A Comparison Between Triple Exponential Smoothing And Monte Carlo Methods In The Prediction Of Chicken Business Profit at Poultry Farm Livestock Of Jatipuro District

Autor:	Yessy Fitriani, Yoga Distra Sudirman, Mochamad Farid Rifai, Dine Tiara Kusuma, Yudhy Setyo Purwanto
Rok vydání:	2020
Předmět:	Financial management History Mean absolute percentage error business.industry Statistics Monte Carlo method Exponential smoothing Livestock business Profit (economics) Computer Science Applications Education Mathematics
Zdroj:	Journal of Physics: Conference Series. 1477:032006
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1477/3/032006
Popis:	With a prediction of profits, farmers can anticipate if the next harvest has experienced a slight profit or failed to harvest and so that farmers still have business capital and they do not experience a stable cage (bankrupt). This research objective is comparing two kind prediction method. Methods to be compared are Triple Exponential Smoothing and Monte Carlo methods. To find out the value of the compatibility of the two methods used MAPE (Mean Absolute Percentage Error) which can find out the percentage of the error value. This method are used for farmers financial management in predict their profit. To implement both methods, past data are used, namely the previous harvest profit data. Result of this study, by using Triple Exponential Smoothing method produces a MAPE value of 12.10% with a value of α = 0.3 and the Monte Carlo method produces a MAPE value of 40.58%.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1ec11f72eef6e3b8d78489f99290e6fd https://doi.org/10.1088/1742-6596/1477/3/032006 Zobrazit plný text záznamu