The era of globalization and accelerated economic growth, as well as various kinds of industrial and technological transformations, are currently causing or triggering very concrete environmental problems, one of which is in terms of the growth in consumption of non-renewable energy, namely oil and natural gas. Oil and gas reserves are part of the socio-economic problems in Indonesia. It is known that oil and gas reserves are spread throughout almost all aspects of Indonesia. However, the utilization of the potential reserves of oil and natural gas resources in Indonesia is still not fully optimized. So that the potential for oil and gas reserves in Indonesia still does not fully have a more significant impact on Indonesia's economic growth. This study examines the influence of oil and gas exploration and exploitation in Indonesia on economic growth in Indonesia. This study used data on Indonesia's GDP and Exploitation and Exploitation of Indonesian Oil and Gas in a time series (1996-2021). In analyzing the data, this study used multiple linear regression. The results showed that the exploration and exploitation of oil and gas have a positive and significant effect on economic growth in Indonesia. It is hoped that this study can serve as an impetus for the government in making regulations and regulations directly related to exploration and exploitation activities both upstream and downstream of oil and gas and as encouragement and motivation for governments directly involved with upstream and downstream oil and gas activities. In addition, to issue policies in the form of continuing to prioritize technological development innovations, especially in the oil and gas sector. It is also hoped that the production results obtained from oil and natural gas exploration and exploitation activities can be more optimal and impact national energy security, state revenues, and Indonesia's economic growth.
{"title":"The Effect of the Exploration and Exploitation of Oil and Gas on Indonesian Economic Growth","authors":"Yassir Achmad, S. Syahnur, C. Seftarita","doi":"10.46336/ijqrm.v3i3.342","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i3.342","url":null,"abstract":"The era of globalization and accelerated economic growth, as well as various kinds of industrial and technological transformations, are currently causing or triggering very concrete environmental problems, one of which is in terms of the growth in consumption of non-renewable energy, namely oil and natural gas. Oil and gas reserves are part of the socio-economic problems in Indonesia. It is known that oil and gas reserves are spread throughout almost all aspects of Indonesia. However, the utilization of the potential reserves of oil and natural gas resources in Indonesia is still not fully optimized. So that the potential for oil and gas reserves in Indonesia still does not fully have a more significant impact on Indonesia's economic growth. This study examines the influence of oil and gas exploration and exploitation in Indonesia on economic growth in Indonesia. This study used data on Indonesia's GDP and Exploitation and Exploitation of Indonesian Oil and Gas in a time series (1996-2021). In analyzing the data, this study used multiple linear regression. The results showed that the exploration and exploitation of oil and gas have a positive and significant effect on economic growth in Indonesia. It is hoped that this study can serve as an impetus for the government in making regulations and regulations directly related to exploration and exploitation activities both upstream and downstream of oil and gas and as encouragement and motivation for governments directly involved with upstream and downstream oil and gas activities. In addition, to issue policies in the form of continuing to prioritize technological development innovations, especially in the oil and gas sector. It is also hoped that the production results obtained from oil and natural gas exploration and exploitation activities can be more optimal and impact national energy security, state revenues, and Indonesia's economic growth.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"233 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78301911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emmanuel Parulian Sirait, Y. Salih, R. A. Hidayana
The stock portfolio is related to how someone allocates several shares in various types of investments so that the results achieve maximum profit. By implementing a diversification system or portfolio optimization on several stocks, investors can reduce the level of risk and simultaneously optimize the expected rate of return. This study aims to determine which stocks listed on the Indonesia Stock Exchange (IDX) and included in the portfolio for the 2021-2022 period are eligible to be included in the optimal portfolio and to determine the proportion of funds for each share in the formation of the optimal portfolio. The population in this study are all shares included in the Indonesia Stock Exchange (IDX) listed on the Indonesia Stock Exchange (IDX) for the 2021-2022 period. The sample of this research is five stocks that are candidate portfolios. The sampling method uses a purposive sampling method with the criteria of 5 stocks with the highest positive ratio. The population in this study was all 30 companies included in the IDX30, while the samples were five companies. Data were analyzed using a mean-variant optimization model with a research duration between May 2021 and May 2022. Based on the results of the investment portfolio optimization analysis on the 5 (five) selected stocks, this study shows that, out of 23 stocks, five stocks are eligible to enter the optimal portfolio with their respective proportions, namely PT Adaro Energy Indonesia Tbk (ADRO) 20%, PT Astra International Tbk (ASII) 26%, PT Merdeka Copper Gold Tbk (MDKA) 10%, PT XL Axiata Tbk (EXCL) 19%, PT Bukit Asam Tbk (PTBA) 25%. The portfolio of these stocks generates an expected return of 0.00217 at a risk level of 0.00022. It is hoped that this research can be helpful to add to the literature on investment optimization models, especially the concentration of Mathematics in Finance, and serve as an additional reference for further research, as well as an alternative for investors in optimizing investment portfolios.
