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Curves of actual versus simulated values using traditional and optimized GM (1,1), NGBM (1,1), and Fourier series.
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Coffee is the most traded commodity after petroleum. The Vietnamese coffee bean industry has raised concerns lately over an inefficient coffee value chain; bets on coffee price uncertainty are increasing worldwide in the current. Accurate optimization of coffee bean prices helps manufacturers to control an unpredictable market and upgrade cooperati...
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... used to evaluate the accuracy of the forecasting model and shown as follows: After finding each model's future price forecasts, Figure 2 displays the validation of coffee bean prices from 2014 to 2019 for each forecasting model, such as GM (1,1), the NGBM (1,1), and Fourier Series Model. We presented the price forecasts for coffee beans grown in Lam Dong below: ...
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... this optimization method, the Fourier series model's average error decreased from 3.926% to 2.077%. However, even though the MAPE percentage was small, for the fluctuating curve given in Figure 2, the Fourier series model surpasses the traditional Fourier series model in the simulation results, being nearly equal to the actual coffee bean price line. ...
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... parameter evaluation of the fitted models was developed by Phan (2015) andChen (2008) below: As shown in Figure 2, for the given fluctuating curve, the NGBM (1,1) surpasses the performance expectations of the Fourier series model in the simulation results. Price forecasting was the best method to generate new ideas for self-innovation in the coffee industry. ...
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... used to evaluate the accuracy of the forecasting model and shown as follows: After finding each model's future price forecasts, Figure 2 displays the validation of coffee bean prices from 2014 to 2019 for each forecasting model, such as GM (1,1), the NGBM (1,1), and Fourier Series Model. We presented the price forecasts for coffee beans grown in Lam Dong below: ...
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... this optimization method, the Fourier series model's average error decreased from 3.926% to 2.077%. However, even though the MAPE percentage was small, for the fluctuating curve given in Figure 2, the Fourier series model surpasses the traditional Fourier series model in the simulation results, being nearly equal to the actual coffee bean price line. ...
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... parameter evaluation of the fitted models was developed by Phan (2015) andChen (2008) below: As shown in Figure 2, for the given fluctuating curve, the NGBM (1,1) surpasses the performance expectations of the Fourier series model in the simulation results. Price forecasting was the best method to generate new ideas for self-innovation in the coffee industry. ...
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Citations
... The moisture content of dried coffee beans can be determined by analyzing the moisture content using a grain meter and calculating the decrease in moisture content using formula (8) The moisture content and mass of the product after drying are listed in Table 2 and in Figs. 19 and 20 . ...
... Penelitian ini menemukan bahwa ada tiga variabel utama yang menentukan situasi keuangan perusahaan antara lain rasio ekuitas dan pendapatan dari penjualan, perbedaan antara indikator likuiditas cepat untuk industri dan untuk perusahaan dan dinamika kewajiban jangka pendek perusahaan. Penelitian tentang model peramalan terintegrasi untuk rantai pasokan biji kopi telah diteliti sebelumnya [7]. Hasil penelitian ini menunjukkan bahwa model peramalan terintegrasi merupakan metode peramalan yang efektif. ...
Industri makanan ringan merupakan salah satu sektor industri yang memiliki tren pertumbuhan positif pada tahun 2022. Sayangnya, dibeberapa daerah sentral makanan ringan kondisi sulit masih terasa seperti di Kabupaten Bekasi. Untuk membantu menentukan arah kebijakan dan keputusan perusahaan agar efektif dan efisien di masa depan adalah dengan mengembangkan sebuah peramalan usaha. Studi kasus penelitian ini adalah CV. Stanley Mandiri Snack yang memfokuskan dalam usaha menentukan stock awal agar dapat meminimalisir ketidakpastian penjualan periode mendatang. Metode Regresi linier dan Polinomial merupakan metode yang digunakan dalam penelitian ini disebabkan sederhana, mudah dalam proses dan memiliki hasil yang optimal. Hasil penelitian ini adalah terbangunnya model persamaan regresi dan polynomial penjualan melalui pendekatan Curve Fit. Kedua model ini dapat diterima karena memiliki nilai evauasi MAPE yang rendah yaitu berkisar 1% dan R2 sebesar 0,99. Berdasarkan model peramalan yang dibangun, perusahaan akan terus mengalami penurunan nilai penjualan untuk beberapa bulan kedepan. Perusahaan perlu mempertimbangkan strategi yang tepat diterapkan agar potensi pasar membaik pada periode berikutnya seperti pemasaran berbiaya rendah, penyesuaian atau mengubah menu dan menghindari program diskon
This chapter intends to investigate and present the possibility of utilizing artificial intelligence to transform the agricultural supply chain. The primary objective is to enhance efficiency, sustainability, and adaptability in response to a shifting climate and expanding global population. The results of this investigation provide significant and valuable knowledge for both new businesses and well-established corporations who have a vested interest in embarking on an intelligent and sustainable digital revolution within the agricultural sector and food supply chains. These findings present insights that can guide these enterprises in their pursuit of transforming their operations using technology to enhance efficiency, productivity, and sustainability. By harnessing the benefits offered by digitization, organizations operating within the agriculture industry will be able to streamline processes, optimize resource allocation, reduce waste, and improve traceability throughout the supply chain network while ultimately securing long-term success.
These authors contributed equally to this work. Abstract Nowadays, the growth of using a huge volume of data in various industries makes it crucial to adopt efficient tools and methods to collect, process, and use them to gain a competitive advantage. Big data analytics (BDA) are referred to as a set of tools and techniques that are used for obtaining meaningful results from large sets of data. BDA is used in many disciplines including logistics and supply chain management functions. Although many reviews aim to study BDA in SCM some deficiencies need to be addressed at the same time. After identifying such gaps in the literature, this paper provides a comprehensive review of the literature and tries to handle such deficiencies in a structured way. We conducted an interdisciplinary method where an organizational view is used to discuss the theoretical and ethical challenges of BDA in SCM. From a technical perspective, we used bottom-up and up-down methods and studied different aspects of BDA in the supply chain narrative. Unlike most reviews, we covered a relatively long period from 2009 to 2023. Finally, we provided theoretical and practical implications for the stakeholders and researchers and mentioned future research directions that were not elaborated on before in the literature.
The research goal presented in this paper was to determine the strength of the relationship between the price of coffee traded on ICE Futures US and Consumer Price Indices in the major urban agglomerations of the United States—New York, Chicago, and Los Angeles—and to predict the future development. The results obtained using the Pearson correlation coefficient confirmed a very close direct correlation (r = 0.61 for New York and Chicago; r = 0.57 for Los Angeles) between the price of coffee and inflation. The prediction made using the SARIMA model disrupted the mutual correlation. The price of coffee is likely to anchor at a new level where it will fluctuate; on the other hand, the CPIs showed strong unilateral pro-growth trends. The results could be beneficial for the analysis and creation of policies and further analyses of market structures at the technical level.
