Perbandingan Kontribusi Bruto Asuransi Syariah Sebelum dan Sesudah Pandemi Covid-19

AbstractIslamic insurance has a big role in the Islamic finance sector with the principle of mutual help. Gross contribution is one of the funds that can be utilized for insurance participants and companies. Covid19, which has an impact on the economic sector, makes understanding the growth of sharia insurance before and after the pandemic in terms of gross contribution very important. This study aims to further review the gross contribution from March-December to find out whether there is a significant difference from the gross contribution of sharia insurance before and after the Covid-19 pandemic. The study was conducted using a comparative quantitative approach with two paired samples. The research sample uses time series data, namely the gross contribution of sharia insurance in 2019 and 2020 for the period from March to December. The results of this study found that the comparison of gross contribution to the Islamic insurance industry seen before the 2019 pandemic and after the 2020 pandemic which was taken from March to December was normally distributed. This means that the development of sharia insurance when viewed before the 2019 pandemic and after the 2020 pandemic according to the gross contributions from sharia insurance participants did not experience a significant difference and will certainly increase.AbstrakAsuransi syariah memiliki peran besar pada sektor keuangan syariah dengan prinsip saling tolongmenolong. Kontribusi bruto merupakan salah satu dana yang dapat dimanfaatkan bagi peserta asuransi maupun perusahaan. Covid-19 yang berdampak pada sektor perekonomian, menjadikan pemahaman mengenai pertumbuhan asuransi syariah sebelum dan sesudah pandemi ditinjau dari kontribusi bruto sangat penting. Penelitian ini bertujuan untuk meninjau lebih lanjut kontribusi bruto dari Maret-Desember untuk mengetahui apakah ada perbedaan yang signifikan dari kontribusi bruto asuransi syariah sebelum dan sesudah pandemi Covid-19. Penelitian dilakukan dengan pendekatan kuantitatif komparatif dengan dua sampel berpasangan. Sampel penelitian menggunakan data time series yaitu kontribusi bruto asuransi syariah tahun 2019 dan 2020 periode bulan Maret hingga Desember. Hasil penelitian ini menemukan bahwa perbandingan kontribusi bruto pada industri asuransi syariah dilihat saat sebelum pandemi tahun 2019 dan sesudah pandemi 2020 yang diambil pada periode Maret hingga Desember berdistribusi normal. Hal tersebut berarti bahwa perkembangan asuransi syariah jika ditinjau pada saat sebelum pandemi tahun 2019 dan sesudah pandemi tahun 2020 menurut kontribusi bruto yang berasal dari para peserta asuransi syariah tidak mengalami perbedaan yang signifikan dan dapat dipastikan akan mengalami peningkatan.

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Magnetospheric chaos and dynamical complexity response during storm time disturbance

10.5194/npg-2020-47 ◽

2020 ◽

Author(s):

Irewola Aaron Oludehinwa ◽

Olasunkanmi Isaac Olusola ◽

Olawale Segun Bolaji ◽

Olumide Olayinka Odeyemi ◽

Abdullahi Ndzi Njah

Keyword(s):

Time Series ◽

Solar Wind ◽

Geomagnetic Storm ◽

Time Series Data ◽

Geomagnetic Storms ◽

Approximate Entropy ◽

Series Data ◽

Dynamical Complexity ◽

Significant Difference ◽

Dynamical Features

Abstract. In this study, we examine the magnetospheric chaos and dynamical complexity response in the disturbance storm time (Dst) and solar wind electric field (VBs) during different categories of geomagnetic storm (minor, moderate and major geomagnetic storm). The time series data of the Dst and VBs are analyzed for the period of nine years using nonlinear dynamics tools (Maximal Lyapunov Exponent, MLE, Approximate Entropy, ApEn and Delay Vector Variance, DVV). We found a significant trend between each nonlinear parameter and the categories of geomagnetic storm. The MLE and ApEn values of the Dst indicate that chaotic and dynamical complexity response are high during minor geomagnetic storms, reduce at moderate geomagnetic storms and declined further during major geomagnetic storms. However, the MLE and ApEn values obtained in VBs indicate that chaotic and dynamical complexity response are high with no significant difference between the periods that are associate with minor, moderate and major geomagnetic storms. The test for nonlinearity in the Dst time series during major geomagnetic storm reveals the strongest nonlinearity features. Based on these findings, the dynamical features obtained in the VBs as input and Dst as output of the magnetospheric system suggest that the magnetospheric dynamics is nonlinear and the solar wind dynamics is consistently stochastic in nature.