股票投资组合是指一个人如何在不同类型的投资中分配几股股票，以获得最大的利润。通过对多只股票实施分散投资或优化投资组合，投资者可以降低风险水平，同时优化预期回报率。本研究旨在确定哪些在印尼证券交易所(IDX)上市并在2021-2022年期间纳入投资组合的股票有资格纳入最优投资组合，并确定在形成最优投资组合中，每个股票的资金比例。本研究中的人口是2021-2022年期间在印度尼西亚证券交易所(IDX)上市的印度尼西亚证券交易所(IDX)的所有股票。本研究的样本是作为候选投资组合的五只股票。抽样方法采用有目的抽样法，以5只正比最高的个股为标准。本研究的人口为IDX30公司中的全部30家公司，样本为5家公司。研究期间为2021年5月至2022年5月，采用均值变异优化模型对数据进行分析。根据对所选5(5)只股票的投资组合优化分析结果，本研究表明，在23只股票中，有5只股票符合进入最优投资组合的条件，分别是PT Adaro Energy Indonesia Tbk (ADRO) 20%、PT Astra International Tbk (ASII) 26%、PT Merdeka Copper Gold Tbk (MDKA) 10%、PT XL Axiata Tbk (EXCL) 19%、PT Bukit Asam Tbk (PTBA) 25%。这些股票的投资组合在风险水平为0.00022时产生0.00217的预期回报。希望本研究能够对投资优化模型的文献，特别是金融学中数学的集中有所补充，为进一步的研究提供参考，也为投资者优化投资组合提供一种选择。
{"title":"Investment Portfolio Optimization Model Using The Markowitz Model","authors":"Emmanuel Parulian Sirait, Y. Salih, R. A. Hidayana","doi":"10.46336/ijqrm.v3i3.344","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i3.344","url":null,"abstract":"The stock portfolio is related to how someone allocates several shares in various types of investments so that the results achieve maximum profit. By implementing a diversification system or portfolio optimization on several stocks, investors can reduce the level of risk and simultaneously optimize the expected rate of return. This study aims to determine which stocks listed on the Indonesia Stock Exchange (IDX) and included in the portfolio for the 2021-2022 period are eligible to be included in the optimal portfolio and to determine the proportion of funds for each share in the formation of the optimal portfolio. The population in this study are all shares included in the Indonesia Stock Exchange (IDX) listed on the Indonesia Stock Exchange (IDX) for the 2021-2022 period. The sample of this research is five stocks that are candidate portfolios. The sampling method uses a purposive sampling method with the criteria of 5 stocks with the highest positive ratio. The population in this study was all 30 companies included in the IDX30, while the samples were five companies. Data were analyzed using a mean-variant optimization model with a research duration between May 2021 and May 2022. Based on the results of the investment portfolio optimization analysis on the 5 (five) selected stocks, this study shows that, out of 23 stocks, five stocks are eligible to enter the optimal portfolio with their respective proportions, namely PT Adaro Energy Indonesia Tbk (ADRO) 20%, PT Astra International Tbk (ASII) 26%, PT Merdeka Copper Gold Tbk (MDKA) 10%, PT XL Axiata Tbk (EXCL) 19%, PT Bukit Asam Tbk (PTBA) 25%. The portfolio of these stocks generates an expected return of 0.00217 at a risk level of 0.00022. It is hoped that this research can be helpful to add to the literature on investment optimization models, especially the concentration of Mathematics in Finance, and serve as an additional reference for further research, as well as an alternative for investors in optimizing investment portfolios.