scholarly journals Sistem Informasi Persediaan Barang Dengan Metode Weight Moving Average Berbasis Android Di Toko Awd Mranggen

2021 ◽  
Vol 14 (2) ◽  
pp. 208-215
Author(s):  
Zaenal Mustofa Zaenal ◽  
Muhammad Sholikhan ◽  
Bachtiar Aziz Mulki
Keyword(s):  
Average Method ◽  
Moving Average ◽  
Sales Data ◽  
The Future ◽  
Forecasting System ◽  
Period Data

The AWD Mranggen store is a store that is engaged in the sale of bags, belts, shoes with sales developments increasing from year to year, with fairly tight business competition, the AWD Mranggen store must be able to calculate the estimated number of items to be purchased based on previous sales data, the prediction is very influential on the decision to determine the number of items to be provided by the AWD Mranggen Store for the next sales period data. Inventory of goods that are not right cause some losses in terms of time and also costs, it is necessary to have a forecasting system. Forecasting is a technique to identify a model that can be used to predict conditions in the future. By using the weight moving average method, it can be seen that the error value is more than smaller than other methods and the estimated results can be more precise so that it can help owners make decisions in carrying out inventory.

scholarly journals Implementasi Sistem Peramalan Persediaan Barang Menggunakan Metode Moving Average

2020 ◽  
Vol 4 (3) ◽  
pp. 707
Author(s):  
Wulandari Wulandari
Keyword(s):  
Information System ◽  
Data Analysis ◽  
Data Collection ◽  
Average Method ◽  
Moving Average ◽  
Analysis Process ◽  
The Future ◽  
Forecasting System ◽  
System Requirements ◽  
A Company

PT. XYZ is a company engaged in the sale of drugs and vitamins for livestock, each period the number of requests for goods always changes. Problems faced by PT. XYZ, which is expired goods because in a certain period the amount of stock is piling up due to the small amount of demand that causes the company to lose. The purpose of this study is to forecast the inventory process in order to minimize the company's losses against the estimates made so far. In order to minimize these problems, the authors model the forecasting information system for procurement of goods using VB.Net and MYSQL and combine the Moving Average method. The method used is the data collection and processing, and continued with the data analysis process, to model the system requirements of the writer using UML. The final result of this study is that the value of accuracy reaches 88% so that the inventory forecasting system using the moving average method can help managers in making decisions to determine the process of inventory in the future

scholarly journals Future climate changes under different scenarios and their effects on runoff in the upper Taohe River Basin

2021 ◽  
Author(s):  
zhen wang ◽  
Meixue Yang ◽  
xuejia wang ◽  
lizhen cheng ◽  
guoning wan ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
River Basin ◽  
Average Method ◽  
Climate Changes ◽  
Hydrological Model ◽  
Moving Average ◽  
Future Climate ◽  
Annual Average ◽  
The Future

Climate changes may pose challenges to water management. Simulation and projection of climate-runoff processes through hydrological models are essential means to assess the impact of global climate change on runoff variations. This study focuses on the upper Taohe River Basin which is an important water sources for arid and semi-arid regions in Northwest China. In order to assess the impacts of environmental changes, outputs from a regional climate model and the SWAT hydrological model were used to analyze the future climate change scenarios to water resources quantitatively. The examined climate changes scenarios results showed that average annual temperature from 2020 to 2099 in this area exhibits a consistent warming trend with different warming rates, at rates of 0.10°C/10a, 0.20°C /10a and 0.54°C /10a under RCP2.6, RCP4.5 and RCP8.5(Representative Concentration Pathways, RCPs), The value of precipitation experiences different trends under different emission scenarios. Under the RCP2.6, average precipitation would decrease at a rate of 3.69 mm/10a, while under the RCP4.5 and RCP8.5, it would increase at rates of 4.97 mm/10a and 12.28 mm/10a, respectively. The calibration and validation results in three in-site observations (Luqu, Xiabagou and Minxian) in the upper Taohe River Basin showed that SWAT hydrological model is able to produce an acceptable simulation of runoff at monthly time-step. In response to future climate changes, projected runoff change would present different decreasing trends. Under RCP2.6, annual average runoff would experience a progress of fluctuating trend, with a rate of-0.6×108m3 by 5-year moving average method; Under the RCP4.5 and RCP8.5, annual average runoff would show steadily increasing trends, with rates of 0.23×108m3 and 0.16×108m3 by 5-year moving average method. The total runoff in the future would prone to drought and flood disasters. Overall, this research results would provide a scientific reference for reginal water resources management on the long term.

scholarly journals Analysis of Data Mining for Forecasting Total Goods Delivery with Moving Average Method

