Articles
<![CDATA[ISLAMIC BANK AND MONETARY POLICY: THE CASE OF INDONESIA ]]>
<![CDATA[Ponziani, Regi Muzio]]>;
<![CDATA[Mariyanti, Tatik]]>
<![CDATA[ International Journal of Islamic Economics and Finance (IJIEF) Vol 3, No 1 (2020): IJIEF Vol 3 (1), January 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/ijief.2124
<![CDATA[Islamic bank in Indonesia exists side by side with its conventional counterpart within dual banking system, while the central bank aims to achieve price stability in the economy using conventional and Islamic monetary instruments within dual monetary system. This posits a very unique environment for Islamic bank. This research aims to examine the role of Islamic bank in monetary policy transmission mechanism using Granger Causality and Autoregressive Distributed Lag (ARDL). The balance sheet components of deposit and financing were hypothesized to function in monetary transmission process within bank financing channel. Granger causality revealed that Islamic interbank overnight rate granger causes Islamic deposit and financing. Islamic deposit and financing granger cause industrial production index. Industrial production index granger cause inflation, Islamic deposit, and Islamic interbank overnight rate. Islamic deposit and inflation granger cause Islamic interbank overnight rate. The ARDL results showed that there were cointegrating relationships in the output and inflation model. Long-term convergence could be reached to correct deviations in output and inflation by way of Islamic banks? deposit and financing. However, short-term influence is contributed only by Islamic banks? deposit to output. Islamic banks? deposit does not contribute in the short-run to inflation. Islamic banks? financing does not have short-term relationship with output and inflation. Hence, there is a declining effectiveness of Islamic banks? financing contribution to the economy.]]>
<![CDATA[NILAI PERUSAHAAN PADA PERUSAHAAN NONKEUANGAN YANG TERDAFTAR DI BEI ]]>
<![CDATA[REGI MUZIO PONZIANI]]>;
<![CDATA[RISMA AZIZAH]]>
<![CDATA[ Jurnal Bisnis dan Akuntansi Vol 19 No 1a-3 (2017): Jurnal Bisnis dan Akuntansi ]]>
Publisher : <![CDATA[Pusat Penelitian dan Pengabdian Masyarakat Sekolah Tinggi Ilmu Ekonomi Trisakti ]]>
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DOI: 10.34208/jba.v19i1a-3.286
<![CDATA[The purpose of this study is to obtain an empirical evidenceabout the factors that affect firm value in nonfinancial companies. Independent variables used in this research are financial leverage, firm size, profitability, earnings per share, intangible asset, audit committee, insider holdings, and industry. This research used companies listed in nonfinancial sector in Indonesia Stock Exchange during 2013-2015. There are 86 companies meet the criteria by using purposive sampling method. The model used in this research is multiple regression analysis with IBM SPSS Version 21. The result shows that return on assets and earnings per sharehave influence toward firm value. Financial leverage, firm Size, intangible asset, audit committee, insider holdings, and industry have no influence toward firm value.]]>
<![CDATA[Forecasting of Jakarta Islamic Index (JII) returns using Holt-Winters family models ]]>
<![CDATA[Regi Muzio Ponziani]]>
<![CDATA[ Asian Journal of Islamic Management (AJIM) VOLUME 3 ISSUE 2, 2021 ]]>
Publisher : <![CDATA[Faculty of Business & Economics, Universitas Islam Indonesia ]]>
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DOI: 10.20885/AJIM.vol3.iss2.art4
<![CDATA[Purpose: This research aims to forecast JII returns by employing various Holt-Winters models. The models used in this research are Holt-Winters seasonality, Holt-Winters damped method, and Holt-Winters with maximum likelihood approach. Holt-Winters model is capable of recognizing and modeling trends and seasonality. Therefore, it is suitable for forecasting purposes.Methodology: Three models are employed in this research. The first one is Holt-Winters seasonality, also known as triple exponential smoothing. This model analyzes the level, trend, and seasonality components in the return series. The second model is the Holt-Winters damped method that uses smoothing parameters to lower the overstatement effect that usually occurs within Holt-Winters seasonality. The third model is Holt-Winters with Maximum Likelihood. Holt-Winters seasonality estimates parameters by choosing the least-squares. At the same time, Holt-Winters with Maximum Likelihood uses maximum likelihood to fit in the series with certain distributions and generate forecasts by determining distributions with the most likelihood.Findings: The result showed that Holt-Winters seasonality forecasts better than the other methods. The model could recognize the seasonal pattern and trend of the JII returns. It has the lowest Root Mean Squared Error (RMSE) as the parameter for forecast accuracy. Holt-Winters damped method has accuracy right below Holt-Winters seasonality. It can also map the pattern and trend of the returns. Holt-Winters with Maximum likelihood predicts less accurately. However, it can recognize the random walk inclination of the return, although