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"73 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83097224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stocks are one of the most popular forms of investment. In investing stocks, it is necessary to know the movement of stock prices and the investment risks that may occur. The purpose of this study is to predict the level of risk, see the characteristics of stock returns, and whether the ESG Risk Rating makes the company's stock performance better. The models used to predict stock returns are Auto Regressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticty (GARCH), and Value at Risk (VaR) is used to predict risk. Based on the research, the potential loss for Bank BCA is IDR29.800.000,00 and Bank Mandiri is IDR33.600.000,00 with the assumption that an investor invests as much as IDR1.000.000.000,00. In addition, Bank BCA has a lower ESG Risk Rating than Bank Mandiri, but has a better performance.
{"title":"Company Stock Performance Analysis on IDX ESG Leaders Index Using the ARIMA-GARCH Model","authors":"Hazelino Rafi Pradaswara, D. Susanti, S. Sukono","doi":"10.46336/ijqrm.v3i3.347","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i3.347","url":null,"abstract":"Stocks are one of the most popular forms of investment. In investing stocks, it is necessary to know the movement of stock prices and the investment risks that may occur. The purpose of this study is to predict the level of risk, see the characteristics of stock returns, and whether the ESG Risk Rating makes the company's stock performance better. The models used to predict stock returns are Auto Regressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticty (GARCH), and Value at Risk (VaR) is used to predict risk. Based on the research, the potential loss for Bank BCA is IDR29.800.000,00 and Bank Mandiri is IDR33.600.000,00 with the assumption that an investor invests as much as IDR1.000.000.000,00. In addition, Bank BCA has a lower ESG Risk Rating than Bank Mandiri, but has a better performance.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84424989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Catastrophe such as hurricanes, heavy rains, and similar occurrence pose serious threats and risks to fishermen's livelihoods as well as losses from damage to their assets. Therefore, it is necessary to have special insurance to protect the fishermen's assets from financial losses due to the risks that can occur, namely Fisherman Micro Insurance. Micro-insurance is an insurance product that is intended for low-income people with features and administration that are simple, easy to obtain, economical prices and immediately in the completion of the provision of compensation. Fisherman's micro insurance guarantees assets in the form of fishing equipment in the occurrence of a risk of an accident causing damage, this insurance product protects against worries without a large premium burden. This study aims to calculate the premium price with an aggregate risk model approach. The data used is data on fisherman’s losses if they did not go to sea which obtained by surveys. The occurrence data follows the Poisson distribution, and the loss data follows the Exponential distribution. Parameter Estimation was carried out using the Maximum Likelihood Estimation. The estimation results from numbers of occurrence and the amount of losses are used to estimate the collective risk model. Estimators of the average and variance of the aggregate risk are used to determine the premium. The results of the premium selection in this study amounted to IDR 153.861.958.00. The premium amount is a collective premium which is the result of a calculation based on the standard deviation principle.