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Analisis pengaruh kredit perbankan, pembiayaan bank syariah dan investasi terhadap pertumbuhan ekonomi di Indonesia periode sebelum pandemi Covid-19 (2015-2019) dan periode pandemi Covid-19 tahun 2020

Jurnal Ekonomi, Bisnis dan Pendidikan ◽

10.17977/um066v1i92021p844-853 ◽

2021 ◽

Vol 1 (9) ◽

pp. 844-853

Author(s):

Deni Andrean ◽

Imam Mukhlis

Keyword(s):

Economic Growth ◽

Time Series ◽

Financial Services ◽

Time Series Data ◽

T Test ◽

Series Data ◽

Islamic Banking ◽

Negative Effects ◽

Paired Samples ◽

Banking Credit

Abstract This study aims to identify the effects of conventional banking credit, Islamic banking financing, PMA and PMDN investment on Indonesia’s economic growth in the before (2015-2019) and after (2019-2020) Covid-19. This study used quantitative method with VAR/VECM analysis. In this study, the time series data were analyzed using eviews 10, while the comparison between before (2019) and after (2020) Covid-19 was carried out using paired samples t-test. The data were collected from various sources, including Financial Services Authority and central Bureau of Statistics. The findings show that the total investment carries significant negative effects on Indonesia’s economic growth, while conventional banking credit carries no effect on Indonesia economic growth. The Islamic banking financing brings positive significant effects in long-term toward Indonesia economic growth. Abstrak Penelitian ini bertujuan untuk mengetahui pengaruh antara kredit perbankan konvensional, pembiayaan perbankan syariah dan investasi PMA dan PMDN terhadap pertumbuhan ekonomi di Indonesia pada periode sebelum covid -19 tahun 2015 sampai 2019 dan periode covid-19 tahun 2019-2020. Penelitian ini menerapkan metode penelitian kuantitatif menggunakan analisis VAR/VECM dengan menggunakan data time series dan diolah menggunakan eviews 10, dan perbandingan perbedaan antara seluruh variabel dari tahun sebelum pandemi (2019) dan setelah adanya pandemic (2020) menggunakan pengujian Uji Beda Paired Samples t-test, data ini dikumpulkan dari berbagai sumber utama termasuk Otoritas Jasa Keuangan (OJK) dan Badan Pusat Statistik (BPS). Temuan ini menunjukkan bahwa total investasi berpengaruh negatif signifikan terhadap pertumbuhan ekonomi di Indonesia, kredit perbankan konvensional tidak berpengaruh terhadap pertumbuhan ekonomi di Indonesia. Sedangkan pada variabel pembiayaan perbankan syariah menunjukkan bahwa pembiayaan perbankan syariah berpengaruh positif signifikan dalam jangka panjang terhadap pertumbuhan ekonomi di Indonesia

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Use of e-cigarettes by young people in Great Britain before and after Tobacco Products Directive

European Journal of Public Health ◽

10.1093/eurpub/ckz185.117 ◽

2019 ◽

Vol 29 (Supplement_4) ◽

Author(s):

G Moore ◽

R Brown ◽

N Page ◽

B Hallingberg ◽

L Gray ◽

...

