(searched for: Determinant Factors of Jakarta Composite Index)
Published: 3 March 2021
European Journal of Business and Management Research, Volume 6, pp 18-22; doi:10.24018/ejbmr.2021.6.2.755
This study aims to examine empirically the influence of macroeconomic variables, namely: GDP growth, inflation, Rupiah exchange rates, and interest rates on the JCI on the Indonesia Stock Exchange. The analysis technique used is multiple regression. The results of the study found that only GDP growth and exchange rates had a significant effect on the JCI, while the inflation rate and interest rates had no effect on the JCI. This study only uses four macroeconomic variables, so further research needs to find other macroeconomic variables that are thought to have an effect on the JCI.
Published: 30 November 2020
Jurnal Statistika Universitas Muhammadiyah Semarang, Volume 8, pp 134-143; doi:10.26714/jsunimus.8.2.2020.134-143
The capital market is one of the economic drivers and representations for assessing the condition of companies in a country. Indonesia Stock Exchange (IDX) as one of the institutions in the capital market has 24 types of indexes that can be used as main indicators that reflect the performance of capital market, two of them are the Composite Stock Price Index (CSPI) and the Jakarta Islamic Index (JII). CSPI and JII movements are influenced by several factors, both from domestic and from foreign, such as inflation and the Dow Jones Industrial Average (DJIA). Modeling of CSPI and JII in this study was carried out using biresponses spline truncated nonparametric regression methods using Graphical User Interface (GUI) R with the intention of facilitating the analysis process. This method is used because there is a correlation between CSPI and JII and there is no specific relationship pattern between the response variable (CSPI and JII) and the predictor variable (inflation and DJIA). The best biresponses spline truncated model is determined by the order, number and location of the knots seen based on minimum GCV criteria. By using monthly data from January 2016 to December 2019, the best biresponses spline truncated model is obtained when the model for CSPI is in order 2 and the model for JII is in order 3 with 2 knots for each predictor variable. This model has a coefficient of determination of 85,54437% and MAPE of 2,65595% so that it has a very good ability in forecasting.
Published: 10 March 2020
DIALEKTIKA : Jurnal Ekonomi dan Ilmu Sosial, Volume 5, pp 53-56; doi:10.36636/dialektika.v5i1.411
Abstrak Indeks Harga Saham Gabungan (IHSG) merupakan cerminan perekonomian Indonesia, saat IHSG menunjukan peningkatan berarti perekonomian Indonesia berada dalam keadaan yang kondusif dan sebaliknya. Untuk dapat mengetahui apa saja yang dapat membantu pergerakan IHSG perlu diperhatikan beberapa faktor seperti tingkat suku bunga SBI, inflasi. Tujuan penelitian ini adalah untuk mengetahui pengaruh suku bunga SBI, Inflasi terhadap IHSG. Penelitian ini dilakukan di BEI dengan menggunakan sampel sebanyak 12 (Tahun 2018) terdiri dari data bulanan seluruh variable selama tahun 2018 dengan pemilihan sampel melalui metode non probabability sampling yaitu dengan metode purposive sampling dan data dianalisis dengan teknik analisis regresi linier berganda. Berdasarkanhasil analisis ditemukan suku bunga SBI, inflasi,berpengaruh terhadap IHSG. Suku bunga SBI, inflasi secara parsial berpengaruh negatif signifikan terhadap IHSG, hal ini berarti peningkatan suku bunga SBI, inflasi dapat mengakibatkan penurunan nilai IHSG. Kata kunci: IHSG,SBI,inflasi Abstract Composite Stock Price Index (CSPI) is a reflection of the Indonesian economy, while JCI showed significant improvement of the Indonesian economy is in a state that is conducive and vice versa. To be able to know anything that can help JCI to consider several factors such as SBI interest rate, inflation. The purpose of this study was to determine the effect of SBI rates, inflation against JCI. The research was conducted on the Stock Exchange by using a sample of 12 (2018) consists of monthly data across variables during 2018 with the selection of the sample through a non probabability method is the method of purposive sampling samplingdan Data were analyzed by multiple linear regression analysis technique. Berdasarkanhasil analysis found SBI interest rates, inflation, affect the JCI. SBI interest rates, inflation partially significant negative effect on the JCI, this means an increase in SBI rates inflation can lead to impairment of JCL. Keywords: JCI, SBI, inflation
Published: 1 January 2020
