scholarly journals Grey Double Exponential Smoothing Dengan Optimasi Levenberg-Marquardt Untuk Peramalan Volume Penumpang Di Bandara Soekarno-Hatta

2020 ◽  
Vol 3 (2) ◽  
pp. 25-39
Author(s):  
Arum Handini Primandari
Keyword(s):  
Low Cost ◽  
Exponential Smoothing ◽  
Volume Data ◽  
Long Distance ◽  
Classic Model ◽  
Class Society ◽  
Double Exponential ◽  
Levenberg Marquardt ◽  
Passenger Volume ◽  
Double Exponential Smoothing

Aircraft has  became the best choice for long distance traveling because it has shortest travel time than any other transportations. Moreover, in recent years, aviation industries have competed for providing low cost flight so that it can also be enjoyed by middle class society. Thus escalate the popularity of aircraft as economical carrier. Knowing the volume of passengers in advance will help government and related institutions to effectively providing facilities. The volume of passengers can be predicted using classic model such as double exponential smoothing model which is simpler and has high accuracy. However, the randomness of Indonesian passenger volume data cause double exponential smoothing (DES) cannot follow both data pattern and data trend. Moreover, classic model often encounters overfitting where the prediction is bigger than the actual data. Therefore, we employed Grey Method applied on DES (GDES) to overcome this problem. GDES enabled the researcher to perform better data fitting because it would generate smoothing curve which showed clearer trend. As the result, although GDES fitting curve had higher error measurement (MSE) than DES, the forecasting result of GDES was more precise than DES. Keyword: Double Exponential Smoothing, Grey Method, Levenberg-Marquardt

FORECASTING ANORGANIC WASTE VOLUME AFTER THE IMPLEMENTATION OF PLASTIC BAG RESTRICTIONS USING DOUBLE EXPONENTIAL SMOOTHING METHOD AT BOGOR CITY

2020 ◽  
Vol 1 (1) ◽  
pp. 28-31
Author(s):  
Ani Andriyati ◽  
Embay Rohaeti
Keyword(s):  
Linear Trend ◽  
Exponential Smoothing ◽  
Plastic Waste ◽  
Regional Government ◽  
Volume Data ◽  
Classic Problem ◽  
Double Exponential ◽  
Plastic Bag ◽  
Double Exponential Smoothing ◽  
Inorganic Waste

Garbage is a classic problem causing environmental and ecosystem damage in every region, including in Bogor City. Plastic is one of the largest types of inorganic waste that causes ecosystem damage. In one day 1,7 tons of plastic waste are produced from a modern shopping center in Bogor. Several attempts were made to reduce the volume of inorganic waste. Since July 2018 the Regional Government of Bogor City has issued a regulation restricting the use of plastic bags in the modern market as an effort to reduce inorganic waste, especially plastic waste. Forecasting the volume of inorganic waste after the enactment of this regulation is needed as an evaluation step. The double exponential smoothing hole model is suitable for linear data trends. This is in accordance with the condition of inorganic waste volume data which tends to have a linear trend. Forecasting produces parameter parameter values α (level) 0,78 and γ (trend) 0,09 also MAPE 7,25%. The forecast results show that the volume of inorganic waste tends to increase in 2020. In order for this regulation to be optimal, it is necessary to consider applying these regulations not only in the modern market but also in the traditional market. In addition, it is also necessary to find an alternative to substitute for plastic so as not to switch to other inorganic types.

scholarly journals PEMODELAN METODE BROWN’S DOUBLE EXPONENTIAL SMOOTHING (B-DES) DAN BROWN’S WEIGHTED EXPONENTIAL MOVING AVERAGE (B-WEMA) MENGGUNAKAN OPTIMASI LEVENBERG-MARQUARDT PADA JUMLAH WISATAWAN DI JAWA TENGAH

