scholarly journals Perspective on Crude Palm Oil Production: The Effect of Raw Palm Oil and Biofuel Prices

2021 ◽  
pp. 15-25
Author(s):  
Afriany ◽  
Rubianto Pitoyo
Keyword(s):  
Production Process ◽  
Palm Oil ◽  
Time Series Data ◽  
Oil Production ◽  
Series Data ◽  
Production Data ◽  
Crude Palm Oil ◽  
Specialized Production ◽  
Production Factors ◽  
The Relationship

Efficiency is the important things in production process. Some production factors as labor, materials, and machinery must be calculate accurately. The purpose of this research is for analyzing the influence of raw palm oil and Biofuel prices against crude palm oil production. Sample in this research is time series data that specialized production data, The technique analysis is using analysis of multiple linier regression. The results from analysis show correlation between raw palm oil and biofuel prices with crude palm oil production is 57.1 %, The relationship between raw palm oil against crude palm oil production have significant effect and biofuel prices against crude palm oil production have no significant effect. Based on the results of F test there are the significant influence between raw palm oil and biofues prices against crude palm oil production. finding in this research is PT. Wilmar using 3 type of fuel for production process, petroleum, biofuel and waste of raw palm oil production which makes biofuel prices have no effect on crude palm oil production

scholarly journals A Model to Manage Crude Palm Oil Production System

2019 ◽  
Vol 255 ◽  
pp. 02001 ◽  
Author(s):  
Inyang John ◽  
Andrew-Munot Magdalene ◽  
Syed Shazali Syed Tarmizi ◽  
Johnathan Tanjong Shirley
Keyword(s):  
Simulation Model ◽  
Production Process ◽  
Conceptual Model ◽  
Palm Oil ◽  
Production System ◽  
Oil Production ◽  
Future Research ◽  
Crude Palm Oil ◽  
Model Based ◽  
The Future

This paper reviews key production process for crude palm oil and highlights factors that highly influence the production of crude palm oil. This paper proposes a generic conceptual model for crude palm production process considering these factors. The conceptual model could be modified to consider other factors not included in this paper. The future research would be to construct a simulation model based on the conceptual model proposed in this paper and analyse the effect of these factors on the performance of crude palm oil production system.

scholarly journals Penerapan Decision Tree J48 dan Reptree dalam Menentukan Prediksi Produksi Minyak Kelapa Sawit menggunakan Metode Fuzzy Tsukamoto

2020 ◽  
Vol 7 (3) ◽  
pp. 483
Author(s):  
Tundo Tundo ◽  
Shofwatul 'Uyun
Keyword(s):  
Decision Tree ◽  
Production Process ◽  
Palm Oil ◽  
Oil Production ◽  
Actual Data ◽  
Production Data ◽  
Actual Production ◽  
Speed Up ◽  
Rule Making

