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Türkiye'deki Kayısı Üreticilerine Zaman Serileri Analizine Bağlı Ekonomik Bir Tavsiye

Year 2022, Volume: 9 Issue: 1, 19 - 25, 22.01.2022
https://doi.org/10.30910/turkjans.1001035

Abstract

Bu çalışmada, Türkiye’ de bulunan kayısı üreticileri için makine ve iş gücü maliyetlerinin ekonomik olarak karşılaştırması yapılmış ve buna bağlı olarak üreticilere ekonomik tavsiye oluşturulmuştur. Türkiye İstatistik Kurumu (TÜİK) 2005-2020 yılları arası ekonomik verileri kullanılarak zaman serisi analizleri başarılı bir şekilde gerçekleştirilmiştir. Zaman serisinde Quadratic ve Exponantial Growth metodları uygulanarak 2020-2024 yılları arası trend tahminleri gerçekleştirilmiştir. Trend tahminleri mevsimlik işçilerin yıl bazında alacakları ücretler ve enflasyon verileri için uygulanmıştır. Enflasyon verilerine bağlı olarak makine fiyatları 2024 yılına kadar hesaplanmıştır. Tahmin verileri kapsamında elde edilen sonuçlara göre sadece makine kullanımı, makine + işgücü ve sadece işgücü maliyetleri karşılaştırmaları yapılmıştır. Bu karşılaştırma sonucunda üreticinin makine alımına ayıracağı sermayeyi 1 yıllık işçi ücreti ile amorti edebileceği ve bu vesile ile bir ömür kullanılacak makine alımını gerçekleştireceği ortaya çıkmaktadır. Ayrıca makine + işgücü kullanımı ile makineye ayrılan sermaye 2 yıl içinde karşılanabilmektedir. Bu durum basit makine gücünün kullanımı ile özellikle Covid-19 sürecinde Türkiye çapında tüm kayısı üreticilerinin hem sağlık hem maddi hem de zaman açısından kar etmesini sağlayabileceğini göstermektedir.

