scholarly journals DAYA SAING EKSPOR PALA INDONESIA DI PASAR INTERNASIONAL

2019 ◽  
Vol 33 (2) ◽  
pp. 179-188
Author(s):  
Asrol Asrol ◽  
Heriyanto Heriyanto
Keyword(s):  
Time Series Data ◽  
International Market ◽  
World Market ◽  
Series Data ◽  
Maturity Stage ◽  
Composition Effects ◽  
Average Value ◽  
The World ◽  
Constant Market Share ◽  
Secondary Time

Indonesia is one of the largest producing and exporting countries for nutmeg commodities in the world market. Indonesia as a nutmeg exporting country is a country that imports nutmeg products. Nutmeg is one of Indonesia's leading spice export commodities on the world market. Based on the description in general, this study aims to analyze the competitiveness of Indonesian nutmeg in the world market. Specifically, this study aims to analyze the export position of nutmeg and the competitiveness of Indonesian nutmeg in the international market. The power used in this study is secondary time series data from 2007-2016. To answer the research objectives, it was analyzed using the Trade Specialization Index (ISP), Revealed Comparative Advantage (RCA) and Constant Market Share (CMS). Based on the results of the study indicate that for the position of Indonesian nutmeg exports on the world market, the average value of Indonesian ISPs on the world market from 2007-2016 was 0.988. This value indicates that the position or stage of Indonesian nutmeg export is at the maturity stage with an indicator value (0.81-1.00). Furthermore, the competitiveness of the results of the average Indonesian nutmeg RCA value on the international market which is calculated from 2007-2016 reached 19,554 because the value of Indonesian nutmeg RCA is greater than one, so Indonesia has a strong competitiveness in the export of nutmeg in the world and tends to be a country exporter rather than importer. For the CMS value of Indonesian nutmegs in the last five years period is negative on the standard growth, composition effects, and market distribution effects but the positive value on the effect of competitiveness.

scholarly journals INDONESIAN COCONUT COMPETITIVENESS IN INTERNATIONAL MARKETS

2019 ◽  
Vol 1 (3) ◽  
pp. 46-50
Author(s):  
Heriyanto Heriyanto
Keyword(s):  
Comparative Advantage ◽  
Supply And Demand ◽  
International Market ◽  
World Market ◽  
International Markets ◽  
Average Value ◽  
A Value ◽  
Constant Market Share Analysis ◽  
Constant Market Share ◽  
Derivative Products

Indonesia is one of the country's largest Coconut producer and exporter in the world market. The management efforts of Indonesia coconut not optimal, coconut export is still largely in the form of primary products, a type of derivative products coconut produced Indonesia is still limited. But in general, this research aims to analyze the Export Competitiveness of coconut Indonesia in international markets, specifically aims to analyze the position and competitiveness of Indonesia coconut commodities in the international market. Methods of data analysis using Trade Specialization Index (TSI), the analysis Revealed Comparative Advantage (RCA), and the Constant Market Share analysis (CMS). The results showed that during the period of 2005-2016, the development of supply and demand are relatively unstable and likely to rise. TSI values during the period of 2005-2016 have the value positive that shows that Indonesia is a country exporting coconut and belongs into the categories of very mature in the international market, indicated by the average value of the TSI of 1.00. The value of the RCA during the period of 2005-2016 have a value above 1 indicating that Indonesia Coconut has a comparative advantage for the commodity. While the analysis results in CMS during the period of 2005-2016 based on the four effects shows that the competitiveness of coconut Indonesia influenced by standard growth effects and efficient distribution where the coconut export growth in Indonesia is affected by the growth of coconut import world.  

scholarly journals A Comparison of World and Domestic Price Volatilities of Oilseeds: The Ethiopian Case

2015 ◽  
Vol 7 (2(J)) ◽  
pp. 145-161
Author(s):  
Zerihun G. Kelbore
Keyword(s):  
Poverty Reduction ◽  
Time Series Data ◽  
Market Price ◽  
Price Volatility ◽  
World Market ◽  
Domestic Market ◽  
Series Data ◽  
The World ◽  
Price Risks ◽  
The Government