{"title":"Determining the Price of Fisherman Micro Insurance Premiums Using the Aggregate Risk Model Approach in Cirebon Regency","authors":"R. Kusumadewi, Riaman Riaman, S. Sukono","doi":"10.46336/ijqrm.v3i3.346","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i3.346","url":null,"abstract":"Catastrophe such as hurricanes, heavy rains, and similar occurrence pose serious threats and risks to fishermen's livelihoods as well as losses from damage to their assets. Therefore, it is necessary to have special insurance to protect the fishermen's assets from financial losses due to the risks that can occur, namely Fisherman Micro Insurance. Micro-insurance is an insurance product that is intended for low-income people with features and administration that are simple, easy to obtain, economical prices and immediately in the completion of the provision of compensation. Fisherman's micro insurance guarantees assets in the form of fishing equipment in the occurrence of a risk of an accident causing damage, this insurance product protects against worries without a large premium burden. This study aims to calculate the premium price with an aggregate risk model approach. The data used is data on fisherman’s losses if they did not go to sea which obtained by surveys. The occurrence data follows the Poisson distribution, and the loss data follows the Exponential distribution. Parameter Estimation was carried out using the Maximum Likelihood Estimation. The estimation results from numbers of occurrence and the amount of losses are used to estimate the collective risk model. Estimators of the average and variance of the aggregate risk are used to determine the premium. The results of the premium selection in this study amounted to IDR 153.861.958.00. The premium amount is a collective premium which is the result of a calculation based on the standard deviation principle.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88123315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rahadatul Aisyi, Friska Anzalni, Yusuf Fajar, D. Suhaedi, Erwin Harahap
Mathematics is the basic foundation for other sciences. Equation is a mathematical model that can describe real-life problems, one of which is estimating non-tax state revenues in the coming year. Non-State Revenue (penerimaan negara bukan pajak, PNBP) is the scope of state finances which is equipped with the State Assets and Auction Service Office (kantor pelayanan keuangan negara dan lelang, KPKNL) which must be reported on the realization of PNBP that will be deposited into the state treasury. Such situation happens because expenditures in each government agency will be available and increase every year by the government. Therefore, direktorat jenderal keuangan negara (DJKN) have to be more optimal in the management of the PNBP. This study aims to determine the results of the best estimates and exponential models in estimating non-tax state income at the KPKNL Bandung, Indonesia, in year of 2017 and 2018. This research includes descriptive research using a qualitative approach. The results show that the calculation using the exponential 4th model is the best model for estimating PNBP such that the estimated PNBP results in 2017 is Rp. 574,775,677 and in 2018 is Rp. 798,022,691.
数学是其他科学的基础。方程是一种数学模型，可以描述现实生活中的问题，其中之一是估计未来一年的非税国家收入。非国家收入(penerimaan negara bukan pajak, PNBP)是国家财政的范围，配备国有资产和拍卖服务办公室(kantor pelayanan keuangan negara dan lelang, KPKNL)，必须在实现PNBP时报告，将存入国库。之所以会出现这种情况，是因为政府各部门的支出每年都会增加。因此，在PNBP的管理中，DJKN局长必须更加优化。本研究旨在确定2017年和2018年印度尼西亚万隆KPKNL估算非税国家收入的最佳估计和指数模型的结果。本研究包括使用定性方法的描述性研究。结果表明，使用指数4模型计算是估计PNBP的最佳模型，2017年的估计PNBP结果为Rp. 574,775,677, 2018年的估计PNBP结果为Rp. 798,022,691。
{"title":"Mathematical Modeling to Estimate Non-Tax State Revenues","authors":"Rahadatul Aisyi, Friska Anzalni, Yusuf Fajar, D. Suhaedi, Erwin Harahap","doi":"10.46336/ijqrm.v3i2.258","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i2.258","url":null,"abstract":"Mathematics is the basic foundation for other sciences. Equation is a mathematical model that can describe real-life problems, one of which is estimating non-tax state revenues in the coming year. Non-State Revenue (penerimaan negara bukan pajak, PNBP) is the scope of state finances which is equipped with the State Assets and Auction Service Office (kantor pelayanan keuangan negara dan lelang, KPKNL) which must be reported on the realization of PNBP that will be deposited into the state treasury. Such situation happens because expenditures in each government agency will be available and increase every year by the government. Therefore, direktorat jenderal keuangan negara (DJKN) have to be more optimal in the management of the PNBP. This study aims to determine the results of the best estimates and exponential models in estimating non-tax state income at the KPKNL Bandung, Indonesia, in year of 2017 and 2018. This research includes descriptive research using a qualitative approach. The results show that the calculation using the exponential 4th model is the best model for estimating PNBP such that the estimated PNBP results in 2017 is Rp. 574,775,677 and in 2018 is Rp. 798,022,691.