it failed to generate the seasonal pattern and trend of the JII returns.Originality: This research attempted to apply Holt-Winters models to predict JII returns. Most research concerning the Islamic stock index focuses on volatility and forecast based on the level of volatility. Therefore, this research can fill in the gaps in the literature in which forecast of Islamic stock index can be conducted by modeling the seasonality and trend using Holt-Winters models.Practical implications: Investors always try to find the best generating investment return. Investors concerned with the shariah rules will always find lawful investment tools such as Islamic stocks or the Islamic stock index. Returns of the Islamic stock index can be forecast by using the Holt-Winters model. Therefore, investors might know the pattern of returns generated by investing in Islamic stocks.]]>
<![CDATA[Determinan internal dan external dari profitabilitas Bank Perkreditan Rakyat ]]>
<![CDATA[Regi Muzio Ponziani]]>
<![CDATA[ Jurnal Akuntansi, Manajemen dan Ekonomi Vol 24 No 1 (2022): Vol 24, No 1, 2022 ]]>
Publisher : <![CDATA[Faculty of Economics and Business, Jenderal Soedirman University ]]>
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DOI: 10.32424/1.jame.2022.24.1.5212
<![CDATA[This research aims to investigate how internal and external factor influence the rate of profitability of rural banks in Indonesia. Internal factors are factors within the bank itself, namely core capital, loan to deposit ratio, and nonperforming loan ratio. External factors are macroeconomics variables uncontrollable to the rural banks, such as inflation and interest rate. VECM test proved the existence of cointegration function. Any deviation from last period will be adjusted at the rate of 8.863%. In the long-run, core capital and inflation affect rural banks’ performance. Impulse response function indicated that any shocks that occurred to core capital, inflation, loan to deposit ratio and nonperforming loan had the inhibiting effect on rural banks’ performance. On the other hand, interest rate was the only variable that provided positive stimulus on rural banks’ performance. This showed us that rural banks should have improved risk and capital management practice so that they will not have to depend on the interest rate to have a better performance.]]>
<![CDATA[Islamic Bank and Monetary Policy: The Case of Indonesia ]]>
<![CDATA[Regi Muzio Ponziani]]>;
<![CDATA[Tatik Mariyanti]]>
<![CDATA[ International Journal of Islamic Economics and Finance (IJIEF) Vol 3, No 1 (2020): IJIEF Vol 3 (1), January 2020 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/ijief.2124
<![CDATA[Islamic bank in Indonesia exists side by side with its conventional counterpart within dual banking system, while the central bank aims to achieve price stability in the economy using conventional and Islamic monetary instruments within dual monetary system. This posits a very unique environment for Islamic bank. This research aims to examine the role of Islamic bank in monetary policy transmission mechanism using Granger Causality and Autoregressive Distributed Lag (ARDL). The balance sheet components of deposit and financing were hypothesized to function in monetary transmission process within bank financing channel. Granger causality revealed that Islamic interbank overnight rate granger causes Islamic deposit and financing. Islamic deposit and financing granger cause industrial production index. Industrial production index granger cause inflation, Islamic deposit, and Islamic interbank overnight rate. Islamic deposit and inflation granger cause Islamic interbank overnight rate. The ARDL results showed that there were cointegrating relationships in the output and inflation model. Long-term convergence could be reached to correct deviations in output and inflation by way of Islamic banks’ deposit and financing. However, short-term influence is contributed only by Islamic banks’ deposit to output. Islamic banks’ deposit does not contribute in the short-run to inflation. Islamic banks’ financing does not have short-term relationship with output and inflation. Hence, there is a declining effectiveness of Islamic banks’ financing contribution to the economy.]]>
<![CDATA[Foreign Tourists Arrival Forecasting at Major Airports in Indonesia: ]]>
<![CDATA[Regi Muzio Ponziani]]>
<![CDATA[ IJEBD (International Journal of Entrepreneurship and Business Development) Vol 4 No 5 (2021): September 2021 ]]>
Publisher : <![CDATA[LPPM of NAROTAMA UNIVERSITY ]]>
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DOI: 10.29138/ijebd.v4i5.1507
