Skip to main content Skip to main navigation menu Skip to site footer
Articles
Published: 2020-12-30

Peramalan Penjualan Kendaraan Mobil Segmen B2B dengan Metode Regresi Linear Berganda, Jaringan Saraf Tiruan dan Jaringan Saraf Tiruan – Algoritma Genetika

Artificial Neural Networks Automotive Industry Forecasting Genetic Algorithms Multiple Linear Regression

Abstract

This study aims to create an effective forecasting model in predicting sales of car products in the B2B segment (Business to Business) to obtain estimates of product sales in the future. This research uses multiple linear regression and artificial neural networks that are optimized by genetic algorithms. Forecasting factors for car sales are generally issued by total national car sales, the Consumer Price Index, the Consumer Confidence Index, the Inflation Rate, Gross Domestic Product (GDP), and Fuel Oil Price. The author has also gotten the factors that play a role in the sale of B2B segment by diverting the survey to 106 DMU (Decision Making Unit) who decide to purchase cars in their company. Then we evaluate the results of the questionnaire in training data and simulations on the Artificial Neural Network. Optimized Artificial Neural Networks with Genetic Algorithms can improve B2B segment car sales' accuracy when comparing error values in the ordinary Artificial Neural Network and Multiple Linear Regression.

References

  1. Brax, S. A., and Visintin, F. (2017). Meta-Model of Servitization: The Itegrative Profiling Approach. Industrial Marketing Management, 60, pp. 17-32.
  2. Caruana, A. (2001). Steps in Forecasting with Seasonal Regression: A Case Study from the Carbonated Soft Drink Market. Journal of Product & Brand Management, 10, pp. 94-102.
  3. Chouksey, P., Deshpande, A., Agarwal, P., Gupta , D. R. (2018). Sales Forecasting Study in An Automobile Company: A Case Study. Industrial Engineering Journal, 10(12).
  4. Cristiana, M. (2009). The Buying Decision Process and Types of Buying Decision Behaviour. Sibiu Alma Mater University Journals. Series A. Economic Sciences, 2(4).
  5. Draper, N. R. and Smith H. (1992) Applied Regression Analysis. Canada: John Wiley & Sons.
  6. Gao, J., Xie, Y., Cui, X., Yu, H., and Gu, F. (2018). Chinese Automobile Sales Forecasting using Economic Indicators and Typical Domestic Brand Automobile Sales Data: A Method Based on Econometric Model. Advances in Mechanical Engineering, 10(2), pp. 1-11.
  7. Jennie, B., Elina, L., & Linda-Marie, W. (2005 ). What Influences B2B Buying Behaviour?: An Empirical Study of Fläkt Woods and Its Customers. Bachelor’s Thesis in Marketing.
  8. Keller, K. L. (1993). Conceptualizing, Measuring, and Managing Customer Based Brand Equity. Journal of Marketing, 12(1).
  9. Keshvari, R.S. (2012). The Impact of B2B Buying Behavior on Customer Satisfaction within SHAHAB KHODRO Company. International Journal of Business and Management, 7(7).
  10. Lihua, Y. and Baolin, L. (2016), The Combination Forecasting Model of Auto Sales Based on Seasonal Index and RBF Neural Network. International Journal of Database Theory and Application, 9(1), pp.67-76.
  11. Makridarkis, S., Wheelwright, S. C., and McGee, V. E (Terjemahan). (1999). Metode dan Aplikasi Peramalan Edisi 2. Jakarta : Binarupa Aksara
  12. Ravi, P., Quester, P.G., and Cooksey, R. W. (2006). Consumer-Based Brand Equity and Country-of-Origin Relationships: Some Empirical Evidence. European Journal of Marketing, 40(5/6).

How to Cite

Nugraha, M. A., Farizal, F., & Gabriel, D. S. (2020). Peramalan Penjualan Kendaraan Mobil Segmen B2B dengan Metode Regresi Linear Berganda, Jaringan Saraf Tiruan dan Jaringan Saraf Tiruan – Algoritma Genetika. EIGEN MATHEMATICS JOURNAL, 3(2), 83–89. https://doi.org/10.29303/emj.v3i2.80