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A. LATAR BELAKANGPerkembangan manajemen nilai tukar Indonesia telah mencatat adanya perubahan yang cukup drastis ketika Bank Indonesia menetapkan perubahan manajemen nilai tukar dari sistem nilai tukar dari mengambang terkendali (managed floating exchange rate) ke sistem nilai tukar mengambang bebas (free floating exchange rate). Perubahan manajemen yang sangat drastis ini berawal dari kondisi moneter yang berubah pada saat memasuki pertengahan tahun 1997. Rupiah mendapatkan tekanantekanan depresiatif yang sangat besar diawali dengan krisis nilai tukar di Thailand dan menyebar ke negara ASEAN lainnya. Nilai tukar rupiah secara simultan mendapat tekanan yang cukup berat karena besarnya capital outflow akibat hilangnya kepercayaan investor asing terhadap prospek perekonomian Indonesia. Tekanan terhadap nilai tukar tersebut diperberat lagi dengan semakin maraknya kegiatan speculative bubble, sehingga sejak krisis berlangsung nilai tukar mengalami depresiasi hingga mencapai 75 persen (Goeltom, 1998).Pada dasarnya Indonesia mempunyai pengalaman dalam menggunakan tiga sistem manajemen nilai tukar sejak tahun 1971 hingga sekarang (Waluyo dan Benny, 1998). Pada rentang tahun 1971 sampai tahun 1978, Indonesia menganut sistem nilai tukar tetap (fixed exchange rate), yaitu nilai rupiah secara langsung dikaitkan dengan nilai USD. Sejak 15 November 1978, sistem nilai tukar diubah menjadi mengambang terkendali (managed floating exchange rate) di mana nilai rupiah tidak lagi sematamata dikaitkan dengan USD, namun terhadap sekeranjang valuta partner dagang utama. Perubahan drastis dalam kebijakan mengambang terkendali tersebut terjadi pada tanggal 14 Agustus 1997, yaitu ketika sebelumnya Bank Indonesia menggunakan rentang sebagai acuan atas pergerakan nilai tukar, maka sejak itu tidak ada lagi rentang sebagai acuan nilai tukar (floating exchange rate sistem) [Simorangkir, 2004:51].Perubahan manajemen nilai tukar ini perlu dicermati lebih saksama tentang bagaimana kejutan nilai tukar akan memengaruhi perekonomian khususnya neraca perdagangan. Perubahan manajemen nilai tukar ini tentunya akan berimplikasi terhadap karakteristik fluktuasi nilai tukar dan pengaruhnya terhadap perekonomian terbuka. Beberapa penelitian menunjukkan adanya perubahan terhadap nilai tukar suatu mata uang mempunyai pengaruh terhadap perekonomian, yang antara lain sering ditujukan dengan perubahan neraca perdagangan dan perubahan output. DAMPAK PERTUMBUHAN NILAI TUKAR RIIL TERHADAP

The study aims to analyze how banking stock prices response to GDP, inflation and exchange rate in the Indonesia Stock Exchange (IDX) and Hong Kong Stock Exchange (HKEX). For this purpose a panel data of of seven listed bank’s company in each country for the 2016Q1-2018Q4 period is used for empirical analysis.  The model analysis using static and dynamic panel regression.  Static regression used are Fixed Effect, Random Effect or Common Effect by Chow test while dynamic regression used Generalized Method of Moments (GMM). The results revealed that stock prices respond positively to GDP and negatively to exchange rates on both exchanges. Furthermore, inflation was responded positively by stock prices on IDX, meanwhile inflation was responded negatively at HKEX. The differences in the values of the regression coefficients on two exchanges represented that the IDX is less responsive to the exchange rate and inflation variables than HKEX. Contrary, GDP was found more sensitive in Indonesian compared to Hongkong.  Dynamic regression is proved that HKEX is more efficient than IDX. Investors in IDX are still responding to the prices of the previous period, while investors at HKEX responded immediately to macroeconomic variable information without considering stock prices in the previous period.