2020 ◽  
Vol 9 (3) ◽  
pp. 316-325
Author(s):  
Dilla Retno Deswita ◽  
Abdul Hoyyi ◽  
Tatik Widiharih
Keyword(s):  
Foreign Exchange ◽  
Optimal Parameter ◽  
Moving Average ◽  
Exponential Smoothing ◽  
Forecasting Accuracy ◽  
Central Java ◽  
Tourism Sector ◽  
Double Exponential ◽  
Levenberg Marquardt ◽  
Double Exponential Smoothing

The tourism sector is one of the national development priority sectors because it contributes to foreign exchange earnings, the development of business areas, and the absorption of investment and labor. In 2018 the tourism sector will become the second largest foreign exchange earner after oil palm. Foreign exchange contributed by the tourism sector in 2018 was US $ 19.29 billion, an increase of 15.4%. The increase in contributions was driven by an increase in the number of foreign tourist arrivals by 12.58%, domestic tourists by 12.37%, and from investment. Therefore it is necessary to study the forecasting of the number of tourists after seeing the great potential generated from the tourism sector. The data forecast is data on the number of tourists in Central Java, both foreign and domestic data. Both data shows the tendency of an upward trend pattern. So that both data can be analyzed using B-DESmethods (Brown's Double Exponential Smoothing) and B-WEMA (Brown's Weighted Exponential Moving Average)that are optimized with LM (Levenberg-Marquardt). Both methods are able to analyze trend patterned data without assumptions making it easier in the analysis process. In addition, the two methods in previous studies were able to produce a small forecasting accuracy. The MAPE (Mean Absolute Percentage Error) value out sample is used to compare the forecasting results of the two methods. The results of the implementation of LM optimization on the data of the number of domestic tourists obtained the optimal parameter value of the B-DES method is 0.21944386 with MAPE out sample 16.26516% and B-WEMA method is 0.219441 with MAPE out sample 16.26515%. While the data on the number of foreign tourists obtained the optimal parameter value of the B-DES method was 0.26213368 with the MAPE out of the sample 23.61278% and the B-WEMA method was 0.26213367 with the MAPE out the sample 23.61278%. This means that both methods have a good level of forecasting accuracy in the data on the number of domestic tourists and an adequate level of accuracy in the data on the number of foreign tourists. Keywords : B-DES, B-WEMA, Levenberg-Marquardt, Tourists in Central Java

scholarly journals Prediction of passenger train using fuzzy time series and percentage change methods

2021 ◽  
Vol 10 (6) ◽  
pp. 3007-3018
Author(s):  
Solikhin Solikhin ◽  
Septia Lutfi ◽  
Purnomo Purnomo ◽  
Hardiwinoto Hardiwinoto
Keyword(s):  
Time Series ◽  
Exponential Smoothing ◽  
Rate Of Change ◽  
Smoothing Method ◽  
Fuzzy Time Series ◽  
Double Exponential ◽  
Passenger Volume ◽  
Double Exponential Smoothing ◽  
Railway Passenger ◽  
Exponential Smoothing Method

In the subject of railway operation, predicting railway passenger volume has always been a hot topic. Accurately forecasting railway passenger volume is the foundation for railway transportation companies to optimize transit efficiency and revenue. The goal of this research is to use a combination of the fuzzy time series approach based on the rate of change algorithm and the Holt double exponential smoothing method to forecast the number of train passengers. In contrast to prior investigations, we focus primarily on determining the next time period in this research. The fuzzy time series is employed as the forecasting basis, the rate of change is used to build the set of universes, and the Holt's double exponential smoothing method is utilized to forecast the following period in this case study. The number of railway passengers predicted for January 2020 is 38199, with a tiny average forecasting error rate of 0.89 percent and a mean square error of 131325. It can also help rail firms identify future passenger needs, which can be used to decide whether to expand train cars or run new trains, as well as how to distribute tickets.

scholarly journals FORECASTING ANORGANIC WASTE VOLUME AFTER THE IMPLEMENTATION OF PLASTIC BAG RESTRICTIONS USING DOUBLE EXPONENTIAL SMOOTHING METHOD AT BOGOR CITY