References

  • Abid, S., Raza, I., Khalil, A., Khan, M.N., Anwar, S., Masood M.A. 2014. Trend Analysis and Forecasting of Maize Area and Production in Khyber Pakhtunkhwa, Pakistan. European Academic Research, 2: 4653-4664.
  • Adamuthe, A.C., Gage, R.A., Thampi, G.T. 2015. Forecasting Cloud Computing using Double Exponential Smoothing Methods. International Conference on Advanced Computing and Communication Systems, Doi: 10.1109/ICACCS.2015.7324108
  • Aday, S., Aday, M.S. 2020. Impact of COVID-19 on the food supply chain. Food Quality and Safety, 4: 167–180.
  • TUIK, 2021. TUİK verileri, Türkiye’de yetiştirilen ağaç başına kayısı verim miktarı. “https://biruni.tuik.gov.tr/medas/?kn=92&%20locale=tr” (Access date: 15.09.2021).
  • Capa, 2021. 7 hp capa makinesi. “https://www.tarimmakinamarket.com/” (Access date: 15.09.2021).
  • Celik, S. 2020. Estimation Modelling of The Amount of Fodder Beet Production In Turkey: Comparative Analysis Of Artificial Neural Networks And Trend Analysis Methods. Journal Of Multidisciplinary Engineering Science Studies, 6: 3372-3375.
  • Costamagna, A.C., Werf, W.V.D., Bianchi, F.J.J.A., Landis, D.A. 2007. An exponential growth model with decreasing r captures bottom-up effects on the population growth of Aphis glycines Matsumura (Hemiptera: Aphididae). Agricultural and Forest Entomology, 9: 297.
  • Ercisli, S. 2009. Apricot culture in Turkey. Scientific Research and Essays, 4: 715-719.
  • Gezer, I., Dikilitas, S. 2002. The study of work process and determination of some working parameters in an apricot pit processing plant in Turkey. Journal of Food Engineering, 53: 111-114.
  • Kadmec, 2021. “https://www.kadmec.com/tarim-makinalari/meyve-zeytin-hasat-makinalari-ve-aletleri/agac-sallama-makinalari” (Access date 15.09.2021)
  • Kaplan, M. 2019. Determining The Criterion and Biotechnical Struggle Methods Against Forficula Auricularia L. (Dermaptera: Forficulidae) Harming in Apricot Orchards in Turkey. Fresenius Environmental Bulletin, 28: 6701-6706.
  • Khair, U., Fahmi, H., Hakim, S.A. and Rahim, R. 2017. Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error. Journal of Physics: Conference Series, 930: 012002.
  • Khan, F., Husain, T., and Lumb, A. 2003. Water Quality Evaluation and Trend Analysis in Selected Watersheds of the Atlantic Region of Canada. Environmental Monitoring and Assessment, 88: 221.
  • Konarasinghe, K.M.U.B. 2016. Forecasting Tourist Arrivals to Sri Lanka: Post-War Period. International Journal of Novel Research in Physics Chemistry & Mathematics. 3: 57-63.
  • McKenzie, J. 2011. Mean absolute percentage error and bias in economic forecasting. Economics Letters,113: 259.
  • Sanli, N. 2018. Türkiyenin Jeopolitik Önemini Kavratmada Coğrafya Dersinin Etkisinin Öğretmen Görüşleri İle Değerlendirilmesi. MSc, Necmettin Erbakan University Institute of Education Sciences, Konya, Turkey.
  • Turkey 2021. “https://www.britannica.com/place/Turkey” (Access date 15.09.2021)
  • Unal MR (2010). Kayisi Araştirma Raporu. https://fka.gov.tr/sharepoint/userfiles/Icerik_Dosya_Ekleri/FKA_ARASTIRMA_RAPORLARI/FKA%20KAYISI%20ARA%C5%9ETIRMA%20RAPORU.pdf (Access date 15.09.2021)

An Economic Advice to Apricot Producers in Turkey, Depend on Time Series Analysis

Year 2022, Volume: 9 Issue: 1, 19 - 25, 22.01.2022
https://doi.org/10.30910/turkjans.1001035

Abstract

In this study, an economic comparison has been made of machine power and labor costs for apricot producers in Turkey. Based on the results of these comparisons, economic advice has been created for producers. The time series analysis was successfully applied using the economic data of the Turkish Statistical Institute (TurkStat) between the years 2005-2020. The possible trend values forecasts for the years 2020-2024 were made by applying Quadratic and Exponential Growth methods in time series analysis. Trend forecasts were applied for seasonal workers' annual wages and inflation data. Machine prices have been calculated until 2024, based on inflation forecast data. According to the results obtained, only machine power use, machine power + labor and only labor costs were compared. As a result of this comparison, it has been determined that the apricot producers can amortize the machine costs with a 1-year workers’ wages. Moreover, they will be able to have the machines to be used for a lifetime. In addition, the capital allocated for the purchase of machinery can be met within 2 years with the use of machinery power + labor force. This situation shows that with the use of simple machine power, especially during the Covid-19 pandemics, all apricot producers across Turkey can make a profit in terms of health, financially and time.

