Peramalan Pertumbuhan Ekonomi Provinsi Bengkulu Menggunakan Single Moving Average, Single Eksponential Smoothing Dan Ensemble

Fransiska, Herlin

doi:10.25157/teorema.v7i1.7002

Cited by 2 publications

(2 citation statements)

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“…For example, in some previous research has been done by combining other methods, among others: Previous research has combined other methods such as the comparison of ARIMA Box Jenkins forecasting with ARIMA ensemble (Tasyah et al, 2023). Other research on economic growth forecasting involves 3 methods Single MA, Single Exponential and ensemble (Fransiska, 2022). And finally another study, comparing ARIMA, GSTAR, ensemble stacking, and ensemble averaging found that the ensemble method produced the lowest RMSE value in rainfall forecasting (Anggraeni et al, 2018).…”

Section: Arima and Arimaxmentioning

confidence: 99%

The Effect of Ensemble Averaging Method on Rainfall Forecasting in Jakarta Using ARIMA and ARIMAX

Mahmudi,

Hidayat,

Wijaya

2024

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This research discusses rainfall modeling using ARIMA and ARIMAX models in Jakarta. This is important because rainfall forecasting in Jakarta has a significant impact on flooding and infrastructure. The focus of this research is on significant ARIMA and ARIMAX models, which are then subtotaled using ensemble averaging. Humidity and temperature variables are of particular interest in ARIMAX modeling due to their high correlation with rainfall. This quantitative research uses secondary data analysis from Tanjung Priok and Kemayoran Stations through the BMKG website, from July 2018 to June 2023. The results obtained at Tanjung Priok Station there are five significant ARIMA models and three significant ARIMAX models. While at Kemayoran Station there are 6 significant ARIMA models and two significant ARIMAX models. After using the ensemble averaging method on both ARIMA and ARIMAX models, the resulting SMAPE value is not better than the best ARIMA or ARIMAX models at both stations. Of all the models performed, the best model in forecasting with the smallest SMAPE is ARIMAX (0,0,1) at Tanjung Priok Station which is 37.83% and at Kemayoran Station which is 27.59%. This research provides new insights and significant contributions in understanding and developing rainfall forecasting in Jakarta using the ensemble averaging method.

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Section: Arima and Arimaxmentioning

confidence: 99%

The Effect of Ensemble Averaging Method on Rainfall Forecasting in Jakarta Using ARIMA and ARIMAX

Mahmudi,

Hidayat,

Wijaya

2024

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“…Selain itu, pemilihan metode peramalan juga pernah dilakukan terhadap pertumbuhan ekonomi Provinsi Bengkulu. Pada penelitian ini metode yang dibandingkan adalah Single Moving Average, Single Exponential Smoothing, dan Ensemble dengan hasil Single Moving Average ialah metode yang terbaik [11].…”

Section: Pendahuluanunclassified

Pemilihan Metode Peramalan yang Tepat Untuk Meramalkan Permintaan Piston Cup Forging di Perusahaan Spare-part Kendaraan

Sari

Winarno

2023

JSE

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The demand for Piston Cup Forging in spare-part companies every period has increased and decreased, which causes uncertainty about product demand. In this case, the company needs to do demand forecasting. There are various methods of doing forecasting. Companies must choose the best forecasting method, so that companies can make decisions more effectively and efficiently. This research aims to compare the best forecasting methods to apply for companies. The methods that will be compared in this research are Moving Average 3 monthly and 5 monthly, and Exponential Smoothing with α = 0,1; α = 0,5; and α = 0,9. The error accuracy calculations used are Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). From the results of calculations and analysis, the method that has the lowest error rate is the Exponential Smoothing method with α = 0,1, with MAD of 16.695, MSE of 510.645.732, and MAPE value of 61%. So in estimating the demand for Piston Cup Forging over the upcoming period in spare-part companies can use the Exponential Smoothing method with α = 0,1.

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Peramalan Pertumbuhan Ekonomi Provinsi Bengkulu Menggunakan Single Moving Average, Single Eksponential Smoothing Dan Ensemble

Cited by 2 publications

References 0 publications

The Effect of Ensemble Averaging Method on Rainfall Forecasting in Jakarta Using ARIMA and ARIMAX

The Effect of Ensemble Averaging Method on Rainfall Forecasting in Jakarta Using ARIMA and ARIMAX

Pemilihan Metode Peramalan yang Tepat Untuk Meramalkan Permintaan Piston Cup Forging di Perusahaan Spare-part Kendaraan

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