2020 ◽  
Vol 3 (2) ◽  
pp. 28-31
Author(s):  
Ani Andriyati ◽  
Embay Rohaeti
Keyword(s):  
Linear Trend ◽  
Exponential Smoothing ◽  
Plastic Waste ◽  
Regional Government ◽  
Volume Data ◽  
Classic Problem ◽  
Double Exponential ◽  
Plastic Bag ◽  
Double Exponential Smoothing ◽  
Inorganic Waste

Garbage is a classic problem causing environmental and ecosystem damage in every region, including in Bogor City. Plastic is one of the largest types of inorganic waste that causes ecosystem damage. In one day 1,7 tons of plastic waste are produced from a modern shopping center in Bogor. Several attempts were made to reduce the volume of inorganic waste. Since July 2018 the Regional Government of Bogor City has issued a regulation restricting the use of plastic bags in the modern market as an effort to reduce inorganic waste, especially plastic waste. Forecasting the volume of inorganic waste after the enactment of this regulation is needed as an evaluation step. The double exponential smoothing hole model is suitable for linear data trends. This is in accordance with the condition of inorganic waste volume data which tends to have a linear trend. Forecasting produces parameter parameter values α (level) 0,78 and γ (trend) 0,09 also MAPE 7,25%. The forecast results show that the volume of inorganic waste tends to increase in 2020. In order for this regulation to be optimal, it is necessary to consider applying these regulations not only in the modern market but also in the traditional market. In addition, it is also necessary to find an alternative to substitute for plastic so as not to switch to other inorganic types.

scholarly journals Pengendalian Persediaan Bahan Baku Nalco Water Treatment Dengan Menggunakan Metode Lot Sizing

2019 ◽  
Vol 2 (2) ◽  
pp. 80
Author(s):  
Masad Hariyadi ◽  
Boy Isma Putra
Keyword(s):  
Water Treatment ◽  
Raw Materials ◽  
Unit Cost ◽  
Exponential Smoothing ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Double Exponential ◽  
Double Exponential Smoothing

The limited supply of Nalco raw materials from producers has become a problem for PT ABC, this has led to the control of raw material inventory at PT ABC not including good management, because in the management of raw materials the company still records inventory with manual systems and in ordering raw materials only based on estimates. From the results of the study, the forecasting method used is the Double Exponential Smoothing Holt's, Brown, and Holt Winters Additive Algorithm methods, from the three methods that are most suitable is the Double Exponential Smoothing Brown method with the smallest Mean Square Error of 256.2. Calculation of Sizing Lot by using Economic Order Quantity method, Least Unit Cost method, and Silver Meal method, of the three methods the most optimal is the Economic Order Quantity method because it has the lowest cost of Rp. 12,651,145. The calculation of Safety Stock gets 17 Pail results. and for Reorder Points for Nalco Water Treatment raw material, which is 29 Pail.

scholarly journals Peramalan Kurs IDR Terhadap USD Menggunakan Double Moving Averages Dan Double Exponential Smoothing

2019 ◽  
Vol 2 (2) ◽  
pp. 48-55
Author(s):  
Padrul Jana ◽  
Rokhimi Rokhimi ◽  
Ismi Ratri Prihatiningsih
Keyword(s):  
Exponential Smoothing ◽  
Moving Averages ◽  
Double Exponential ◽  
Double Exponential Smoothing

Kurs IDR terhadap USD yang fluktuatif sangat mempengaruhi ekonomi Indonesia saat ini, dibutuhkan suatu metode untuk meramalkan Kurs IDR terhadap USD agar bisa diprediksi. Diharapkan  para pemangku kepentingan segera mengambil kebijakan strategis demi stabilitas ekonomi nasional. Metode peramalan dalam tulisan ini menggunakan Double Moving Averages dan Double Exponential Smoothing dengan . Hasil peramalan menggunakan metode Double Moving Averages diperoleh IDR/USD, IDR/USD, IDR/USD dan Double Exponential Smoothing diperoleh IDR/USD, IDR/USD, IDR/USD. 14"> Kata Kunci: IDR, USD, Double Moving Averages, Double Exponential Smoothing.

Sign in / Sign up

Export Citation Format

Share Document