References

  • Abid, S., Raza, I., Khalil, A., Khan, M.N., Anwar, S., Masood M.A. 2014. Trend Analysis and Forecasting of Maize Area and Production in Khyber Pakhtunkhwa, Pakistan. European Academic Research, 2: 4653-4664.
  • Adamuthe, A.C., Gage, R.A., Thampi, G.T. 2015. Forecasting Cloud Computing using Double Exponential Smoothing Methods. International Conference on Advanced Computing and Communication Systems, Doi: 10.1109/ICACCS.2015.7324108
  • Aday, S., Aday, M.S. 2020. Impact of COVID-19 on the food supply chain. Food Quality and Safety, 4: 167–180.
  • TUIK, 2021. TUİK verileri, Türkiye’de yetiştirilen ağaç başına kayısı verim miktarı. “https://biruni.tuik.gov.tr/medas/?kn=92&%20locale=tr” (Access date: 15.09.2021).
  • Capa, 2021. 7 hp capa makinesi. “https://www.tarimmakinamarket.com/” (Access date: 15.09.2021).
  • Celik, S. 2020. Estimation Modelling of The Amount of Fodder Beet Production In Turkey: Comparative Analysis Of Artificial Neural Networks And Trend Analysis Methods. Journal Of Multidisciplinary Engineering Science Studies, 6: 3372-3375.
  • Costamagna, A.C., Werf, W.V.D., Bianchi, F.J.J.A., Landis, D.A. 2007. An exponential growth model with decreasing r captures bottom-up effects on the population growth of Aphis glycines Matsumura (Hemiptera: Aphididae). Agricultural and Forest Entomology, 9: 297.
  • Ercisli, S. 2009. Apricot culture in Turkey. Scientific Research and Essays, 4: 715-719.
  • Gezer, I., Dikilitas, S. 2002. The study of work process and determination of some working parameters in an apricot pit processing plant in Turkey. Journal of Food Engineering, 53: 111-114.
  • Kadmec, 2021. “https://www.kadmec.com/tarim-makinalari/meyve-zeytin-hasat-makinalari-ve-aletleri/agac-sallama-makinalari” (Access date 15.09.2021)
  • Kaplan, M. 2019. Determining The Criterion and Biotechnical Struggle Methods Against Forficula Auricularia L. (Dermaptera: Forficulidae) Harming in Apricot Orchards in Turkey. Fresenius Environmental Bulletin, 28: 6701-6706.
  • Khair, U., Fahmi, H., Hakim, S.A. and Rahim, R. 2017. Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error. Journal of Physics: Conference Series, 930: 012002.
  • Khan, F., Husain, T., and Lumb, A. 2003. Water Quality Evaluation and Trend Analysis in Selected Watersheds of the Atlantic Region of Canada. Environmental Monitoring and Assessment, 88: 221.
  • Konarasinghe, K.M.U.B. 2016. Forecasting Tourist Arrivals to Sri Lanka: Post-War Period. International Journal of Novel Research in Physics Chemistry & Mathematics. 3: 57-63.
  • McKenzie, J. 2011. Mean absolute percentage error and bias in economic forecasting. Economics Letters,113: 259.
  • Sanli, N. 2018. Türkiyenin Jeopolitik Önemini Kavratmada Coğrafya Dersinin Etkisinin Öğretmen Görüşleri İle Değerlendirilmesi. MSc, Necmettin Erbakan University Institute of Education Sciences, Konya, Turkey.
  • Turkey 2021. “https://www.britannica.com/place/Turkey” (Access date 15.09.2021)
  • Unal MR (2010). Kayisi Araştirma Raporu. https://fka.gov.tr/sharepoint/userfiles/Icerik_Dosya_Ekleri/FKA_ARASTIRMA_RAPORLARI/FKA%20KAYISI%20ARA%C5%9ETIRMA%20RAPORU.pdf (Access date 15.09.2021)
There are 18 citations in total.

Details

Primary Language Turkish
Journal Section Research Articles
Authors

Ayça Nur Şahin Demirel 0000-0003-2988-8448

Publication Date January 22, 2022
Submission Date September 26, 2021
Published in Issue Year 2022 Volume: 9 Issue: 1

Cite

APA Şahin Demirel, A. N. (2022). Türkiye’deki Kayısı Üreticilerine Zaman Serileri Analizine Bağlı Ekonomik Bir Tavsiye. Türk Tarım Ve Doğa Bilimleri Dergisi, 9(1), 19-25. https://doi.org/10.30910/turkjans.1001035