<p>Penelitian ini menerangkan penerapan <em>decision tree</em> J48 dan REPTree dengan menggunakan metode <em>fuzzy Tsukamoto</em> dengan objek yang digunakan adalah penentuan jumlah produksi minyak kelapa sawit di perusahaan PT Tapiana Nadenggan dengan tujuan untuk mengetahui <em>decision tree</em> mana yang hasilnya mendekati dari data sesungguhnya sehingga dapat digunakan untuk membantu memprediksi jumlah produksi minyak kelapa sawit di PT Tapiana Nadenggan ketika proses produksi belum diproses. Digunakannya <em>decision tree</em> J48 dan REPTree yaitu untuk mempercepat dalam pembuatan <em>rule </em>yang digunakan tanpa harus berkonsultasi dengan para pakar dalam menentukan <em>rule</em> yang digunakan. Dari data yang digunakan akurasi dari decision tree J48 adalah 95.2381%, sedangkan akurasi REPTree adalah 90.4762%, akan tetapi dalam kasus ini <em>decision tree</em> REPTree yang lebih tepat digunakan dalam proses prediksi produksi minyak kelapa sawit, karena di uji dengan data sesungguhnya pada bulan Maret tahun 2019 menggunakan REPTree diperoleh 16355835 liter, sedangkan menggunakan J48 diperoleh 11844763 liter, dimana data produksi sesungguhnya sebesar 17920000 liter. Sehingga dapat ditemukan suatu kesimpulan bahwa untuk kasus ini data produksi yang mendekati dengan data sesungguhnya adalah REPTree, meskipun akurasi yang diperoleh lebih kecil dibandingkan dengan J48.</p><p><em><strong>Abstract</strong></em></p><div><p><em>This study explains the application of the J48 and REPTree decision tree using the fuzzy Tsukamoto method with the object used is the determination of the amount of palm oil production in the company PT Tapiana Nadenggan with the aim of knowing which decision tree the results are close to the actual data so that it can be used to help predict the amount palm oil production at PT Tapiana Nadenggan when the production process has not been processed. The use of the J48 and REPTree decision tree is to speed up the rule making that is used without having to consult with experts in determining the rules used. From the data used the accuracy of the J48 decision tree is 95.2381%, while the REPTree accuracy is 90.4762%, but in this case the REPTree decision tree is more appropriate to be used in the prediction process of palm oil production, because it is tested with actual data in March 2019 uses REPTree obtained 16355835 liters, while using J48 obtained 11844763 liters, where the actual production data is 179,20000 liters. So that it can be found a conclusion that for this case the production data approaching the actual data is REPTree, even though the accuracy obtained is smaller compared to J48.</em></p></div><p><em><strong><br /></strong></em></p>

scholarly journals Evaluating the Sustainability and Inherent Safety of a Crude Palm Oil Production Process in North-Colombia

2021 ◽  
Vol 11 (3) ◽  
pp. 1046
Author(s):  
Angel Darío González-Delgado ◽  
Andrés F. Barajas-Solano ◽  
Jeffrey Leon-Pulido
Keyword(s):  
Production Process ◽  
Palm Oil ◽  
Return On Investment ◽  
Oil Production ◽  
Rapid Expansion ◽  
Process Equipment ◽  
Inherent Safety ◽  
Safety Index ◽  
Crude Palm Oil ◽  
Complete Evaluation

The African palm is the main source of vegetable oil worldwide, representing about 29.60% of the total oil and fat production around the world. The rapid expansion of this sector has faced several concerns related to environmental and social aspects that have driven the search for sustainable alternatives. In this work, the inherent safety analysis and sustainability evaluation for the crude palm oil production process was performed using the inherent safety index (ISI) method and the sustainable weighted return on investment metric (SWROIM), respectively. The process was designed for a processing capacity of 30 t/h of palm bunches and under North-Colombian conditions. Three technical indicators were considered to evaluate the process sustainability including exergy efficiency, potential environmental impacts output (PEI output), and the total inherent safety index (ITI). The economic factor is directly considered since the SWROIM is an extension of the conventional return on investment (ROI). The resulting ITI at 11 indicated an inherently safe process, and the highest risk was observed for the process equipment safety subindex. The SWROIM reached a higher value (53%) compared to the conventional ROI (49.39%), which suggests positive impacts on sustainability. The novelty of this work lies in detecting the inherent risks and providing a decision making criteria for this project through a complete evaluation that relates economic, energy, environmental, and safety criteria.

scholarly journals ANALISIS PENGARUH NILAI TUKAR TERHADAP EKSPOR KOMODITAS UNGGULAN INDONESIA

2019 ◽  
Vol 2 (1) ◽  
pp. 141-146
Author(s):  
M Taufiq ◽  
Nu Aliyah Natasah
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Palm Oil ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Series Data ◽  
Simple Linear Regression ◽  
Crude Palm Oil ◽  
Independent Variable ◽  
Positive Effect