This study investigates and compares oilseeds price volatilities in the world market and the Ethiopian market. It uses a monthly time series data on oilseeds from February 1999 to December 2012; and analyses price volatilities using unconditional method (standard deviation) and conditional method (GARCH). The results indicate that oilseeds prices are more volatile, but not persistent, in the domestic market than the world market. The magnitude of the influence of the news about past volatility (innovations) is higher in the domestic market for Rapeseed and in the World market for Linseed. However, in both markets there is a problem of volatility clustering. The study also identified that due to the financial crisis the world market price volatilities surpassed and/or paralleled the higher domestic oilseeds price volatilities. The higher domestic oilseeds price volatility may imply that the price risks are high in the domestic oilseeds market. As extreme price volatility influences farmers` production decision, they may opt to other less risky, low-value and less profitable crop varieties. The implications of such retreat is that it may keep the farmers in the traditional farming and impede their transformation to the high value crops, and results in lower income hindering the poverty reduction efforts of the government. This is more important to consider today than was before, because measures undertaken to reduce poverty must bring sustainable change in the lives of the rural poor. For this reason, agricultural policies that enable farmers cope with price risks and enhance their productivity are crucial.

scholarly journals MODEL PENAWARAN DAN PERMINTAAN MINYAK KELAPA SAWIT INDONESIA DI PASAR INTERNASIONAL

2020 ◽  
Vol 35 (3) ◽  
pp. 119-128
Author(s):  
Tia Sofiani Napitupulu ◽  
Djaimi B Akce ◽  
Almasdi Syahza ◽  
Brilliant Asmit ◽  
Syaiful Hadi
Keyword(s):  
Palm Oil ◽  
Time Series Data ◽  
Supply And Demand ◽  
Coconut Oil ◽  
Oil Prices ◽  
World Market ◽  
Least Square ◽  
Series Data ◽  
The World

ABSTRACT   Indonesia is the leading producer of palm oil in the world. In 2016 Indonesia and Malaysia produced 81% of the world's palm oil. This study aims to analyze the response of the supply and demand for Indonesian palm oil in the world market. This study used time-series data from 1980-2016. The model built is an econometric model, simultaneous equations. To answer the research objectives, the data were analyzed using the Two Stages Least Square (2SLS) method. The main finding of this study is that in the short term, there are no responsive variables. In the long term, the variable that is responsive to the supply of Indonesian palm oil is the lag area of Indonesian palm oil. In the Malaysian palm oil supply equation, the response variable is the lag area of Malaysian palm oil. In terms of domestic demand for Indonesian palm oil, there are no responsive variables both in the short and long term. In the equation of demand for Malaysian palm oil, the responsive variables are the price of Malaysian palm oil and the price of Malaysian coconut oil. In the international demand for palm oil, the responsive variables are the increase in world palm oil prices, world palm oil prices, 2-year lag in world palm oil prices, and GDP per capita Pakistan. In terms of price, the responsive variable affecting the price of Indonesian palm oil is the world price of palm oil.

scholarly journals RICE EXPORT FROM INDIA: TRENDS, PROBLEMS AND PROSPECTS

2016 ◽  
Vol 4 (7) ◽  
pp. 122-136
Author(s):  
Ramakrishna ◽  
Chaya Degaonkar
Keyword(s):  
Time Series Data ◽  
Secondary Data ◽  
Careful Analysis ◽  
World Market ◽  
Vital Role ◽  
Basmati Rice ◽  
Series Data ◽  
Rice Varieties ◽  
Good Market ◽  
The World

In India, agriculture is the main occupation. About 58 per cent of the population depends upon agriculture. It is the backbone of the Indian economy. In agriculture, rice is one of the most important food crops of India. It feeds more than 50 per cent of the world’s population. Rice is continues to play vital role in the national exports. India is one of the important countries in the world in export of rice. Indian rice exports are reached first place in the world markets. This study has analysed the trends and variability of rice export, assess the prospects of rice export and the various problems/constraints of rice export from India to various countries in the world. The study based on secondary data. The time series data on export of rice from India for the period 2001-02 to 2013-14.This paper indicates that there is good market for some Indian rice varieties, especially basmati rice in the world market. Pakistani basmati, as a sole competitor of India, does not have the unique aroma and taste as the Indian varieties. During 2012-13 the foreign earning from basmati rice has increased considerably. Despite considerable area being under rice cultivation in the country, the share of India in world rice export is very low which can be attributed to the fact that the average productivity of rice in the country is low and even in some rice producing states, the productivity is 40 to 50 per cent lower than the national average, in spite of having good potential capacity. The reasons of low productivity of rice in the country may be due to use of less quantity of chemical fertilizers, pesticides, more area under traditional varieties and more dependence on rain. If we want to increase our exports share in the world rice market, the production growth rate should be adequate surplus in the country. This requires careful analysis of low productivity of rice in the country. Besides, more important, the critical analysis is necessary to enquire into the constraints involved in rice export from India.