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"94 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84293418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aims to analyze the influence of the agricultural sector on poverty in Aceh Province. In this study, the variables used in influencing the poverty level in Aceh Province are the share of Gross domestic product (GDP) in the agricultural sector, labor in the agricultural sector, agricultural land, Farmer Education and Gross Regional Domestic Product (GRDP) per capita. The regression model used in this study is the method of multiple linear regression analysis (ordinary least squares regression analysis) using panel data and a fixed effect approach (fixed effect model) to determine the effect between variables. The results of this study are based on a simultaneous test (Test F) which shows that overall, the independent variables (share of GDP in the agricultural sector, labor in the agricultural sector, agricultural land, Farmer Education and GRDP per capita together show their effect on the poverty level. The results of the study based on a partial test (t test) showed that the share of the agricultural sector GRDP and the GDP per capita variable had a negative and significant effect on poverty and agricultural sector labor had a positive and significant effect on poverty, while the variables of agricultural land and farmer education negative effect, but not significant. The value of Adjusted R-squared in this study is 0.868629. This shows that the 86.86 percent change in the dependent variable, namely the Poverty of Aceh Province, can be explained by the independent variable, namely Share of Agricultural GRDP, Agricultural Manpower, Agricultural Land, Farmer Education and Per Capita GRDP. While the remaining 13.14% is explained by other factors outside the model.
{"title":"The Effect of the Agriculture Sector on Poverty in Aceh Province","authors":"Ridho Fatwa, Srinita Srinita, M. Abrar","doi":"10.46336/ijqrm.v3i2.275","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i2.275","url":null,"abstract":"This study aims to analyze the influence of the agricultural sector on poverty in Aceh Province. In this study, the variables used in influencing the poverty level in Aceh Province are the share of Gross domestic product (GDP) in the agricultural sector, labor in the agricultural sector, agricultural land, Farmer Education and Gross Regional Domestic Product (GRDP) per capita. The regression model used in this study is the method of multiple linear regression analysis (ordinary least squares regression analysis) using panel data and a fixed effect approach (fixed effect model) to determine the effect between variables. The results of this study are based on a simultaneous test (Test F) which shows that overall, the independent variables (share of GDP in the agricultural sector, labor in the agricultural sector, agricultural land, Farmer Education and GRDP per capita together show their effect on the poverty level. The results of the study based on a partial test (t test) showed that the share of the agricultural sector GRDP and the GDP per capita variable had a negative and significant effect on poverty and agricultural sector labor had a positive and significant effect on poverty, while the variables of agricultural land and farmer education negative effect, but not significant. The value of Adjusted R-squared in this study is 0.868629. This shows that the 86.86 percent change in the dependent variable, namely the Poverty of Aceh Province, can be explained by the independent variable, namely Share of Agricultural GRDP, Agricultural Manpower, Agricultural Land, Farmer Education and Per Capita GRDP. While the remaining 13.14% is explained by other factors outside the model.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73967951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Public awareness in social and environmental sustainability became a challenge that turned into general assessments. ESG (Environmental, Social, Governance) performance became essential. Hence, the firm that does not apply ESG criteria in its business activities will face a consequence from investors impacting its performance, associated with financial risk. This study examines ESG performance within ESG score, ESG controversy, and BGD (Board Gender Diversity) on the total and systematic risk as a proxy for the financial risk of public companies listed on the stock exchange. This study uses a sample of 105 listed public firms from each stock exchange in ASEAN-5 (Philippines, Indonesia, Malaysia, Singapore, and Thailand) from 2016 to 2020 and applies panel regression analysis. The result suggests that ESG Score significantly influences total but not systematic risk in ASEAN-5. ESG controversy does not considerably affect total and systematic risk. BGD significantly influences total risk but not systematic risk. The findings will help investors and portfolio managers evaluate how ESG performance influences the firm's financial risk and make better investment decisions in ASEAN-5.
