Using Bigdata for Choosing the Right Forecasting Method, Dataset and Period in a Time Series Analysis

Year 2024, Volume: 39 Issue: 2, 437 - 452, 11.07.2024

Serap Akcan , Murat Akcıl , Metin Özşahin

https://doi.org/10.21605/cukurovaumfd.1514451

Abstract

Nowadays especially production companies gathering a huge data due to their daily transactions on the own systems. Production companies should handle this raw data as handling the raw materials too. Today, scientific studies carried out for this purpose are gathered under the title of BigData. The BigData creates many helps to companies’ competitive advantages according to their competitors. For this view, the purpose of this study was to determine the best demand forecasts method and forecasting period by using BigData at forest production industry. Using the time series analysis module of the WEKA program, the algorithm and data set providing the most accurate estimate for each of the selected decor papers were determined. As a result, it is thought that this study will provide a route map for about choosing right data period and forecasting method for the forest products.

Keywords

Big data, Data mining, Time series analysis, Demand forecasting, Forest products sector

Zaman Serisi Analizinde Doğru Tahmin Yöntemini, Veri Kümesini ve Dönemi Seçmek İçin Büyük Veriyi Kullanma

Abstract

Günümüzde özellikle üretim firmaları kendi sistemleri üzerinde yaptıkları günlük işlemlerden dolayı büyük miktarda veri toplamaktadır. Üretim şirketleri, ham maddeyi ele aldığı gibi bu ham veriyi de ele almalıdır. Günümüzde bu amaçla yapılan bilimsel çalışmalar büyük veri başlığı altında toplanmaktadır. Büyük veri, şirketlerin rakiplerine göre rekabet avantajı sağlamasına birçok katkı sağlamaktadır. Bu doğrultuda bu çalışmanın amacı, orman ürünleri sektöründe büyük veri kullanarak en iyi talep tahmin yöntemini ve tahmin dönemini belirlemektir. Çalışmada, WEKA programının zaman serisi analiz modülü kullanılarak seçilen dekor kağıtlarının her biri için en doğru tahmini sağlayan algoritma ve veri seti belirlenmiştir. Sonuç olarak bu çalışmanın orman ürünlerine ilişkin doğru veri periyodu seçimi ve tahmin yöntemi konusunda bir yol haritası oluşturacağı düşünülmektedir.

Keywords

Büyük veri, Veri madenciliği, Zaman serisi analizi, Talep tahmini, Orman ürünleri sektörü

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