DAYA SAING EKSPOR KARET ALAM TIGA NEGARA ITRC (INDONESIA, THAILAND, MALAYSIA) DI PASAR INTERNASIONAL PERIODE 1994-2018

2020 ◽  
Vol 4 (1) ◽  
pp. 81-87
Author(s):  
Shinta Dwi Ardanari ◽  
Rynalto Mukiwihando
Keyword(s):  
Natural Rubber ◽  
Analytical Method ◽  
International Market ◽  
World Market ◽  
Competitive Advantages ◽  
Market Demand ◽  
Export Share ◽  
Intense Competition ◽  
Time Period ◽  
The World

ABSTRACTShare of Indonesia's export value of natural rubber in the international market is almost always below Thailand, which is one of the competiting countries. The others countries began to become a threat to Indonesia because their exports share of natural rubber showed an increasing. This indicates that there is intense competition in the international market. As a country with the largest plantation area in the world, Indonesia should be superior. But this can be an opportunity to be able to compete in the world market so it is important to be managed more deeply so that it can create competitive advantages that can increase competitiveness. This study aims to determine the position of the competitiveness of natural rubber exports for the three countries of ITRC in the international market. The analytical method used is dynamic RCA. The results showed that all products of natural rubber coded HS 400110, 400121, 400122, 400129 and 400130 were experiencing a decline in growth in the export share of the three countries of ITRC : Indonesia, Thailand and Malaysia, but the market demand conditions for these products were declining in that time period.

Prediction and Analysis of Gold Prices using Ensemble Machine Learning Algorithms

2021 ◽  
Vol 9 (VI) ◽  
pp. 4367-4374
Author(s):  
Gudipally Chandrashakar
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Time Series Data ◽  
Gold Price ◽  
Machine Learning Algorithms ◽  
Series Data ◽  
Gradient Boosting ◽  
Support Vector ◽  
Average Value ◽  
Ensemble Machine Learning

In this article, we used historical time series data up to the current day gold price. In this study of predicting gold price, we consider few correlating factors like silver price, copper price, standard, and poor’s 500 value, dollar-rupee exchange rate, Dow Jones Industrial Average Value. Considering the prices of every correlating factor and gold price data where dates ranging from 2008 January to 2021 February. Few algorithms of machine learning are used to analyze the time-series data are Random Forest Regression, Support Vector Regressor, Linear Regressor, ExtraTrees Regressor and Gradient boosting Regression. While seeing the results the Extra Tree Regressor algorithm gives the predicted value of gold prices more accurately.

scholarly journals FAKTOR – FAKTOR YANG MEMPENGARUHI KONSUMSI GAS DI INDONESIA

2021 ◽  
Vol 3 (2) ◽  
pp. 69
Author(s):  
Rohim Rohim ◽  
Mike Triani
Keyword(s):  
Time Series ◽  
World Bank ◽  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Industrial Growth ◽  
A Value ◽  
The World Bank ◽  
The World ◽  
Gas Consumption

The purpose of this research is to determine (1) the effect of income on gas consumption in Indonesia (2) the effect of population on gas consumption in Indonesia (3) the effect of industrial growth on gas consumption in Indonesia. This type of research is descriptive and associative. The data used in this research is secondary data from Indonesia in the form of time series data from 1970 to 2019 and this data was obtained from official institutions of the World Bank and BP Statistic World. The data were processed using multiple linear regression. The results showed that the income had a negative and significant effect on gas consumption with a probability value of 0.0005 <0.05, the population had a positive and significant effect on gas consumption with a value of prob t-count of 0.0010 <0.05 and industrial growth had a positive and significant effect on gas consumption.  The significant to gas consumption in Indonesia with a value of prob t-count value of 0.5219 <0.05 and suggestions for further researchers to be able to analyze other factors that affecting gas consumption in Indonesia.  Because from the gas sectors, there are still many factors that affected gas consumption until the research results will be better

scholarly journals Analysis of social responsibility of mining companies in the international market

2021 ◽  
Vol 303 ◽  
pp. 01003
Author(s):  
Olena Kozyrieva ◽  
Nataliia Tkalenko ◽  
Valentina Vyhovska ◽  
Alina Pinchuk
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Corporate Sustainability ◽  
International Market ◽  
World Market ◽  
The World ◽  
Governance Practice ◽  
Corporate Governance Practice ◽  
Corporate Social