This study aims to determine the effect of exchange rates on Indonesian commodity exports. Where the exchange rate is a comparison of the value or price of the Rupiah against other currencies. The dependent variable is the export of Indonesia's leading commodities, including Crude Palm Oil (Y1), Rubber (Y2) and textile (Y3) with the independent variable, namely the rupiah exchange rate (X). The data used in this study are time series data from 2012-2017. The method used is simple linear regression analysis, and is processed using the SPSS 16.0 program. The results of this study indicate that the rupiah exchange rate has a positive and significant effect on rubber export commodities and does not have a positive effect on palm oil (CPO) and textile commodities.

scholarly journals Forecasting of crude palm oil price using hybridizing wavelet and group method of data handling model

2017 ◽  
Vol 13 (4) ◽  
pp. 642-648
Author(s):  
Huma Basheer ◽  
Azme Khamis
Keyword(s):  
Time Series ◽  
Palm Oil ◽  
Wavelet Decomposition ◽  
Time Series Data ◽  
Spectral Band ◽  
Absolute Error ◽  
Series Data ◽  
Group Method ◽  
Data Handling ◽  
Crude Palm Oil

Forecasting of Crude Palm Oil (CPO) is one of the most important and the largest vegetable oil traded in the world market. This study investigates the forecasting of Crude Palm Oil (CPO) price using a hybrid model of Group Method of Data Handling (GMDH) with wavelet decomposition. The original monthly data of CPO time series were decomposed into the spectral band. After that, these decomposed subseries were given as input time series data to GMDH model to forecast the CPO price of monthly time series data. The result performance of hybridized GMDH model is compared with the original GMDH model. The measurements results from the mean absolute error (MAE) and the root mean square error (RMSE) showed that the hybrid GMDH model with wavelet decomposition gives more accurate result of predictions compared with the original GMDH model.

scholarly journals Optimasi Fuzzy Artificial Neural Network dengan Algoritma Genetika untuk Prediksi Harga Crude Palm Oil

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Anwar Rifa'i
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Palm Oil ◽  
Basis Function ◽  
Time Series Data ◽  
Training Data ◽  
Series Data ◽  
Crude Palm Oil ◽  
Testing Data ◽  
Radial Basis

Crude Palm Oil (CPO) is one of Indonesia's best export commodities. CPO production competition causes price fluctuations so that it can trigger losses. The solution that can be taken to avoid losses is to predict the price of CPO. Time series data in the previous months, starting from January 2009 until January 2020, are used as a reference to predict the next CPO price. In this research, CPO price prediction is carried out with a combination of artificial intelligence concepts, namely Radial Basis Function Neural Network (RBFNN), and fuzzy logic. The combination of these methods, namely Fuzzy Radial Basis Function Neural Network (FRBFNN), is then optimized using genetic algorithms. The prediction results show that the error based on the MAPE value for FRBFNN prediction on training data is 11.7% and the MAPE value for testing data is 9.4%. In the FRBFNN prediction that was optimized using a genetic algorithm, the MAPE value was 10.2% for training data and 8.3% for testing data.

scholarly journals Excess Capacity and Entry Deterrence: The Case of Malaysian Palm Oil Refining Industry

2020 ◽  
Author(s):  
Choo Sze Yi ◽  
Suhaila H. A. Jalil
Keyword(s):  
Palm Oil ◽  
Time Series Data ◽  
Entry Deterrence ◽  
Refining Industry ◽  
Oil Refining ◽  
Series Data ◽  
Excess Capacity ◽  
Estimation Model ◽  
Data Capacity ◽  
The Relationship

This paper empirically examines the relationship between excess capacity and probability of entry into Malaysian palm oil refining industry using time series data. Capacity and production, two components crucial to the study of excess capacity, were included in the estimation model. The analysis was conducted specifically in the Malaysian palm oil refining industry and the sample covered the period from 1976 to 2011. Logit model was employed in this analysis, where the results exhibited that excess capacity does not significantly influence probability of entry into the palm oil refining industry in Malaysia.  