{"title":"Is There any Effect of ESG Performance in the Improvement of Financial Risk in ASEAN-5?","authors":"Nadia Rahma, R. Rokhim","doi":"10.46336/ijqrm.v3i2.274","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i2.274","url":null,"abstract":"Public awareness in social and environmental sustainability became a challenge that turned into general assessments. ESG (Environmental, Social, Governance) performance became essential. Hence, the firm that does not apply ESG criteria in its business activities will face a consequence from investors impacting its performance, associated with financial risk. This study examines ESG performance within ESG score, ESG controversy, and BGD (Board Gender Diversity) on the total and systematic risk as a proxy for the financial risk of public companies listed on the stock exchange. This study uses a sample of 105 listed public firms from each stock exchange in ASEAN-5 (Philippines, Indonesia, Malaysia, Singapore, and Thailand) from 2016 to 2020 and applies panel regression analysis. The result suggests that ESG Score significantly influences total but not systematic risk in ASEAN-5. ESG controversy does not considerably affect total and systematic risk. BGD significantly influences total risk but not systematic risk. The findings will help investors and portfolio managers evaluate how ESG performance influences the firm's financial risk and make better investment decisions in ASEAN-5.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82923652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thailand isa popular tourist country in southeast Asia where millions of tourists come to visit each year. However, most of the first visitors left the question why so few people have tourist behavior back to the destination of Thailand. The study is to find out how the image of destinations, access surveys affect the behavior behavior through the satisfaction of Indonesian tourists on the travel destination in Thailand. The research method used is quantitative, sample retrieval technique using non-sampling and obtained samples as much as 385 respondents, the analysis tools used are path analysis and hypotheses using the import analysis tools used by Amos and SPSS. The study suggests that the live test of destination image and access reading variables affected the behavioral test of Indonesian tourists on Thai tour destinations and then for the satisfaction of tourists able to improve the relationship between the image of destinations and the behavior of Indonesian tourists on the Thai tour destinations, it contributed by reviewing the behavior patterns of tourists in Indonesia while visiting the destination of tourism. The academic and managerial implications of this discovery are useful in devising a tourist destination country tourism strategy in Thailand.
{"title":"Thailand’s Destination Image and Intention to Visit Perception Tourist in Indonesia","authors":"Sunchai Gamon, A. Malee","doi":"10.46336/ijqrm.v3i2.271","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i2.271","url":null,"abstract":"Thailand isa popular tourist country in southeast Asia where millions of tourists come to visit each year. However, most of the first visitors left the question why so few people have tourist behavior back to the destination of Thailand. The study is to find out how the image of destinations, access surveys affect the behavior behavior through the satisfaction of Indonesian tourists on the travel destination in Thailand. The research method used is quantitative, sample retrieval technique using non-sampling and obtained samples as much as 385 respondents, the analysis tools used are path analysis and hypotheses using the import analysis tools used by Amos and SPSS. The study suggests that the live test of destination image and access reading variables affected the behavioral test of Indonesian tourists on Thai tour destinations and then for the satisfaction of tourists able to improve the relationship between the image of destinations and the behavior of Indonesian tourists on the Thai tour destinations, it contributed by reviewing the behavior patterns of tourists in Indonesia while visiting the destination of tourism. The academic and managerial implications of this discovery are useful in devising a tourist destination country tourism strategy in Thailand. ","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76715598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research is to determine factors that influenced Gross Regional Development Product (GRDP) Banda Aceh and Lhokseumawe city in context relationship between core and periphery using panel data regression of 23 districts/cities in Aceh Province, Indonesia year 2010-2020. Selected independent variables in this paper are GRDP core and periphery, population, distance between core and periphery, availability of hospital, availability of university and availability of industry. Based on estimation results, all independent variabels have significant effect toward GRDP Banda Aceh and Lhokseumawe city. Variabels that found have positive effect toward GRDP Banda Aceh city are GRDP core and periphery, and distance between core and periphery. Variabels that found have negative effect toward GRDP core Banda Aceh city are population, availability of hospital, availability of university and availability of industry. Then, variabels that found have positive effect toward GRDP Lhokseumawe city are GRDP core and periphery, distance between core and periphery, and availability of university. Variabels that found have negative effect toward GRDP core Lhokseumawe city are population, availability of hospital, and availability of industry. It is hoped that this findings will provide useful information for policymakers in attempt to enhance the competitiveness of regional economy.