2017 ◽  
Vol 2 (1) ◽  
pp. 7 ◽  
Author(s):  
M. Azman Maricar ◽  
Putu Widiadnyana ◽  
I Wayan Arta Wijaya
Keyword(s):  
Data Mining ◽  
Average Method ◽  
Mean Absolute Error ◽  
Moving Average ◽  
Absolute Error ◽  
Test Method ◽  
Period Data ◽  
Strong Attachment ◽  
Forecasting Techniques

In the logistics and distribution of goods, the expedition service is necessary, because the expedition is an important part of a business that has a strong attachment to the distribution. The number of deliveries from an expedition per period is uncertain, sometimes the number increases or decreases. This may result in an imbalance between existing facilities and employees and the number of shipments from customers or company policies. To overcome this, required forecasting techniques that are able to predict total shipments, as well as predict which goods and products are the most widely sent. The moving average method using the last 5 period data is used as a way of forecasting. MAPE (Mean Absolute % Error) is used as a test method, and a result of 34 %, indicates that the method is feasible to use.

Menghitung Penjualan Sepeda Motor Domestic Tahun 2019 Menggunakan Metode Simple Moving Average

2020 ◽  
Author(s):  
Rendy Alfianto ◽  
Indah Mustika Sary ◽  
Ade Azhari
Keyword(s):  
Average Method ◽  
Moving Average ◽  
Knowing How ◽  
Know How ◽  
Margin Of Error ◽  
The Future

Knowing how many products are sold in a few months or years is helpful to know if the products sold by the company are experiencing a downturn or decline. In helping to know how many products will be sold in the future can use the Moving Average method, here we want to forecast motorcycle sales with moving average method and get different results with what has been predicted. These different results are commonly referred to as Margin of Error.

Penerapan Metode SMA Untuk Peramalan Tingkat Produksi Tanaman Pangan di Dinas Pertanian

2021 ◽  
Vol 1 (1) ◽  
pp. 27-32
Author(s):  
Novita Sari Sitorus ◽  
Yessica Siagian ◽  
Romy Aulia
Keyword(s):  
Production Rate ◽  
Average Method ◽  
Crop Production ◽  
Moving Average ◽  
Visual Basic ◽  
Food Crops ◽  
Food Crop ◽  
Forecasting System ◽  
Food Crop Production

Abstract: Food is the most important foodstuff needed by humans, in addition to consumption, the production of food crops can also be used as a source of business in the economy. This study aims to predict the production of food crops in the Agriculture Office of Asahan Regency. Based on data on food crop production from 2012 to 2019 at the Asahan District Agriculture Office experienced ups and downs, food crop production sometimes does not meet the consumption of people in Asahan Regency (devisit) and sometimes overproduction (surplus). So far, the Agriculture Office of Asahan Regency has predicted the production of food crops only with estimates so that the results are not accurate. Based on these problems, a proper forecasting system is needed so that it is able to predict the production rate of food crops quickly and accurately. Applications are built using Visual Basic Net 2010 and MySQL databases and use the Single Moving Average method. The results of this study can help the Agriculture Office of Asahan Regency in predicting the amount of food crop production in the next period according to the needs. Keywords : Forecasting, Production, Food Crops, Single Moving Average  Abstrak: Pangan merupakan bahan makanan paling utama yang di butuhkan oleh manusia, selain untuk dikomsumsi, hasil produksi dari tanamana pangan juga dapat dijadikan sebagai sumber usaha dalam perekonomian. Penelitian ini bertujuan untuk melakukan prediksi produksi tanaman pangan pada Dinas Pertanian Kabupaten Asahan. Berdasarkan data produksi tanaman pangan dari tahun 2012 sampai dengan tahun 2019 pada Dinas Pertanian Kabupaten Asahan mengalami naik turun, produksi tanaman pangan terkadang tidak memenuhi konsumsi masyarakat di Kabupaten Asahan (devisit) dan terkadang kelebihan produksi (surplus). Selama ini Dinas Pertanian Kabupaten Asahan melakukan prediksi produksi tanaman pangan hanya dengan perkiraaan-perkiraan saja sehingga hasilnya tidak akurat. Berdasarkan permasalahan tersebut maka dibutuhkan sistem peramalan yang tepat sehingga mampu meramalkan tingkat produksi tanaman pangan dengan cepat dan akurat. Aplikasi dibangun menggunakan Visual Basic Net 2010 dan database MySQL serta menggunakan metode Single Moving Average. Hasil dari penelitian ini dapat membantu Dinas Pertanian Kabupaten Asahan dalam memprediksi jumlah produksi tanaman pangan pada periode berikutnya sesuai dengan kebutuhan. Kata Kunci : Peramalan, Produksi, Tanaman Pangan, Single Moving Average

scholarly journals Perbandingan Metode Moving Average dan Metode Naïve Dalam Peramalan Data Kemiskinan