Testing Structural Break in the Relationship Between Exchange Rate and Macroeconomic Variables

2019 ◽  
Vol 23 (4) ◽  
pp. 442-453 ◽  
Author(s):  
Saidia Jeelani ◽  
Joity Tomar ◽  
Tapas Das ◽  
Seshanwita Das
Keyword(s):  
Exchange Rate ◽  
Structural Breaks ◽  
Time Series Data ◽  
Structural Break ◽  
Series Data ◽  
Ripple Effect ◽  
Macroeconomic Factors ◽  
Parameter Instability ◽  
Macroeconomic Variables ◽  
The Relationship

The article aims to study the relationship between those macroeconomic factors that the affect (INR/USD) exchange rate (ER). Time series data of 40 years on ER, GDP, inflation, interest rate (IR), FDI, money supply, trade balance (TB) and terms of trade (ToT) have been collected from the RBI website. The considered model has suggested that only inflation, TB and ToT have influenced the ER significantly during the study period. Other macroeconomic variables such as GDP, FDI and IR have not significantly influenced the ER during the study period. The model is robust and does not suffer from residual heteroscedasticity, autocorrelation and non-normality. Sometimes the relationship between ER and macroeconomic variables gets affected by major economic events. For example, the Southeast Asian crisis caused by currency depreciation in 1997 and sub-prime loan crisis of 2008 severely strained the national economies. Any global economic turmoil will affect different economic variables through ripple effect and this, in turn, will affect the ER of different economies differently. The article has also diagnosed whether there is any structural break or not in the model by applying Chow’s Breakpoint Test and have obtained multiple breaks between 2003 and 2009. The existence of structural breaks during 2003–2009 is explained by the fact that volume of crude oil imported by India is high and oil price rise led to a deficit in the TB alarmingly, which caused a structural break or parameter instability.

scholarly journals Non-bank financial institutions and economic growth: Evidence from Africa’s three largest economies

2017 ◽  
Vol 20 (1) ◽  
Author(s):  
Ronald Rateiwa ◽  
Meshach J. Aziakpono
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Financial Institutions ◽  
Time Series Data ◽  
Bank Lending ◽  
Series Data ◽  
The Sustainable Development ◽  
Long Run ◽  
The Relationship

Background: In order for the post-2015 world development agenda – termed the sustainable development goals (SDGs) – to succeed, there is a pronounced need to ensure that available resources are used more effectively and additional financing is accessed from the private sector. Given that traditional bank lending has slowed down, the development of non-bank financing has become imperative. To this end, this article intends to empirically test the role of non-bank financial institutions (NBFIs) in stimulating economic growth.Aim: The aim of this article is to empirically test the existence of a long-run equilibrium relationship between economic growth and the development of NBFIs, and the causality thereof.Setting: The empirical assessment uses time-series data from Africa’s three largest economies, namely, Egypt, Nigeria and South Africa, over the period 1971–2013.Methods: This article uses the Johansen cointegration and vector error correction model within a country-specific setting.Results: The results showed that the long-run relationship between NBFI development and economic growth is relatively stronger in Egypt and South Africa, than in Nigeria. Evidence in respect of Nigeria shows that such a relationship is weak. The nature of the relationship between NBFI development and economic growth in Egypt is positive and significant, and predominantly bidirectional. This suggests that a virtuous relationship between NBFIs and economic growth exists in Egypt. In South Africa, the relationship is positive and significant and predominantly runs from NBFI development to economic growth, implying a supply-leading phenomenon. In Nigeria, the results are weak and mixed.Conclusion: The study concludes that in countries with more developed financial systems, the role of NBFIs and their importance to the economic growth process are more pronounced. Thus, there is need for developing policies targeted at developing the NBFI sector, given their potential to contribute to economic growth.

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