ARDL METHOD: Forecasting Data Curah Hujan Harian NTB

Azmi, Ulul; Hadi, Zilullah Nazir; Soraya, Siti

doi:10.30812/varian.v3i2.627

Cited by 13 publications

(11 citation statements)

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“…There are several calculations commonly used to calculate the total forecasting error. Several methods commonly used are mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percent error (MAPE) [6].…”

Section: Literature Review a Forecastingmentioning

confidence: 99%

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Application of the Single Moving Average, Weighted Moving Average and Exponential Smoothing Methods For Forecasting Demand At Boy Delivery

Alex

Rahmawati²

2023

TJAIE

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Boy Delivery is a delivery service in the city of Lamongan which has been operating for about 4 years. Boy Delivery has an average of 12,000 demand per month. However, the high demand was not accompanied by good demand management, Boy Delivery often piled up and even rejected a number of demand due to the unavailability of drivers at that time, this was due to an incorrect prediction of demand. Therefore this research was conducted to help forecast future demand using the Single Moving Average, Weighted Moving Average, and Exponential Smoothing methods. Of the three methods, the Single Exponential Smoothing method was obtained as the best method with the most accurate results with a smaller error of 5.481%.

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Section: Literature Review a Forecastingmentioning

confidence: 99%

“…This value is determined by taking the deviation value and then dividing it by the number of periods (n) [13]. What needs to be remembered here is that MAD is the error value that appears and becomes the first parameter of the success of a model [6]. (2) (1)…”

Section: F Mad (Mean Absolute Deviation)mentioning

confidence: 99%

Application of the Single Moving Average, Weighted Moving Average and Exponential Smoothing Methods For Forecasting Demand At Boy Delivery

Alex

Rahmawati²

2023

TJAIE

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“…Metric evaluasi digunakan untuk mengukur kesesuaian antara data yang yang sudah ada dengan data yang di prediksi. Ketepatan prediksi adalah suatu hal yang penting untuk peramalan [17]. Adapun uraian dari beberapa perhitungan performa prediksi, sebagai berikut.…”

Section: Metric Evaluationunclassified

“…Hal tersebut bertujuan untuk mengantisipasi kesalahan atau error yang bernilai negatif, sehingga dapat menentukan nilai rata-rata kesalahan secara tepat [17]. Dimana 𝑒 𝑖 merupakan rata-rata nilai kesalahan dan n merupakan banyaknya data.…”

Section: ) Mean Absolute Error (Mae)unclassified

Perbandingan Kinerja Algoritma Recurrent Neural Network (Rnn) Dan Long Short-Term Memory (Lstm): Studi Kasus Prediksi Kemacetan Lalu Lintas Jaringan Pt Xyz

Nurashila,

Hamami,

Kusumasari

2023

jipi. jurnal. ilmiah. penelitian. dan. pembelajaran. informatik

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Peningkatan perkembangan teknologi sebanding dengan peningkatan penggunaan internet. Kualitas jaringan internet di Indonesia yang masih rendah dengan peningkatan penggunaan jaringan yang terus bertambah menyebabkan kemungkinan terjadinya kemacetan jaringan lebih tinggi. Penggunaan internet yang tinggi menyebabkan seringkali terjadi kemacetan jaringan yang menyebabkan penurunan kualitas dan performa jaringan. Pada penelitian ini akan dilakukan prediksi lalu lintas jaringan. Terdapat beberapa model algoritma yang dapat digunakan untuk melakukan prediksi dan penelitian ini akan dibahas mengenai perbandingan performa dari model Long Short-Term Memory (LSTM) dan Recurrent Neural Network (RNN). Dari hasil perbadingan diperoleh bahwa LSTM memiliki nilai yang lebih tinggi dalam performa dengan mendapatkan nilai akurasi R-Squard sebesar 99.2% jika debandingkan dengan model dengan algoritma RNN yang memiliki nilai akurasi R-Squard sebesar 99,1%. Manfaat dari penelitian ini yaitu untuk menguji performa dari model LSTM dan RNN terhadap dataset PT XYZ. Penelitian ini diharapkan dapat memberikan referensi kepada pengembang model Deep Learning untuk pengembangan kedepannya agar mendapatkan hasil yang lebih baik.

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“…Dimana Xt = Data aktual St = Data hasil peramalan n = jumlah periode Mean Absolute Deviation (MAD) merupakan ukuran pertama atas keseluruhan dalam kesalahan peramalan untuk model [17]. Nilai ini dihitung dengan mengambil jumlah nilai absolut kesalahan peramalan individual (deviasi) dan membaginya dengan jumlah data (n).…”

Section: Pengukuran Akurasiunclassified

Komparasi Metode Single Moving Average dan Double Exponential Smoothing untuk Peramalan Penjualan Produk Gerabah pada UD. Amerta Sedana

Yanti¹,

Ginantra²,

Wulandari³

et al. 2022

Jur. Ris. Kom.

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One of the areas producing creative industries in Bali is Tabanan Regency which produces creative industries in the form of pottery. In the community, earthenware products are usually known in the form of objects that function as containers, for example flower vases, pots, barrels, jugs, jars and so on. Sales of pottery products at the UD company. Amerta Sedana every month experiences erratic fluctuations. In planning sales, the company only estimates the number of sales without using the scientific method as a benchmark to assist the company in determining the next sales. This causes the company to be unable to maximize sales for the following month and fulfill consumer demand for goods. One solution that can be used is to do forecasting. Forecasting is a picture of the state of the company in the future and this picture is very important for the company. There are various types of methods that can be used to perform forecasting calculations. This study uses a comparison of the Single Moving Average and Double Exponential Smoothing methods for forecasting sales of small pot number 1, pot lion white, and pot monkey. The results showed that the calculation with the smallest error value was the sale of small pot number 1 with the 2-month Single Moving Average method with an MSE value of 56.1 and an MAD value of 4.942857, a lion white pot with a 2-month Single Moving Average method with an MSE value of 707.3214. and the MAD value is 18.82857, the monkey pot uses the 2-month Single Moving Average method with a value of 247.8786 and a MAD value of 11.32857

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ARDL METHOD: Forecasting Data Curah Hujan Harian NTB

Cited by 13 publications

References 0 publications

Application of the Single Moving Average, Weighted Moving Average and Exponential Smoothing Methods For Forecasting Demand At Boy Delivery

Application of the Single Moving Average, Weighted Moving Average and Exponential Smoothing Methods For Forecasting Demand At Boy Delivery

Perbandingan Kinerja Algoritma Recurrent Neural Network (Rnn) Dan Long Short-Term Memory (Lstm): Studi Kasus Prediksi Kemacetan Lalu Lintas Jaringan Pt Xyz

Komparasi Metode Single Moving Average dan Double Exponential Smoothing untuk Peramalan Penjualan Produk Gerabah pada UD. Amerta Sedana

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