Penerapan Metode Eksponential Smoothing Dalam Memprediksi Jumlah Peserta Didik Baru Di Sma Favorit Kota Payakumbuh

Abstract

Forecasting is a technique for estimating a value on a particular object in the future by paying attention to past data. This forecasting uses the Exponential Smoothing models because the data used is in accordance with the model. This study aims to predict the number of students in favorite high schools in Payakumbuh based on data obtained from 2014 until 2021 which is grouped into science and social studies classes. Forecasting is done using a Single Exponential Smoothing and Double Exponential models. MAPE results show that the Double Exponential Smoothing model is better at predicting the number of new students than Single Exponential Smoothing. Keywords: Double exponential smoothing, forecasting, single exponential smoothingMSC2020: 62M10

Strategy for Services Anticipation at the Rehabilitation Center of BNN Based on Moving Average and Exponential Smoothing Forecasting Method

“…SES is generally used in short-term forecasting and is a smoothing method more suitable for predicting things that are fluctuating randomly or something that is not regular. This method assumes that data fluctuates around a fixed average value without any consistent trend or growth pattern (Marizal & Mutiarani, 2022). SES Formula: 𝐹𝑡 +1 = 𝐹𝑡 + 𝛼 (𝑌𝑡 − 𝐹𝑡) Description: 𝐹𝑡+1: new forecast (for time period 𝑡 + 1); 𝐹𝑡: previous forecast (for time period t); α: constant alignment; and 𝑌𝑡: the actual value of the last period.…”

“…DES is a type of forecasting done when the data shows a consistent trend or change in the data obtained (Marizal & Mutiarani, 2022). DES Formula:…”

Prediction Of New Students Using The Exponential Smoothing Method (Case Study: STMIK Kaputama)

“…Exponential smoothing is a moving average forecasting method with advanced weighting, but it is still easy to use. This method does very little mutilation of past data [9]. The " single exponential method Smoothing is the development of a simple moving avarage method, which initially uses the formula: Ft+1: forecast for the period to t + 1 XT: the real value of the period to t T : moving average timeframe…”

“…Variable is an attribute or nature or value of people, objects or activities that have certain variations that are set by researchers to be studied and then drawn conclusions [9] To clarify, the symbol X is given as a free variable and the symbol Y as a bound variable.…”

Penerapan Metode Triple Exponential Smoothing dalam Peramalan Produksi Buah Nenas di Provinsi Riau

“…Plot Time series Produksi Nenas Provinsi RiauBerdasarkan plot data pada diatas, dapat dilihat bahwa pola data hasil produksi nenas di Provinsi Riau dari tahun 2019 sampai 2022 cenderung mengalami kenaikan dan penurunan yang dapat kita asumsikan sebagai pola trend dan juga musiman sehingga metode peramalan Tripple Exponantial Smoothing dapat digunakan. Metode Triple Exponential Smoothing adalah sebuah metode yang menggunakan data Time series yang diperoleh dari tiga pemulusan, yaitu pemulusan Trend, dan musiman dengan tiga parameter pemulusan yaitu ,, dan  yang masing-masing parameter permulusan bernilai antara 0-1 [19]. Mencari nilai pemulusan untuk data keseluruhan, trend, dan musiman.…”