This study is to expose the sharia concept in the Islamic market, especially on the practice of the equilibrium model or the Capital Asset Pricing Model (CAPM). Islamic index and sharia market are introduced to answer the Islamic investment. However, we cannot apart from the interest rate, which is related to ‘riba’ and prohibited in Islam religion. Many references proposed the Islamic theory into the CAPM, so the model has been modified and adjusted to deliver the new solution on sharia investment. We provide a general illustration to explain how the sharia concept in CAPM as an equilibrium model and its implementation in Jakarta Islamic Index (JII). The result shows that the range of return is various, while the risk both beta and standard deviation have remained steady. The result shows that the Sharia version with the Sukuk rate performs better than the others from the expected return.

Recurrent neural network is a network which provides feedback connections. This network is believed to have a more powerful approach than the typical neural network for learning given data. The current research was aimed to apply the simplest recurrent neural network model, namely the Elman recurrent neural network (ERNN) model, to the consumer price index (CPI) of education, recreation, and sports data in Yogyakarta. The pattern of CPI data can be categorized as a function of time period, which tends to move upwards when the time period is increased, and jump at some points of the time period. This pattern was identified as similar to the pattern resulted by the function of the truncated polynomial spline regression model (TPSR). Hence, this research considered ERNN model which the inputs such as in the TPSR model were established by taking into account the location of the knot or jump points. In addition, the ERNN model with a single input, a time period was also generated. The results demonstrated that the two models have high accuracy both in training and testing data. More importantly, it was found that the first model is more appropriate than the second one in testing data. Keywords-Elman recurrent neural network; CPI of education recreation, and sports in Yogyakarta; truncated polynomial spline regressionI.

Human Development Index is one of the indicators to measure the success of a region in the field of human development sector. There are several factors that affect Human Development Index, such as life expentancy, the literacy rate, the average length of the school, and the index of purchasing power. The aim in this paper is to analyze the relationship between factors that affect Human Development Index in Yogyakarta using regression analysis. One of the assumptions of classical regression is not going multicollinierity. Multicollinierity cause misinterpretation of regression coefficients with Ordinary Least Square (OLS) method. One method used to overcome multicollinierity is Partial Least Square (PLS). The result of Human Development Index data analysis showed there was a high correlation between the predictor variables or in other words going multicollinierity, so using PLS method, we obtained adjusted R 2 of 99.3% Human Development Index variables can be explained by the four predictor variables. By using PLS method, multicollinierity resolved in the problem of violation in the linear regression assumption. Keywords: IPM, OLS, regression, PLS. PENDAHULUANIndeks Pembangunan Manusia (IPM) memperlihatkan tingkat pembangunan sumber daya manusia di suatu wilayah, sehingga dapat dijadikan sebagai tolak ukur angka kesejahteraan suatu daerah atau negara. IPM merupakan indikator gabungan dari beberapa indikator, yaitu indikator kesehatan (ditunjukkan dengan indeks angka harapan hidup waktu lahir), indikator pendidikan (ditunjukkan dengan indeks angka melek huruf dan ratarata lama sekolah), serta indikator ekonomi (ditunjukkan dengan konsumsi per kapita yang disesuaikan/indeks daya beli penduduk).Analisis regresi adalah teknik statistika yang dapat digunakan untuk menjelaskan pengaruh variabel prediktor terhadap variabel respon. Model regresi linier dapat diperoleh dengan melakukan estimasi terhadap parameter-parameternya dengan menggunakan metode tertentu. Adapun metode yang dapat digunakan untuk mengestimasi parameter model regresi linier adalah metode Ordinary Least Square (OLS). Setelah diperoleh dugaan regresi linier selanjutnya dilakukan pengujian kelayakan, uji parameter, serta uji asumsi klasik (Aryani dan Retno, 2014

Purpose This research aims to demonstrate portfolio modeling, which leads to Sharia compliance in encountering crises because of COVID-19. The authors proposed modifying the Black–Litterman (BL) model adapted to the Sharia principle. The implementation of BL on Shariah-compliant stock data with capital asset pricing model (CAPM) requires adjustment because of the interest rate in the calculation. Thus, the objective of this study is to develop and evaluate the modified BL for Shariah-compliant stock portfolios in the financial crisis caused by the COVID-19 pandemic. Design/methodology/approach The Sharia-compliant asset pricing model (SCAPM) with the inflation rate was regarded as the new starting point in the BL model. This proposed model was implemented in Indonesia using monthly returns from the Jakarta Islamic Index (JII) list collected from February 2014 to June 2019. Furthermore, the portfolio performance of BL-SCAPM was compared with two reference portfolios, the mean-variance method and BL-CAPM. Findings The result presents that the portfolio performance of BL-SCAPM outperformed the MV and BL-CAPM. The impact of the Sharpe ratio of BL-SCAPM was more significant than the reference portfolio. The equal benefit was procured from both portfolios in July and August 2019. After the COVID-19 outbreak was officially declared in January 2020, the performance of BL-SCAPM was still above the BL. Despite a decline in portfolio value before and during the outbreak, the reference portfolio losses were higher than those of BL-SCAPM. Hence, this study manifested that BL-SCAPM outperformed the reference portfolio. Practical implications The results illustrate the empirical study which can be implemented for the Shariah-compliant stock market in Indonesia. By evaluating portfolio value on the COVID crisis for long investment, replacing CAPM with SCAPM in the BL model can transform the asset proportion. It decreased the portfolio loss during the crisis. Future research can be developed more from the open problems in this implementation to deliver the portfolio model into the Shariah framework with varied SCAPM in BL. Originality/value The attention to BL studies on portfolio building with Sharia-compliant stocks is rarely focused on the Islamic perspective. Hence, the novelty of this research is the idea of modifying the BL model with a Shariah starting point. More generally, this research enriches Shariah financial literacy regarding the stock market and, specifically, its implementation in the Indonesian stock market.