2019 ◽  
Vol 3 (1) ◽  
pp. 65
Author(s):  
Ais Kumila ◽  
Baqiyatus Sholihah ◽  
Evizia Evizia ◽  
Nur Safitri ◽  
Safama Fitri
Keyword(s):  
Average Method ◽  
Moving Average ◽  
Naive Method ◽  
Forecasting System ◽  
Simulation Results

Abstrak: Penelitian ini bertujuan untuk memprediksi metode terbaik pada sistem peramalan dengan menggunakan metode Moving Average (SMA, WMA, dan EMA) dan metode Naive. Pada tahap simulasi, kami menggunakan data jumlah kemiskinan penduduk Provinsi Nusa Tenggara Barat (NTB) tahun 2002-2018 untuk memprediksi data tahun 2019. Adapun, model dievaluasi untuk melihat tingkat akurasi masing-masing metode berdasarkan nilai MAD, MSE, RMSE dan MAPE. Berdasarkan hasil simulasi data dari metode-metode yang diuji, diketahui bahwa metode Naive paling akurat dengan hasil prediksi tahun 2019 sebesar 737.460 dengan MAD, MSE, RMSE dan MAPE berturut-turut sebesar 41.427,188; 2.711.468.146; 52.071,760; dan 0.043. Abstract: This study aims to predict the best method on the forecasting system using the Moving Average method (SMA, WMA, and EMA) and the Naive method. In the simulation phase, we used data on the Number of Poverty of the Population of West Nusa Tenggara (NTB) in 2002-2018 to predict the Poverty of Population of the Province of West Nusa Tenggara (NTB) in 2019. Meanwhile, the model was evaluated to see the accuracy of each method based on the value MAD, MSE, RMSE and MAPE. Based on the simulation results of the data from the methods tested, it can be seen that the Naive method is most accurate with the results of the 2019 prediction of 737,460 with MAD, MSE, RMSE and MAPE in the amount of 41.427,188; 2.711.468.146; 52.071,760; and 0.043.

scholarly journals A statistical study of COVID-19 pandemic in Egypt

2021 ◽  
Vol 54 (1) ◽  
pp. 233-244
Author(s):  
Taha Radwan
Keyword(s):  
Linear Relationship ◽  
Statistical Study ◽  
Moving Average ◽  
Arima Model ◽  
Decision Makers ◽  
Accurate Data ◽  
Autoregressive Integrated Moving Average ◽  
The World ◽  
The Future

Abstract The spread of the COVID-19 started in Wuhan on December 31, 2019, and a powerful outbreak of the disease occurred there. According to the latest data, more than 165 million cases of COVID-19 infection have been detected in the world (last update May 19, 2021). In this paper, we propose a statistical study of COVID-19 pandemic in Egypt. This study will help us to understand and study the evolution of this pandemic. Moreover, documenting of accurate data and taken policies in Egypt can help other countries to deal with this epidemic, and it will also be useful in the event that other similar viruses emerge in the future. We will apply a widely used model in order to predict the number of COVID-19 cases in the coming period, which is the autoregressive integrated moving average (ARIMA) model. This model depicts the present behaviour of variables through linear relationship with their past values. The expected results will enable us to provide appropriate advice to decision-makers in Egypt on how to deal with this epidemic.

scholarly journals Pemisahan Anomali Regional-Residual pada Metode Gravitasi Menggunakan Metode Moving Average, Polynomial dan Inversion

2016 ◽  
Vol 3 (01) ◽  
pp. 10 ◽  
Author(s):  
Jarot Purnomo ◽  
Sorja Koesuma ◽  
Mohtar Yunianto
Keyword(s):  
Average Method ◽  
Moving Average ◽  
Continuation Method ◽  
Inversion Method ◽  
Polynomial Method ◽  
Minimum Error ◽  
Gravity Method ◽  
Upward Continuation ◽  
And Inversion ◽  
Separation Results

<span>It has been done a research about separation of regional-residual anomaly in Gravity method. <span>This research compares the result of three methods i.e. moving average method, polynomial <span>method, and inversion method. The computer program is created using a computer programming <span>Matlab 7. From three methods that have been made, the separation results are compared with<br /><span>results of separation by using Upward Continuation method. From the results of these <span>comparisons will be available an excellent program of regional-residual anomali separation. The <span>results show that in polynomial method of the order 4 obtained similar contour to the separation <span>by Upward Continuation Software. So that the output of this separation will be treated again <span>with Grav2DC software. The output of this software is the density of rock Grav2DC of the study<br /><span>area. Processing results obtained the minimum error of 1.85% for the separation by polynomial <span>method, while for the method of Upward Continuation obtained minimum error of 2.22%. The <span>results obtained show that the separation of regional-residual anomali by polynomial method is <span>similar to separation by Upward Continuation method.</span></span></span></span></span></span></span></span></span></span></span></span><br /></span>

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