<![CDATA[Purpose: This research purports to forecast the number of foreign tourists arriving at major airport in Indonesia. The airports chosen are Soekarno Hatta, Juanda, I Gusti Ngurah Rai, and Kualanamu international airports. Design/methodology/approach: The data used were foreign tourists arrival at major airports located in Jakarta, Surabaya, Medan, and Denpasar. The data extended from January 2014 until December 2018. Two time-series methods were employed, namely Holt-Winter Seasonality and Exponential Smoothing with maximum likelihood. The forecasts would reveal the fitted numbers of foreign tourists arriving from January 2019 until December 2019. The fitted numbers would then be compared to the actual numbers of January 2019 to December 2019. Findings: The results showed that, overall, Holt-Winters seasonality excel at forecasting foreign tourists arrival at Soekarno Hatta and Juanda international airports. While Exponential Smoothing perform better for prediction at I Gusti Ngurah Rai and Kualanamu international airports. The MAPE for Holt-Winters at Soekarno Hatta and Juanda international airports were 26.1585% and 14.538%. The MAPE for Exponential Smoothing at at I Gusti Ngurah Rai and Kualanamu international airports were 7.76% and 15.6791%. Research limitations/implications: Forecasting for foreign tourist arrival at Soekarno Hatta and Juanda international airports should employ Holt-Winters approach. Forecasting for foreign tourists arrival at I Gusti Ngurah Rai and Kualanamu international airports should employ Exponential Smoothing with maximum likelihood. Practical implications: Certain forecasting methods work better than the others at certain international airports. Many forercasting methods are available. Two methods are specifically prominent for detecting seasonality and trend, i.e Holt-Winters and Exponential Smoothing with maximum likelihood. Originality/value: Most research focus on one method at a time. This research compares two methods so that we can know better which method is suitable for certain airports. Four international airports are sampled in this study. Not many research focus on several places at a time. Paper type: Research paper]]>
<![CDATA[Stock Indices Forecasting: A Comparison of Holt-Winters Seasonality and Dynamic Harmonic Regression ]]>
<![CDATA[Regi Muzio Ponziani]]>
<![CDATA[ Jurnal Keuangan dan Perbankan Vol 26, No 2 (2022): APRIL 2022 ]]>
Publisher : <![CDATA[University of Merdeka Malang ]]>
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DOI: 10.26905/jkdp.v26i2.6755
<![CDATA[This research aims to investigate the performance of various time-series forecasting approaches in predicting stock indices in Indonesia. This research compared the performance of additive Holt-Winters seasonality, multiplicative Holt-Winters seasonality, and Dynamic Harmonic regression. The stock indices being forecast are SRI-KEHATI, LQ45, and IHSG. Forecasting SRI-KEHATI index is the novelty in this research. SRI-KEHATI index contains all the companies that comply with the requirements regarding sustainability and concerns for the environmental impact of the companies operations. Decompositions of SRI-KEHATI, LQ45, and IHSG reveal that the trend and seasonality components are all existent within all indices. The results showed that Holt-Winters models are superior to Dynamic Harmonic Regression. Multiplicative Holt-Winters seasonality forecast best for SRI-KEHATI and LQ45. Additive Holt-Winters excelled at predicting IHSG. Although Dynamic Harmonic Regression had less accuracy, its performance was still very outstanding since its mean average percentage errors never exceeded 8%. The result signifies the excellence of the Holt-Winters model for predicting stock indices and also shows that Dynamic Harmonic Regression also scores high in accuracy. Both models validate the time variance notion of the stock market proposed by Boudreaux (1995). The practical benefit for Investors is that this research enables investors to forecast the stock indices in the future and make adjustments in their trading strategy thereof.]]>
<![CDATA[The Inflation Forecasting of Major Cities In East Kalimantan: A Comparison Of Holt-Winters And SARIMA Model ]]>
<![CDATA[Regi Muzio Ponziani]]>
<![CDATA[ Internasional Journal of Data Science, Engineering, and Anaylitics Vol. 1 No. 2 (2021): International Journal of Data Science, Engineering, and Analytics Vol 1, No 2, ]]>
Publisher : <![CDATA[International Journal of Data Science, Engineering, and Analytics ]]>
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DOI: 10.33005/ijdasea.v1i2.8
<![CDATA[This research aims to compare the performance of Holt Winters and Seasonal Autoregressive Integrate Moving Average (SARIMA) models in predicting inflation in Balikpapan and Samarinda, two biggest cities in East Kalimantan province. The importance of East Kalimantan province cannot be overstated since it has been declared as the venue for the capital of Indonesia. Hence, inflation prediction of the two cities will give valuable insights about the economic nature of the province for the country’s new capital. The data used in this study extended from January 2015 to September 2021. The data were divided into training and test data. The training data were used to model the time series equation using Holt winters and SARIMA models. Later, the models derived from training data were employed to produce forecasts. The forecasts were compared to the actual inflation data to determine the appropriate model for forecasting. Test data were from January 2015 to December 2020 and test data extended from January 2021 to September 2021. The result showed that Holt-Winters performed better than SARIMA in prediction inflation. The Root Mean Squared Error (RMSE) values are lower for Holt-Winters Exponential Smoothing for both cities. It also predicts better timing of cyclicality than SARIMA model.]]>
