Prediction Of Tiger Shrimp Supply Using Time Series Anlysis Method Case Study CV.Surya Perdana Benur

  • Yoesril Ihza Mahendra Narotama University
  • Natalia Damastuti
Keywords: ARIMA, AR, MA, Tiger Shrimp, ACF, PACF

Abstract

Prediction of demand for tiger shrimp buyers using data from the company CV. Surya Perdana Benur. The process is carried out with the models in the Autoregressive Integrated Moving Average method. Tiger shrimp is a marine animal that is now widely cultivated by big company in Indonesia. Tiger shrimp has important economic value, so its existence must be maintained as part of Indonesian germplasm. The problem now faced by many tiger shrimp companies is the inadequate availability of goods for consumers. This time series data method is useful for predicting the availability of goods for consumers who want to buy goods at the company CV. Surya Perdana Benur. This time series data method is useful for predicting the availability of goods for consumers who want to buy goods at the company CV. Surya Perdana Benur. Autoregressive (AR), MovingAverage (MA), and Autoregressive Integrated Moving Average (ARIMA) model and will be evaluated through Mean Absolute Percent Error (MAPE). The initial process that will be carried out after the data is processed is model identification, estimation of model parameters, residual inspection, using forecasting models if the model has been fulfilled will be evaluated using MAPE until the results come out 14875.593875 to be able to predict the next buyer demand.

Downloads

Download data is not yet available.
Published
2021-02-02
How to Cite
MahendraY., & DamastutiN. (2021). Prediction Of Tiger Shrimp Supply Using Time Series Anlysis Method Case Study CV.Surya Perdana Benur. JEEIT nternational ournal of lectrical ngineering and nformation echnology, 3(1), 27 - 32. https://doi.org/10.29138/ijeeit.v3i1.1303
Section
Articles
Abstract viewed = 0 times
PDF downloaded = 0 times