2021 ◽  
Vol 8 (2) ◽  
pp. 75-81
Saefudin ◽  
Diki Susandi ◽  
Fairuza Nafis

Abstrak - Teknologi informasi sudah menjadi kebutuhan dalam kehidupan masyarakat saat ini, karena sistem dan teknologi informasi dapat membantu dalam pengambilan keputusan yang efektif dan efisien. Saat ini Inti Jaya Block membutuhkan suatu sistem yang terkomputerisasi untuk membantu dalam mengambil keputusan, karena kendala yang sering terjadi yaitu masih kesulitan dalam menentukan jumlah produksi untuk periode mendatang. Tujuan dari penelitian ini adalah membuat sistem peramalan penjualan menggunakan metode single moving average. Metode single moving average ini  digunakan untuk melakukan peramalaman dalam menentukan berapa jumlah produksi yang harus disediakan pada periode mendatang. Sistem Peramalan ini dibuat dengan menggunakan metode pengembangan sistem Waterfall Model, perancangan sistemnya menggunkaan UML dan bahasa pemrograman PHP dan database MySQL. Hasil peramalan yang telah dilakukan, didapat nilai kesalahan terkecil yang berbeda tiap periode pada setiap barang. Nilai kesalahan terkecil untuk Paving Block Tipe Bata menggunakan 6 periode, dengan nilai MAD sebesar 437,037, MSE sebesar 262708, dan MAPE sebesar 3,76935% dan untuk tipe hexagon menggunakan 6 periode diperoleh nilai penjualan1980 dengan nilai MAD 125, MSE 24986,3 dan MAPE 6,32166%.   Kata Kunci : Sistem Peramalan, Penjualan, Peramalan, Single Moving Average. Waterfall

2018 ◽  
Vol 1 (3) ◽  
pp. 120
Gede Aditra Pradnyana ◽  
I Made Arisetiawan Sunarya ◽  
Dewa Gede Hendra Divayana

A pharmacy is a place of health service but indirectly also an effort to get the benefit. From the business point of view, of course, the pharmacy requires a system of processing inventory of goods, especially drugs - drugs in order to avoid losses. One of the pharmacies that have not optimally utilized the technology is at Apotek Karunia Asih located in Canggu Badung Bali. To overcome the problem of inventory control, at Apotek Karunia Asih requires inventory control application. The purpose of this research is to develop inventory control application with hybrid periodic order quantity - moving average method in Apotek Karunia Asih which gives benefit to the controlling of goods in pharmacies so that the goods and drugs sold in another are no longer past the expiration date, dead stock, stacking or stock shortages. Development of inventory control application with hybrid periodic order quantity - moving average method in Apotek Karunia Asih uses SDLC (Software Development Life Cycle) process to describe the stages in software development. SDLC process used is waterfall model. Waterfall model is a model that is systematic and sequential in building software, starting from the analysis, design, coding, testing, and support or maintenance. Implementation of this research is applied by using PHP programming language with the help of Codeigniter framework. For the testing process, five (5) test process stages are performed: (1) white box test which states that the source code implementation is appropriate and there is no error, (2) black box test to find out whether all software functional is appropriate, (3) test the suitability of the system to find out the correctness of the calculation process performed by the application, (4) the user response test which states the application and the methods used are very appropriate in controlling the supply of drugs in pharmacies; (5) the previous training test on forecasting that the previous training score will be used to predict the need is 6 because it has the smallest MAPE and MSE so that the forecasting results can be in accordance with the actual data.

2020 ◽  
Vol 3 (3) ◽  
pp. 239-246
Mustofa Ahyar ◽  
Yudhiakto Pramudya ◽  
Okimustava Okimustava