{"title":"Analysis of Economic Growth Core and Periphery: Evidence from Aceh Province, Indonesia","authors":"Risnasari Risnasari, A. Jamal, S. Syahnur","doi":"10.46336/ijqrm.v3i2.277","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i2.277","url":null,"abstract":"This research is to determine factors that influenced Gross Regional Development Product (GRDP) Banda Aceh and Lhokseumawe city in context relationship between core and periphery using panel data regression of 23 districts/cities in Aceh Province, Indonesia year 2010-2020. Selected independent variables in this paper are GRDP core and periphery, population, distance between core and periphery, availability of hospital, availability of university and availability of industry. Based on estimation results, all independent variabels have significant effect toward GRDP Banda Aceh and Lhokseumawe city. Variabels that found have positive effect toward GRDP Banda Aceh city are GRDP core and periphery, and distance between core and periphery. Variabels that found have negative effect toward GRDP core Banda Aceh city are population, availability of hospital, availability of university and availability of industry. Then, variabels that found have positive effect toward GRDP Lhokseumawe city are GRDP core and periphery, distance between core and periphery, and availability of university. Variabels that found have negative effect toward GRDP core Lhokseumawe city are population, availability of hospital, and availability of industry. It is hoped that this findings will provide useful information for policymakers in attempt to enhance the competitiveness of regional economy.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74088906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Siti Rosa Lismawati, Candra Hadi Utomo, Fenty Fauziah
The purpose of this study was to determine and analyze the effect of cash holding and dividends on firm value in property and real estate companies listed on the Indonesia Stock Exchange, either partially or simultaneously. The quantitative type of research used in this study, the research population is all property and real estate companies listed on the Indonesia Stock Exchange for the 2010-2019 period and the sample selection technique uses purposive sampling so that a sample of companies is obtained. The data collection techniques with documentation and are secondary data used in research. The data analysis technique used is panel data with the help of a statistical data processing program called Eviews 9. The results of the study, cash holding partially has a negative and insignificant effect on firm value, while dividends partially have a positive and significant effect on firm value, while simultaneously cash holding and dividends have a significant effect on firm value.
{"title":"Influence of Cash Holding and Dividend Against Firm Value on Property Company and Real Estate Listed on the Indonesia Stock Exchange","authors":"Siti Rosa Lismawati, Candra Hadi Utomo, Fenty Fauziah","doi":"10.46336/ijqrm.v3i2.272","DOIUrl":"https://doi.org/10.46336/ijqrm.v3i2.272","url":null,"abstract":"The purpose of this study was to determine and analyze the effect of cash holding and dividends on firm value in property and real estate companies listed on the Indonesia Stock Exchange, either partially or simultaneously. The quantitative type of research used in this study, the research population is all property and real estate companies listed on the Indonesia Stock Exchange for the 2010-2019 period and the sample selection technique uses purposive sampling so that a sample of companies is obtained. The data collection techniques with documentation and are secondary data used in research. The data analysis technique used is panel data with the help of a statistical data processing program called Eviews 9. The results of the study, cash holding partially has a negative and insignificant effect on firm value, while dividends partially have a positive and significant effect on firm value, while simultaneously cash holding and dividends have a significant effect on firm value.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"99 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72838603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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