<![CDATA[The Dynamics of Macroeconomic and Microeconomic Determinants with The Capital of Rural Banks ]]>
<![CDATA[Ponziani, Regi Muzio]]>
<![CDATA[ JEJAK: Jurnal Ekonomi dan Kebijakan Vol 15, No 1 (2022): March 2022 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/jejak.v15i1.31902
<![CDATA[The research aims to investigate the dynamics among rural banks’ capital, macroeconomic variables and microconomic variables. Macroeoconomic variable consists of infllation and interest. Microeconomic variables consist of loan to deposi ratio, nonperforming loans, and return on assets. The data are excerpted from OJK and BI’s website. The data are monthly data extending from January 2010 until May 2021. The testing method used is vector error correction model (VECM). The results show that rural banks’ capital is significantly affected the previous state of capital and profitability. This indicates the importance of sustainability of capital in rural banks and how it is very much dependent upon the profitability of the rural banks. Further, the research results show that there ar two cointegrating functions in the model. Both cointegration functions are influential to inflation. The speed adjustment derived from the residuals of capital function is 0.6754% and 13.5669% for residual from inflation function itself. The slow adjustment process is due to the small market share and assets of rural banking sector. In addition, capital, nonperforming loans, and return on assets are pivotal for central bank monetary policy to control inflation.]]>
<![CDATA[THE ANALYSIS OF HIGHEST PAYING DIVIDEND COMPANIES STOCK RETURNS VOLATILITY IN INDONESIA ]]>
<![CDATA[Ariesta Tika Kinanti Pangestu Putri]]>;
<![CDATA[Hilary Flora Agustina Tulli Lasar]]>;
<![CDATA[Regi Muzio Ponziani]]>
<![CDATA[ Jurnal Muara Ilmu Ekonomi dan Bisnis Vol. 7 No. 1 (2023): Jurnal Muara Ilmu Ekonomi dan Bisnis ]]>
Publisher : <![CDATA[Lembaga Penelitian dan Pengabdian Kepada Masyarakat, Universitas Tarumanagara ]]>
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DOI: 10.24912/jmieb.v7i1.23150
<![CDATA[Penelitian ini bertujuan untuk memodelkan volatilitas return indeks saham perusahaan dividen tertinggi di Indonesia (DIV 20) sebelum dan sesudah pandemi COVID 19. Model keluarga ARCH (Autoregressive Conditional Heteroscedasticity) digunakan dalam hal ini. Periode penelitian diperpanjang dari 18 Mei 2018 hingga 18 Februari 2022. Batas waktu dimulainya pandemi adalah 1 April 2020. Data pengembalian adalah pengembalian mingguan. Hasilnya menunjukkan bahwa sebelum pandemi, GJR-GARCH(1,1) dapat memetakan dan melacak volatilitas dengan sangat baik karena mencetak AIC dan SIC pra-pandemi terendah. Oleh karena itu, penelitian ini menguatkan bukti adanya reaksi asimetris dari partisipasi pasar terhadap kemunculan dan penyebaran berita baik dan buruk di pasar. Setelah pandemi, efek ARCH menjadi kurang jelas. Angka signifikansi menurun meskipun efek ARCH masih signifikan pada 0,15. Performa model ARCH(1) secara signifikan lebih tinggi daripada model lain pasca-pandemi. Hasil tersebut menjadi bukti bahwa pascapandemi ketidakpastian yang dihadapi pelaku pasar sangat tinggi. Hal ini mengakibatkan meningkatnya volatilitas. Model keluarga ARCH menjadi kurang signifikan karena pengembaliannya lebih acak. Analisis lebih lanjut, bagaimanapun, menunjukkan bahwa pengembalian belum mengikuti model random walk meskipun keacakan meningkat. Oleh karena itu, ARCH(1) masih sesuai untuk memodelkan volatilitas setelah Pandemi. This research aims at modeling the volatility of Indonesian highest paying dividend companies stock index (DIV 20) returns before and after pandemic COVID 19. The ARCH (Autoregressive Conditional Heteroscedasticity) family models were employed in this regard. The research period extended from 18 May 2018 to 18 February 2022. The cutoff for the commencement of pandemic was 1st April 2020. The return data were weekly returns. The results suggested that before pandemic, GJR-GARCH(1,1) could map and trace the volatility very well since it scored the lowest AIC and SIC pre-pandemic. Therefore, this research corroborated the evidence that there existed asymmetric reaction from the market participation toward the emergence and spread of good and bad news in the market. After pandemic, the ARCH effect became less obvious. The significance number was decreasing although the ARCH effect was still significant at 0.15. ARCH(1) model performance was significantly higher than the other models post-pandemic. The result presented evidence that after pandemic the uncertainty facing the market participants was very high. This resulted in the increase of the volatility. The ARCH family model was becoming less significant because the returns were more random. Further analysis, however, showed that the returns did not yet follow the random walk model despite the increasing randomness. Therefore, ARCH(1) was still appropriate to model the volatility after Pandemic.]]>