Keyword(s):

Time Series ◽

Young People ◽

School Health ◽

Time Series Data ◽

Research Network ◽

Series Data ◽

Initial Increase ◽

Cigarette Use ◽

Tobacco Products ◽

Before And After

Abstract Background Young people’s experimentation with e-cigarettes has increased in recent years, although regular use remains rare. In May 2016, the EU Tobacco Products Directive (TPD) introduced regulations aimed in part at preventing use by young people. It imposed warnings on e-cigarette packets, banned many forms of advertising, and restricted nicotine strength. This paper examines change in young people’s e-cigarette use after TPD, as well as complementary and alternative causal explanations for change, from young people’s perspectives. Methods Quantitative data sources were 2013, 2015 and 2017 School Health Research Network/Health Behaviour in School-aged Children surveys in Wales and 2014 and 2016 Smoking Drinking and Drug Use surveys in England. Data were analysed using segmented binary logistic regression in Wales, with simpler before and after analyses in England. Results were considered alongside qualitative interview data from young people aged 14-15 years in England, Wales and Scotland, collected in 2017 and 2018. Results Ever-use of e-cigarettes almost doubled from 2013-15, though subsequent increases were smaller. In Wales, where pre-legislation time series data were available, under a range of assumptions, prior growth in e-cigarette ever-use did not continue post-TPD. Change in trend post-TPD did not reach significance (OR = 0.96; 95%CI=0.91 to 1.01), but became significant after adjusting for change in smoking rates across the time-series (OR = 0.93; 95%CI=0.88 to 0.98). Regular use did not increase significantly from 2015 to 2017 in Wales, although ever and regular use in England both increased from 2014 to 2016. Young people described limited interactions with core components of TPD, while commonly describing e-cigarette use as a fad which was beginning to run its course. Conclusions Growth in youth experimentation with e-cigarettes may be slowing. Qualitative data from young people provide a range of explanations which appear largely unrelated to TPD itself. Key messages Survey data provide preliminary evidence that use of e-cigarettes may be plateauing among young people in the UK after a rapid initial increase in experimentation. Explanations position e-cigarettes as a passing fad which is beginning to lose its appeal in UK youth. Longer term monitoring of trends and perceptions remain vital.

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The Impact of Macroeconomic Indicator on Islamic Insurance Demand in Indonesia

Al-Iqtishad Journal of Islamic Economics ◽

10.15408/aiq.v11i2.7690 ◽

2019 ◽

Vol 11 (2) ◽

Author(s):

Salahuddin El Ayyubi ◽

W Widyastutik ◽

A. Anditta

Keyword(s):

Time Series Data ◽

Insurance Industry ◽

Least Square ◽

Series Data ◽

Insurance Demand ◽

Ordinary Least Square ◽

Macroeconomic Indicators ◽

Islamic Insurance ◽

The Impact ◽

Macroeconomic Indicator

This research aimed to determine the development of Islamic insurance industry in Indonesia and analyze the influence of macroeconomic indicators Islamic insurance demand in Indonesia. Ordinary Least Square (OLS) was used in this research with monthly time series data from January 2014 to December 2016. The results of this research indicated that the variables of money supply, interest rate, GDP per capita, and education had a positive (significant) effect to the Islamic insurance demand in Indonesia. Moreover, the inflation variable and dependency ratio had a negative (significant) effect to the Islamic insurance demand in Indonesia.

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DAMPAK KETIDAKSTABILAN NILAI TUKAR RUPIAH TERHADAP PERMINTAAN UANG M2 DI INDONESIA

Jurnal Ekonomi Pembangunan Kajian Masalah Ekonomi dan Pembangunan ◽

10.23917/jep.v9i2.1020 ◽

2008 ◽

Vol 9 (2) ◽

pp. 121

Author(s):

Etty Puji Lestari

Keyword(s):

Time Series ◽

Impulse Response ◽

Time Series Data ◽

Research Result ◽

Forecast Model ◽

Variance Decomposition ◽

Series Data ◽

Stationary Condition ◽

Before And After ◽

Structural Innovation

This article attempts to estimate demand for M2 money in Indonesia using time series non-stationary technique in 1997.1 - 2006.4. There are four methods are used in research, first, VAR estimation used to forecast model which have interaction of data time series. Second, function impulse response to see response from every variable to structural innovation of the other variables at the same time. Third, variance decomposition to know dissociating variation change of shock from each variable to other variables in model. Fourth method, ADL ECM to see long-range adjustment in variable, before and after addition of variable. The result, there are non-stationary condition in the time series data in the research. Result of VAR estimation show that there is no causality relation two ways among fifth of variable. From impulse, response known that response of M2 variable to other variable very fluctuative but finally the condition will return to stabilize.