Polusi cahaya sangat berpengaruh terhadap kecerahan langit. Tingkat kecerahan langit dapat diukur dengan Sky Quality Meter (SQM). Hasil data SQM sangat banyak, perlu aplikasi untuk mempermudah pengolahan datanya. Fitur Visual Basic Microsoft Excel dapat membantu pengolahan data SQM. Penelitian menggunakan metode observasi tingkat kecerahan langit dengan SQM. Analisis data menggunakan metode moving average. Pengembangan perangkat lunak menggunakan model waterfall dengan lima tahapan permodelan, yaitu: analisis, desain, implementasi, pengujian, dan perawatan. Model pengembangan waterfall mampu untuk membuat sistem pengolahan data SQM, data dengan berbagai kolom dapat dipilih secara otomatis dan cepat sehingga dapat dibuat grafik tingkat kecerahan langit terhadap waktu.Light pollution dramatically affects the brightness of the sky. Sky brightness level can be measured using Sky Quality Meter (SQM). SQM data results are huge data. It needs an application to facilitate data processing. Microsoft Excel Visual Basic features can assist the SQM data processing. The study used observational methods of sky brightness with SQM. Data analysis using the moving average method. Software development used the waterfall model with five stages of modeling, namely: analysis, design, implementation, testing, and maintenance. The waterfall development model was able to create an SQM data processing system. The data with various columns can be selected automatically and quickly. Hence, it is able to graph the level of sky brightness versus time.

2019 ◽  
Vol 9 (2) ◽  
pp. 244
Rizal Bakri ◽  
Umar Data ◽  
Niken Probondani Astuti

Business analytics plays an important role in optimizing the management of product marketing strategies. One of the most popular analytical tools in business analytics is sales forecasting. Businesses need to conduct sales forecasting to optimize marketing management in the form of product availability predictions, predictions of capital adequacy, consumer interest, and product price governance. However, the problem that is often encountered in forecasting is the number of forecasting methods available so that it makes it difficult for business people to choose the best forecasting method. The aims of this research is to develop a forecasting software tha can be accessed online based on computational intelligence, which is a software that can make forececasting with various methods and then intelligently choose the best forecasting method. The software development method used in this study is the SDLC with waterfall model. The result of this research is the Auto sales forecasting software was developed using the R programming language by combining various package and can be accessed online through the page Http:// This software can be used to conduct forecast analysis with various methods such as Simple Moving Average, Robust Exponential Smoothing, Auto ARIMA, Artificial Neural Network, Holt-Winters, and Hybrid Forecast. This software contains intelligence computing to choose the best forecasting method based on the smallest RMSE value. After testing the sales transaction data at the Futry Bakery & Cake Shop in Makassar, the results show that the Robust Exponantial Smoothing method is the best forecasting method with an RMSE value of 0.829

1982 ◽  
Vol 14 (3) ◽  
pp. 156-166 ◽  
Chin-Sheng Alan Kang ◽  
David D. Bedworth ◽  
Dwayne A. Rollier

2000 ◽  
Vol 14 (1) ◽  
pp. 1-10 ◽  
Joni Kettunen ◽  
Niklas Ravaja ◽  
Liisa Keltikangas-Järvinen

Abstract We examined the use of smoothing to enhance the detection of response coupling from the activity of different response systems. Three different types of moving average smoothers were applied to both simulated interbeat interval (IBI) and electrodermal activity (EDA) time series and to empirical IBI, EDA, and facial electromyography time series. The results indicated that progressive smoothing increased the efficiency of the detection of response coupling but did not increase the probability of Type I error. The power of the smoothing methods depended on the response characteristics. The benefits and use of the smoothing methods to extract information from psychophysiological time series are discussed.

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Dusan Marcek

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

TAPPI Journal ◽  
2015 ◽  
Vol 14 (6) ◽  
pp. 395-402

Alkali charge is one of the most relevant variables in the continuous kraft cooking process. The white liquor mass flow rate can be determined by analyzing the chip bulk density fed to the process. At the mills, the total time for this analysis usually is greater than the residence time in the digester. This can lead to an increasing error in the mass of white liquor added relative to the specified alkali charge. This paper proposes a new approach using the Box-Jenkins methodology to develop a dynamic model for predicting chip bulk density. Industrial data were gathered on 1948 observations over a period of 12 months from a Kamyr continuous digester at a bleached eucalyptus kraft pulp mill in Brazil. Autoregressive integrated moving average (ARIMA) models were evaluated according to different statistical decision criteria, leading to the choice of ARIMA (2,0,2) as the best forecasting model, which was validated against a new dataset gathered during 2 months of operations. A combination of predictors has shown more accurate results compared to those obtained by laboratory analysis, allowing a reduction of around 25% of the chip bulk density error to the alkali addition amount.

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