This research aims to define Sharia housing products from the perspective of real estate developers in Greater Bandung. The authors try to dig deeper into whether the housing made by these developers is by the fundamental understanding of sharia housing or not. This study also tries to determine what is still missing and what has been running well in practice. In the preliminary research, the authors attempted to define this sharia property by theories and more focused on the consumer side. This study is using Qualitative Analysis with Semi-Structured Interviews. From the result of this research, it can be seen that sharia housing in Bandung is not very focused on the design of sharia buildings in private residential, but rather to provide sharia facilities for public use and other Islamic activities in their neighbourhood. This research would be useful for property developers, consumers, and other parties like academicians or the government.

The increasing of Islam news in internet makes some perceptions for many people in the world. One of them is about "Halal" concepts as the Islam standard for muslim belief of God. Halal product is the product that created based on Islamic standard law. In every product, it is necessary to ensure its safety by conducting halal certification from the Indonesian Ulama Council (MUI). Then, based on the explanation, this research aims to analysis what internet user say about halal by using social media Twitter. This research uses text mining, word networking and word networking matrix to understanding the use of halal word. This research shows that "halal" has a large network and having relationship with many of word such as: food, meat, certification, restaurant, slaughter, animal, and industry. Then, from the network shows that "food" is the biggest word matrix in the "halal" networking. It word define degree centrality 75, betwenness centrality 20.001,38, and closeness centrality 0.473064 which mean that "halal" word have strong relationship with "food".

According to the rating of PEFINDO, there are 10 biggest Banks in Indonesia which dominate 65.2% of the total asset. From this rating, writer examine the best fitted volatility model using ARCH, GARCH, TARCH and EGARH. The result from R-Squared, AIC and SIC, all of the bank have good fitted volatility with EGARCH model, but when writer double checking for the EGACRH model with time series diagnostic checking and fitted model performance measurement, the result show that not all of the banks is fitted volatility by EGARCH model. ABSTRAK Menurut peringkat PEFINDO, ada 10 Bank terbesar di Indonesia yang mendominasi 65,2% dari total aset. Dari peringkat ini, penulis menguji model volatilitas yang paling cocok menggunakan ARCH, GARCH, TARCH dan EGARH. Hasil dari R-Squared, AIC dan SIC, semua Bank memiliki volatilitas yang sesuai dengan model EGARCH, tetapi ketika penulis memeriksa dua kali untuk model EGACRH dengan pemeriksaan diagnostik deret waktu dan pengukuran fitted model performance, hasilnya menunjukkan bahwa tidak semua Bank masuk ke dalam kategori volatilitas dengan model EGARCH

AbstrakInflasi akan mempengaruhi tingkat suku bunga. Ketika inflasi naik maka tingkat suku bunga akan meningkat begitupun sebaliknya, ketika inflasi turun maka tingkat suku bunga akan menurun juga. Tidak seperti negara lain, Indonesia memiliki keadaan yang unik, terkadang meskipun BI Rate turun namun tingkat kredit tidak turun. Jadi, berdasarkan kasus ini, makalah ini mengkaji hubungan Inflasi, Suku Bunga dan Tingkat Kredit. Dengan menggunakan model Vasicek, paper ini mengevaluasi fitting long-term, speed and volatility dari setiap tingkat kredit berdasarkan kategori bank di Indonesia. Kemudian menilai tingkat fluktuasi pada masing-masing bank. Tingkat masing-masing kategori bank sangat fluktuasi namun tidak lebih dari 0,005 dan tidak lebih rendah dari 0,005.