Proceedings of the Tarumanagara International Conference on the Applications of Social Sciences and Humanities (TICASH 2019) pp 15-22; doi:10.2991/assehr.k.200515.004
Conference: Tarumanagara International Conference on the Applications of Social Sciences and Humanities (TICASH 2019), 2019-6-27 - 2019-6-28
This research was aimed to finding out whether it’s related to the Exchange Rate of Rp/USD, Net Foreign Fund (NFF), Consumer Price Index (CPI) to the Jakarta Composite Index (JCI). The population are all data on the exchange rate of Rp/USD, data on all share purchases by foreign investors, all data on the Consumer Price Index on BPS and data on the JCI on the IDX. The sample selection method is a purposive using two kinds of data (daily and monthly). The results of this study are that there is a significant difference in the IDR / USD exchange rate against the JCI, and there is no influence on the NFF and CPI on the JCI on monthly data using the OLS model, while the research studies on daily data are associated with significant IDR / USD, and NFF towards the JCI using the GARCH model. The results of by using GARCH (1,1) indicate that the NFFF variable is the most important determinant for JCI. This is based on observations testing various variations of the GARCH model, the t-test value of NFFF is always higher than the KURS. This finding confirms that the IDX is still driven by foreign investors.
Published: 22 February 2018
IOP Conference Series: Earth and Environmental Science, Volume 123; doi:10.1088/1755-1315/123/1/012032
Recently, a highway development is required as a liaison between regions to support the economic development of the regions. Even the availability of highways give positive impacts, it also has negative impacts, especially related to the changes of vegetated lands. This study aims to determine the change of vegetation coverage in Jagorawi corridor Jakarta-Bogor during 37 years, and to analyze landscape patterns in the corridor based on distance factor from Jakarta to Bogor. In this study, we used a long-series of Landsat images taken by Landsat 2 MSS (1978), Landsat 5 TM (1988, 1995, and 2005) and Landsat 8 OLI/TIRS (2015). Analysis of landscape metrics was conducted through patch analysis approach to determine the change of landscape patterns in the Jagorawi corridor Jakarta-Bogor. Several parameters of landscape metrics used are Number of Patches (NumP), Mean Patch Size (MPS), Mean Shape Index (MSI), and Edge Density (ED). These parameters can be used to provide information of structural elements of landscape, composition and spatial distribution in the corridor. The results indicated that vegetation coverage in the Jagorawi corridor Jakarta-Bogor decreased about 48% for 35 years. Moreover, NumP value increased and decreasing of MPS value as a means of higher fragmentation level occurs with patch size become smaller. Meanwhile, The increase in ED parameters indicates that vegetated land is damaged annually. MSI parameter shows a decrease in every year which means land degradation on vegetated land. This indicates that the declining value of MSI will have an impact on land degradation.
Published: 7 December 2017
State-of-the-Art Theories and Empirical Evidence pp 27-39; doi:10.1007/978-981-10-6926-0_2
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AL-MUZARA'AH, Volume 1, pp 39-55; doi:10.29244/jam.1.1.39-55
Jakarta Islamic Index (JII) is a reference for investors to place their fund in Indonesia Stock Exchange which is in line with Islamic teaching. It has a specific requirements (screening process) which must be passed by one stock to be included in JII. Nevertheless, the screening process of JII composition is seen to have limitations because the process is merely based on the quantitative and qualitative criteria. Therefore, this research explores and analyzes the deeper aspects (Othman, et al., 2009) which is called as Islamic Social Reporting (ISR). ISR analyzes the compliance to Islamic teaching application from the company perspective. The research period is from the year of 2006 until 2008, while the research sample is taken from companies listed in the JII. This research adopts full interaction model to determine significant factors of ISR. Previous research did not apply the interaction model theory, i.e. the Difference in Difference (DiD) theory1. It can show meaningful existence of dummy variable with other proxies. The proxies used in this study are industry type, company size, and profitability. The results show that there are no differences among the industry type, while the company size affects the ISR.