Building The Prediction of Sales Evaluation on Exponential Smoothing using The OutSystems Platform


Sasa Ani Arnomo(1*); Yulia Yulia(2); Ukas Ukas(3);

(1) Universitas Putera Batam
(2) STIE Nagoya Indonesia
(3) Universitas Putera Batam
(*) Corresponding Author

  

Abstract


To get a large profit in a company or business is to determine sales predictions for the next period. Prediction or forecasting is one of the keys to the success of sales because the predicted value of sales can be used as a reference to determine the order of goods, so there is no loss. Exponential smoothing method is a fairly superior forecasting method in long-term, medium-term and short-term forecasting. The data to be processed is sales data for the 2020-2022 period. The single exponential smoothing method was chosen because it can determine sales predictions for the next period with the smallest error value. The evaluation method used is MAPE, ME, MAD and MSE where this forecasting method is used to find the smallest error value. Based on the calculation results, the smallest error value obtained is ME at 62.8, MAD at 179.9, MSE at 55564.5, and MAPE at 9.20%. The value is at alpha 0.3. The next stage is to design a prediction system using the out-systems platform version 11.14.1 as a place to design the system. The test results of the system that has been designed to assist business owners in making decisions on product inventory estimates.

Keywords


Evaluation; Exponential Smoothing; Forecasting; Prediction; Sales

  
  

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doi  https://doi.org/10.33096/ilkom.v15i2.1529.222-228 		  

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S. A. Arnomo and Y. Yulia, “Clustering the potential bandwidth upgrade of FTTH broadband subscribers,” Ilk. J. Ilm., vol. 13, no. 1, pp. 51–57, 2021.

A. W. Saputra, A. P. Wibawa, U. Pujianto, and ..., “LSTM-based Multivariate Time-Series Analysis: A Case of Journal Visitors Forecasting,” Ilk. J. …, vol. 14, no. 1, pp. 57–62, 2022.

S. Panggabean, P. R. Sihombing, and ..., “Simulasi Exponential Moving Avarage dan Single Exponential Smoothing: Sebuah Perbandingan Akurasi Metode Peramalan,” J. Pemikir. dan Penelit. Pendidik. Mat., vol. 4, no. 1, pp. 1–10, 2021.

A. Picu and T. Spyropoulos, “DTN-Meteo: Forecasting the performance of DTN protocols under heterogeneous mobility,” IEEE/ACM Trans. Netw., vol. 23, no. 2, pp. 587–602, 2015.

A. Werth, N. Kitamura, and K. Tanaka, “Conceptual Study for Open Energy Systems: Distributed Energy Network Using Interconnected DC Nanogrids,” IEEE Trans. Smart Grid, vol. 6, no. 4, pp. 1621–1630, 2015.

Muladi, S. A. Siregar, and A. P. Wibawa, “Double Exponential-Smoothing Neural Network for Foreign Exchange Rate Forecasting,” Proc. - 2nd East Indones. Conf. Comput. Inf. Technol. Internet Things Ind. EIConCIT 2018, pp. 118–122, 2018.

S. A. Arnomo, Nopriadi, R. Harman, and Yulia, “Model Importance Performance Analysis Dan Webqual Untuk Evaluasi Website,” J. Desain Dan Anal. Teknol., vol. 1, no. 1, pp. 36–44, 2022.

S. Juriah, “Peramalan (Forecasting) Volume Penjualan Sepatu,” JUDICIOUS J. Manag., vol. 2, no. 2, pp. 134–137, 2021.

E. Balouji, O. Salor, and M. Ermis, “Exponential Smoothing of Multiple Reference Frame Components with GPUs for Real-Time Detection of Time-Varying Harmonics and Interharmonics of EAF Currents,” IEEE Trans. Ind. Appl., vol. 54, no. 6, pp. 6566–6575, 2018.

Nugroho Arif Sudibyo, Ardymulya Iswardani, Arif Wicaksono Septyanto, and Tyan Ganang Wicaksono, “Prediksi Inflasi Di Indonesia Menggunakan Metode Moving Average, Single Exponential Smoothing Dan Double Exponential Smoothing,” J. Lebesgue J. Ilm. Pendidik. Mat. Mat. dan Stat., vol. 1, no. 2, pp. 123–129, 2020.

F. Sidqi and I. D. Sumitra, “Forecasting Product Selling Using Single Exponential Smoothing and Double Exponential Smoothing Methods,” IOP Conf. Ser. Mater. Sci. Eng., vol. 662, no. 3, 2019.

R. Rachmat and S. Suhartono, “Comparative Analysis of Single Exponential Smoothing and Holt’s Method for Quality of Hospital Services Forecasting in General Hospital,” Bull. Comput. Sci. Electr. Eng., vol. 1, no. 2, pp. 80–86, 2020.

R. P. Kristianto and A. Setyanto, “Golden section search-multi variable algorithm for optimization parameter of triple exponential smoothing algorithm to predict sufferers of lungs disease,” Proc. - 2018 3rd Int. Conf. Inf. Technol. Inf. Syst. Electr. Eng. ICITISEE 2018, pp. 194–198, 2018.

R. Gustriansyah, N. Suhandi, F. Antony, and A. Sanmorino, “Single exponential smoothing method to predict sales multiple products,” J. Phys. Conf. Ser., vol. 1175, no. 1, 2019.

S. Fachrurrazi, “Peramalan Penjualan Obat Menggunakan Metode Single Exponential Smoothing Pada Toko Obat Bintang Geurugok,” Techsi, vol. 6, no. 1, pp. 19–30, 2015.

K. D. Hartomo, S. Yulianto, and J. Maruf, “Spatial model design of landslide vulnerability early detection with exponential smoothing method using google API,” Proc. - 2017 Int. Conf. Soft Comput. Intell. Syst. Inf. Technol. Build. Intell. Through IOT Big Data, ICSIIT 2017, vol. 2018-Janua, pp. 102–106, 2017.

Chusyairi Ahmad, Ramadar N.S. Pelsri, and Bagio, “The Use of Exponential Smoothing Method to Predict Missing Service E-Report 2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE) : proceedings : 1-2 November 2017, Yogyakarta, Indonesia,” in International Conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE), 2017, pp. 39–44.

R. Martins, F. Caldeira, F. Sa, M. Abbasi, and P. Martins, “An overview on how to develop a low-code application using OutSystems,” Proc. Int. Conf. Smart Technol. Comput. Electr. Electron. ICSTCEE 2020, pp. 395–401, 2020.

Harliana and Hartatik, “Optimizing Single Exponential Smoothing Method by Using Genetic Algorithm for Object Selling Prediction,” in International Conference on Information and Communications Technology (ICOIACT), 2020, pp. 77–82.


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