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"ABSTRAKThe Research will confirm that the differences between the Islamic Economic System and the Conventional Economic System should generate differences between the sharia market and the conventional market. Conventional Market clearly is influenced by banking interest rate, speculation, and permit gambling, disobedience, and other bussiness that are prohibited by Islamic values. However, Sharia Market should be free from banking interest rates, speculation, and not permit gambling, disobedience, and other bussiness that are prohibited by Islamic values. Through bivariate and multivariate analysis, the research conducted regression, correlation, and determination test to know whether conventional market influence on sharia market. The analysis is based on the investigation of Indonesia Stock Exchange datas from December 2006 to May 2017. In these cases, Jakarta Stock Exchange (JSX) Composite Index (Indeks Harga Saham Gabungan (IHSG)) and Jakarta Stock Exchange Liquid Index (LQ45) are classified as conventional market. Meanwhile, Sharia Market is represented by Jakarta Islamic Index (JII) dan Indonesia Sharia Stock Index (ISSI). The results show that Conventional Market has a strong and positive correlation with Sharia Market, which indicates that sharia market runs together with conventional market with the same character, in other words sharia market is still influenced mainly by banking interest rate and speculation. The research will observe specifically at the fluctuations of sharia stocks at JII and ISSI compared with the fluctuations of conventional stocks on IHSG and LQ45. The reseach quantitative methods are Least Square Bivariate Analysis dan Multivariate Analysis, serta Pearson product moment correlation and determination coefficient. The next steps, the research will also accurately investigate the list of issuers on IHSG, LQ45, JII, and ISSI, and compare the specific sharia issuers with non sharia issuers, so that the classification of IHSG and LQ45 as conventional market is corrected. Based on the results of the analysis of regression, correlation, determination, and investigation of datas, the research will formulate model of effective solution of sharia market stability."

"Dalam beberapa dekade terakhir, pesatnya pertumbuhan industri dan meningkatnya kepadatan lalu lintas di wilayah perkotaan termasuk DK Jakarta menimbulkan masalah kualitas udara. Salah satu indikator terjadinya pencemaran udara adalah turunnya hujan asam. Hujan asam terjadi akibat zat polutan berupa SO2 dan NO2 bereaksi dengan air (H2O). Dampak hujan asam antara lain dapat merusak kesuburan tanah sehingga dapat mempengaruhi kualitas hidup manusia dan juga dapat merusak benda maupun infrastruktur. Penelitian ini bertujuan untuk menganalisa sebaran SO2 dan NO2 secara spasial temporal, juga membuat model keasaman air hujan berdasarkan sebaran SO2 dan NO2 di DK Jakarta. Sebaran SO2 dan NO2 diperoleh menggunakan teknik penginderaan jauh dengan memanfaatkan citra Satelit Sentinel 5P. Pengolahan dilakukan menggunakan GEE. Dari hasil analisis bivariat diketahui bahwa sebaran spasial SO2 dipengaruhi oleh curah hujan dan tidak dipengaruhi oleh kecepatan angin. Sedangkan sebaran NO2 dipengaruhi secara signifikan oleh curah hujan dan juga kecepatan angin. Secara temporal, sebaran SO2 pada tahun 2023 memiliki nilai tertinggi di bulan Juni dan sebaran NO2 memiliki nilai tertinggi pada bulan Agustus. Hasil validasi antara data SO2 dan NO2 yang diperoleh melalui penginderaan jauh dengan data observasi pada SPKU milik BMKG, menjelaskan bahwa data penginderaan jauh pada beberapa stasuin tidak konsisten dengan data hasil observasi di SPKU. Model prediksi tingkat keasaman air hujan diperoleh berdasarkan sebaran SO2 dan NO2 pada Tahun 2023 di Jakarta. Hasil regresi linier berganda menunjukan bahwa ada korelasi antara pH air hujan dengan sebaran SO2 dan NO2. Koofisien korelasi bernilai (-) 0,7305 yang berarti korelasi berada dalam kategori kuat. Korelasi bersifat negatif yang menjelaskan bahwa semakin besar kadar SO2 dan NO2 maka pH air hujan akan semakin kecil/ asam. Diperoleh nilai 13% dalam perhitungan MAPE yang berarti model prediksi termasuk kedalam kategori baik dan dapat digunakan untuk memprediksi keasaman air hujan (pH) di Jakarta.

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In the last few decades, rapid industrial growth and increasing urban traffic density, have caused air quality problems including in DK Jakarta. One indicator of air pollution is acid rain. Acid rain occurs due to pollutants in the form of SO2 and NO2 reacting with water (H2O). The impact of acid rain, among other things, can damage soil fertility, affect the quality of human life, and damage objects and infrastructure. This research aims to analyze the distribution of SO2 and NO2 spatially and temporally, as well as create a rainwater acidity model based on the distribution of SO2 and NO2 in DK Jakarta. The distribution of SO2 and NO2 was obtained using remote sensing techniques using Sentinel 5P Satellite imagery. Processing is carried out using GEE. From the results of the bivariate analysis, it is known that the spatial distribution of SO2 is influenced by rainfall and is not influenced by wind speed. Meanwhile, the distribution of NO2 is significantly influenced by rainfall and wind speed. Temporally, the distribution of SO2 in 2023 has the highest value in June and the distribution of NO2 has the highest value in August. The validation results between SO2 and NO2 data obtained through remote sensing with observation data by BMKG explain that remote sensing data at several stations is inconsistent with observation data. The prediction model for rainwater acidity levels was obtained based on the distribution of SO2 and NO2 in 2023 in Jakarta. The results of multiple linear regression show that there is a correlation between rainwater acidity and the distribution of SO2 and NO2. The correlation coefficient is (-) 0.7305, which means the correlation is in the strong category. The correlation is negative, which explains that the greater the SO2 and NO2 levels, the more acidic the rainwater will be. A value of 13% was obtained in the MAPE calculation, which means the prediction model is included in the good category and can be used to predict rainwater acidity in Jakarta."