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Effects of Speed Limit Enforcement Cameras on Accident Rates

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1830-04 ◽

2003 ◽

Vol 1830 (1) ◽

pp. 25-33 ◽

Cited By ~ 12

Author(s):

Stephane Hess ◽

John Polak

Keyword(s):

Time Series ◽

Time Series Data ◽

Series Data ◽

Speed Limit ◽

Regression To The Mean ◽

Average Decrease ◽

The Best Approximation ◽

Before And After ◽

Accident Data ◽

Accident Rates

Speed limit enforcement cameras (SLECs) have been in operation in Great Britain since 1991. However, there is still considerable dispute regarding their effectiveness in reducing accident rates. The aim of this research was to analyze the effects of SLECs on accident rates in Cambridgeshire, United Kingdom, using time series data collected over an 11-year period. A time series analysis of the accident data revealed the presence of both trend and seasonality components. A method was developed to remove the influence of these two components from the data and compare mean accident levels before and after installation of the camera. The method was also constructed in such a way that it would be able to distinguish between the actual effects of the camera installation and the effects of regression to the mean. The initial investigation into the effects of SLECs showed an average decrease over sites in the monthly accident frequency by around 18%; a more detailed analysis suggested that the best approximation of the effect of the introduction of a SLEC is a decrease in injury accidents by 31.26%, thus giving clear evidence that SLECs do indeed contribute to a significant decrease in accident numbers.

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Impact of the As Samra wastewater treatment plant upgrade on the water quality (COD, electrical conductivity, TP, TN) of the Zarqa River

Water Science & Technology ◽

10.2166/wst.2013.686 ◽

2013 ◽

Vol 67 (7) ◽

pp. 1455-1464 ◽

Cited By ~ 8

Author(s):

A. Al-Omari ◽

Z. Al-houri ◽

R. Al-Weshah

Keyword(s):

Water Quality ◽

Electrical Conductivity ◽

Time Series ◽

Wastewater Treatment ◽

Time Series Data ◽

Wastewater Reuse ◽

Treatment Plant ◽

Series Data ◽

Before And After ◽

Zarqa River

The impact of the As Samra wastewater treatment plant upgrade on the quality of the Zarqa River (ZR) water was investigated. Time series data that extend from October 2005 until December 2009 obtained by a state-of-the-art telemetric monitoring system were analyzed at two monitoring stations located 4 to 5 km downstream of the As Samra effluent confluence with the Zarqa River and about 25 km further downstream. Time series data that represent the ZR water quality before and after the As Samra upgrade were analyzed for chemical oxygen demand (COD), electrical conductivity (EC), total phosphorus (TP) and total nitrogen (TN). The means of the monitored parameters, before and after the As Samra upgrade, showed that the reductions in the COD, TP and TN were statistically significant, while no reduction in the EC was observed. Comparing the selected parameters with the Jordanian standards for reclaimed wastewater reuse in irrigation and with the Ayers & Westcot guidelines for interpretation of water quality for irrigation showed that the ZR water has improved towards meeting the required standards and guidelines for treated wastewater reuse in irrigation.

