, In this case the moving average method is also used to compare the results of forecasting with double exponential smoothing method. Forecasting results for the period 25 = 899.208, the 26 = 885, 792, 27 = 872.375 period, a period of 28 = 858.958, period 29 = 845.542, and the period of 30 = 832.125. Value for RMSE = 101.131 and MAPE = 7.756. Both methods together - both have very good performance because the value of MAPE is below 10%, but the method of exponential smoothing has a value of RMSE and MAPE are smaller than the moving average method.
format	article
author	Faisol Faisol Sitti Aisah
author_facet	Faisol Faisol Sitti Aisah
author_sort	Faisol Faisol
title	PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN
title_short	PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN
title_full	PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN
title_fullStr	PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN
title_full_unstemmed	PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN
title_sort	penerapan metode exponential smoothing untuk peramalan jumlah klaim di bpjs kesehatan pamekasan
publisher	Department of Mathematics, UIN Sunan Ampel Surabaya
publishDate	2016
url	https://doaj.org/article/7766e024fdf543039003655e8977f0e4
work_keys_str_mv	AT faisolfaisol penerapanmetodeexponentialsmoothinguntukperamalanjumlahklaimdibpjskesehatanpamekasan AT sittiaisah penerapanmetodeexponentialsmoothinguntukperamalanjumlahklaimdibpjskesehatanpamekasan
_version_	1718381152216023040

PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN

Ejemplares similares