The article proves that the implementation of the principles and use of the tools of corporate social responsibility can increase the reputation of the corporation and its activity in the world market. The purpose of the article is to substantiate and determine the role of corporate social responsibility of the mining and metals companies in ensuring and improving their reputation in the world market. The article substantiates that the low level of corporate governance practice and insufficient part of social contribution to the companies negatively affect formation of corporate social responsibility of the corporations. The article analyzes the indicators of Corporate sustainability and Transparency for 2018-2019 according to the professional rating of the largest Ukrainian mining and metals companies, based on leading international practices. The analysis of indicators made it possible to identify the proportional dependence of the reputation of the corporation on the measures of corporate social responsibility that the latter implements. It is determined on the basis of the study that corporate social responsibility is an effective tool to increase the competitiveness of mining and metals companies.

scholarly journals Risk Based Bank Rating dalam Mengukur Tingkat Kesehatan Perbankan

2019 ◽  
Vol 3 (2) ◽  
pp. 114-123
Author(s):  
Neny Tri Indrianasari ◽  
Khoirul Ifa
Keyword(s):  
Corporate Governance ◽  
Financial Services ◽  
Time Series Data ◽  
Risk Profile ◽  
Series Data ◽  
Average Value ◽  
Good Corporate Governance ◽  
Source Data ◽  
The Government ◽  
Descriptive Method

The Financial Services Authority assesses the national banking industry in the better shape shown by some indicators, one of which the involvement of the Government in realizing economic growth. With the better banking conditions will marimbas Bank on growth Of Islamic Peoples. This research aims to know the level of health of bank Syariah BPR in East Java by using methods of Risk-Based Bank Rating. The assessment by the method of Risk-Based Bank Rating consists of four factors of risk profile, Good Corporate Governance, earning and capital of each bank. This research uses descriptive method quantitative approach to analyze the ratio-the ratio of the measured. The data type used is the time series data of the year 2015 – 2017. Source data obtained from the Financial Services Authority website (OJK). Data analysis techniques using analysis of Risk-Based Bank Rating (RBBR) consist of four-factor risk profile, Good Corporate Governance, earning and capital. The study concluded that the overall average value of NPF Bank Of Islamic People (BPRS) of 13.37% unhealthy, with an average overall rating Of Sharia Rural Banks ROA (BPRS) of 0.11% with the predicate less healthy and that the average overall rating Of Sharia Rural Banks CAR (BPRS) amounted to 28.47% with very healthy.

A Deep Learning Based Methods for Forecasting Gold Price with Respect to Pandemics

2020 ◽  
Author(s):  
Mahtab Mohtasham Khani ◽  
Sahand Vahidnia ◽  
Alireza Abbasi
Keyword(s):  
Time Series Data ◽  
Short Term Memory ◽  
Specific Model ◽  
Gold Price ◽  
Series Data ◽  
Trade Relations ◽  
Market Values ◽  
The World ◽  
Proper Estimation ◽  
Validation Set

Abstract The spread of COVID-19 in the world had a devastating impact on the world economy, trade relations, and globalization. As the pandemic advances and new potential pandemics are on the horizon, a precise analysis of recent fluctuations of trade becomes necessary for international decisions and controlling the world in similar crisis. The COVID-19 pandemic made a new pattern of trade in the world and affected how businesses work and trade with each other. It means that every potential pandemic or any unprecedented event in the world can change the market rules. This research develops a novel model to have a proper estimation of the stock market values with respect to COVID-19 dataset using long short-term memory networks (LSTM).The nature of the features in each pandemic is totally different, thus, prediction results for a pandemic by a specific model cannot be applied to other pandemics. Hence, recognising and extracting the features which affect the pandemic is in the highest priorities. In this study, we develop a framework, providing a better understanding of the features and feature selection. This study is based on a preliminary analysis of such features for enhancing forecasting models' performance against fluctuations in the market.Our forecasts are based on the market value data and COVID-19 pandemic daily time-series data (i.e. the number of new cases). In this study, we selected Gold price as a base for our forecasting task which can be replaced by any other markets. We have applied Convolutional Neural Networks (CNN) LSTM, Vector Out-put Sequence LSTM, Bidirectional LSTM, and Encoder-Decoder LSTM on our dataset and our results achieved an MSE of 6.0e-4, 8.0e-4, and 2.0e-3 on the validation set respectfully for one day, two days, and 30 days predictions in advance which is outperforming other proposed method in the literature.

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