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Insurance Customer Authentication Using SVM and Financial Time Series Analysis for Mobile Applications

Webology ◽

10.14704/web/v17i2/web17079 ◽

2020 ◽

Vol 17 (2) ◽

pp. 945-956

Author(s):

R. Harikrishnan ◽

R. Jebakumar ◽

S. Ganesh Kumar ◽

Amu tha

Keyword(s):

Time Series ◽

Support Vector Machine ◽

Mobile Applications ◽

Time Series Data ◽

Financial Time Series ◽

Mobile Apps ◽

Insurance Industry ◽

Series Data ◽

Support Vector ◽

Financial Time

Insurance industry facilitates the users to access the information easily in their jobs without the repetition of password and remember the multiple passwords. Current technology attracts the insurers in authentication process. The identity authentification processes requires the customers to jump through the many hoops, which construct an unpleasant customer experience. The proposed method reduces the challenges in insurance business data using the classification algorithms using the support vector machine (SVM)for the mobile Applications since the growing trend in mobile apps will make it easy for the users. A seasonal variations and correlation in this financial time series data using statistical methods and ultimately generate trading signals for the insurance data. The feature extraction process increases the user security. The classification process improves different level of user identity. The support vector machine increases the data validation process quickly. Finally the proposed work enhances the user authentication process. The frame work is implemented using the matlabR2014 software and results were simulated for mobile apps.

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Magnetospheric chaos and dynamical complexity response during storm time disturbance

Nonlinear Processes in Geophysics ◽

10.5194/npg-28-257-2021 ◽

2021 ◽

Vol 28 (2) ◽

pp. 257-270

Author(s):

Irewola Aaron Oludehinwa ◽

Olasunkanmi Isaac Olusola ◽

Olawale Segun Bolaji ◽

Olumide Olayinka Odeyemi ◽

Abdullahi Ndzi Njah

Keyword(s):

Time Series ◽

Solar Wind ◽

Geomagnetic Storm ◽

Time Series Data ◽

Geomagnetic Storms ◽

Approximate Entropy ◽

Series Data ◽

Dynamical Complexity ◽

Significant Difference ◽

Non Linear

Abstract. In this study, we examine the magnetospheric chaos and dynamical complexity response to the disturbance storm time (Dst) and solar wind electric field (VBs) during different categories of geomagnetic storm (minor, moderate and major geomagnetic storm). The time series data of the Dst and VBs are analysed for a period of 9 years using non-linear dynamics tools (maximal Lyapunov exponent, MLE; approximate entropy, ApEn; and delay vector variance, DVV). We found a significant trend between each non-linear parameter and the categories of geomagnetic storm. The MLE and ApEn values of the Dst indicate that chaotic and dynamical complexity responses are high during minor geomagnetic storms, reduce at moderate geomagnetic storms and decline further during major geomagnetic storms. However, the MLE and ApEn values obtained from VBs indicate that chaotic and dynamical complexity responses are high with no significant difference between the periods that are associated with minor, moderate and major geomagnetic storms. The test for non-linearity in the Dst time series during major geomagnetic storm reveals the strongest non-linearity features. Based on these findings, the dynamical features obtained in the VBs as input and Dst as output of the magnetospheric system suggest that the magnetospheric dynamics are non-linear, and the solar wind dynamics are consistently stochastic in nature.

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Linkage Effects Mining in Stock Market Based on Multi-Resolution Time Series Network

Information ◽

10.3390/info9110276 ◽

2018 ◽

Vol 9 (11) ◽

pp. 276 ◽

Cited By ~ 1

Author(s):

Lingyu Xu ◽

Huan Xu ◽

Jie Yu ◽

Lei Wang

Keyword(s):

Time Series ◽

Stock Market ◽

Time Series Data ◽

Financial Time Series ◽

Investment Strategy ◽

Series Data ◽

Policy Makers ◽

Evolution Characteristics ◽

Before And After ◽

Linkage Effects

Previous research on financial time-series data mainly focused on the analysis of market evolution and trends, ignoring its characteristics in different resolutions and stages. This paper discusses the evolution characteristics of the financial market in different resolutions, and presents a method of complex network analysis based on wavelet transform. The analysis method has proven the linkage effects of the plate sector in China’s stock market and has that found plate drift phenomenon occurred before and after the stock market crash. In addition, we also find two different evolutionary trends, namely the W-type and M-type trends. The discovery of linkage plate and drift phenomena are important and referential for enterprise investors to build portfolio investment strategy, and play an important role for policy makers in analyzing evolution characteristics of the stock market.

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