The hypothesis are guess that Fed Rate negative influence to jakarta stock composite  index, guess that foreign exchange negative influence to jakarta stock composite  index and inflation negative influence to jakarta stock composite  index. Analysis instrument to knowing influence of fed rate, foreign exchange and inflation are use multiple linier regression analysis. To know what is the reach of independent variable influence to dependent variable use a hypothesis testing with a partial test (t test), simultant test (f test) and to knowing how the independent variable representative to dependent variable use a godness of fit (R2). The results of hypothesis analysis shows that Fed rate, foreign exchange and inflation have a simultant significant influence to jakarta stock composite  index. The evidence from the results shows that F test > F table (35,51624>2,95).  Partial test shows that Fed rate has negative influence to jakarta stock  composite index which t test > t table ((-6.016280 >2,048), foreign exchange has not influence to jakarta stock composite index with level a significant 5% and inflation has negative influence to jakarta stock composite index.

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The Fintech company has raised its number significantly in Indonesia and threatened the banking sector as Islamic Banking is not the exception. Fintech can provide better financial services than Islamic Bank with its technological advantages. This research aims to observe the effect of Fintech's on Islamic banks and discover the collaboration model between Fintech and Islamic banks to improve financial services. The method was carried out by Systematic Literature Review (SLR), then analyzed using Nvivo 12 to quantify the words counted to the papers found. The result showed that there were 14 papers found to analyze in the systematic review. According to Nvivo 12 words counted result, the highest words counted was ‘services’ with 21%, followed by ‘user’ and ‘customers’ combined with 16%. Furthermore, Fintech acts as the disruptor for Islamic Banking, shown in its Return on Asset and its potential to take over the millennial customers segment. The collaboration can be done by sharing product marketing, loans, and transaction services. For the customer, big data analysis, the legal aspects, risk of human error, and data security protocol should be mitigated by tightening the registration system to minimize fraud, enhancing the internet server to prevent failure transactions, and closely cooperating with the Authority of Financial Service in Indonesia (OJK) to ensure the legal aspects are fulfilled.

Research aims: The purpose of this study was to determine the credit distribution level used as working capital assistance for Micro, Small, and Medium Enterprises (MSMEs) during the COVID-19 pandemic.Design/Methodology/Approach: This study used a sample of 8 cities/regencies in East Java. Meanwhile, the Micro, Small, and Medium Enterprises (MSMEs) credit recipients were the population of the sample areas. This research's analysis model was panel data regression (generalized least square) by considering the emergence of heteroscedasticity in cross-section data between regional objects. The control variables outside the COVID-19 were the BI rate, third-party funds (TPF), and inflation.Research findings: This study’s results showed that the COVID-19 pandemic had a significant negative impact only on medium-sized business loans, while micro and small business loans are more resilient. Besides, Micro, Small, and Medium Enterprises (MSMEs) credit was significantly positively influenced by TPF; inflation did not affect credit; the BI rate only negatively affected medium-sized business credit.Theoretical contribution/Originality: Studies on Micro, Small, and Medium Enterprises (MSMEs) credit-related to economic phenomena and monetary policy have been widely carried out. However, the catastrophic virus that causes long-term economic uncertainty and impacts banks and Micro, Small, and Medium Enterprises (MSMEs) still requires in-depth study. Also, this study employed the GLS model that considers heteroscedasticity, which is still rarely used in previous studies.Practitioner/Policy implication: This research can be essential information for the Indonesian Financial Services Authority (Otoritas Jasa Keuangan or OJK) and Bank Indonesia (BI) in policymaking, both regulatory aspects and bank liquidity provision, in stimulating Micro, Small, and Medium Enterprises (MSMEs) credit, especially in the COVID-19 pandemic era.Research limitation/implication: The impact of COVID-19 on Micro, Small, and Medium Enterprises (MSMEs) loans is still classified based on micro, small and medium. It is still not grouped based on the Micro, Small, and Medium Enterprises (MSMEs) business sector in various cities and regencies in East Java. The analysis has not been clustered based on the spatial concentration of the Micro, Small, and Medium Enterprises (MSMEs) recipient areas.