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"ABSTRAKPada penelitian ini, detergen cair dalam bentuk nanofluida disintesis dari surfaktan MES dan nanopartikel TiO2. Selain itu, dilakukan juga penambahan CMC carboxymethyl cellulose sebagai penstabil detergen. Tujuan dari penelitian ini adalah untuk memperoleh detergen ramah lingkungan dengan stabilitas dan kinerja yang optimum. Surfaktan MES disintesis dari minyak goreng bekas melalui proses pretreatment, transesterifikasi, dan sulfonasi yang dilanjutkan dengan tahap pemurnian dan netralisasi. Kemudian dilakukan sintesis detergen dengan variasi konsentrasi surfaktan MES dan CMC untuk mendapatkan komposisi optimum dari detergen nanofluida dengan konsentrasi TiO2 konstan sebesar 0,1 . Hasil menunjukkan bahwa minyak goreng bekas hasil pretreatment telah memenuhi kriteria untuk dapat dilangsungkan proses transesterifikasi. Pada proses transesterifikasi, yield metil ester tertinggi sekitar 96 diperoleh pada rasio mol minyak dan metanol sebesar 1:9. pH netralisasi optimum untuk proses sulfonasi adalah pada pH 7 dengan kandungan disalt sebesar 4,8 dan nilai tegangan permukaan terendah sebesar 32,4 mN/m. Analisis stabilitas detergen menunjukkan pada konsentrasi surfaktan MES 1,5 , diperoleh kestabilan terbaik mencapai 99 dan setelah penambahan CMC sebesar 4 , tidak terjadi pengendapan selama dua minggu pengamatan. Kinerja detergen dianalisis berdasarkan kemampuan detergen dalam mengangkat dan mendegradasi kotoran. Pada konsentrasi surfaktan MES 1,5 memiliki kemampuan dalam mengangkat kotoran terbaik dan tegangan permukaan terendah sebesar 32,8 dyne/cm. Setelah dilakukan penambahan CMC 4 , kemampuannya meningkat sebesar 14 . Pada uji degradasi kotoran, kinerja detergen dapat ditingkatkan dengan reaksi fotokatalisis TiO2 yang masing-masing meningkat sebesar 11 dan setelah penambahan CMC menjadi sebesar 5.

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ABSTRACT In this study, liquid detergent in the form of nanofluid was synthesized from MES surfactant and titanium dioxide nanoparticles. On the other hand, the addition of CMC carboxymethyl cellulose was done to improve detergent stability. The purpose of this study was to obtain an eco friendly detergent with optimum stability and performance. MES surfactant was synthesized from waste cooking oil WCO through pretreatment, transesterification and sulfonation process followed by purification and neutralization step. Then synthesis of detergent was done with concentration of MES surfactant and CMC were varied to achieve optimum composition of nanofluid detergent while TiO2 concentration was kept at 0.1 . The results showed that after pretreatment, WCO has fulfilled the criteria for transesterification process. In the transesterification process, the highest yield of methyl ester about 96 was obtained at mole ratio of oil and methanol 1 9. The optimum condition of pH neutralization after sulfonation process at pH 7 with disalt content of 4.8 and lowest surface tension value, 32.4 mN m. The analysis of detergent stability showed at MES surfactant concentration of 1.5 , detergent had the best stability about 99 and after addition of CMC 4 , no sedimentation occurred within two weeks. Performance test were studied by stain removal test and stain degradation test. At MES concentration of 1.5 has the best performance for stain removal and the lowest surface tension value, 32.8 dyne cm. After the addition of CMC 4 , detergent performance increased about 14 . While stain degradation test showed that detergent performance can be improved by TiO2 photocatalytic reaction, which respectively increased about 11 and after the addition of CMC increased 5 ."

"Most of Indonesian oil field had been categorized as mature filed in which production had been declined for some time. Therefore EOR technology is a must to be implemented to these kinds of field. There are several EOR technologies had been employed successfully in laboratory and also field scales, including gas, thermal, and chemical infection."

"[ABSTRAKTesis ini membahas mengenai pengukuran kontribusi risiko sistemik danhubungannya dengan karakteristik individu bank pada perbankan Indonesiadengan periode pengamatan dari 2003 s.d 2013.Metode yang digunakan untukmengukur kontribusi risiko sistemik adalah CoVaR (Girardi dan Ergun, 2013) danMES (Acharya, 2010). CoVaR digunakan untuk melihat kontribusi risiko sistemikmasing-masing bank terhadap sistem keuangan apabila bank mengalami distresssedangkan MES digunakan untuk melihat bagaimana kontribusi risiko sistemikmasing-masing bank apabila sistem keuangan mengalami distress. Dari hasilpengukuran ditemukan bank yang memiliki nilai Delta CoVaR terbesar adalahBMRI, BBRI, BBCA dan BBNI.Ke 4 (empat) bank tersebut merupakan bankterbesar di Indonesia.Hal ini menunjukan bahwa bank yang akan memberikant kontribusi risikokepada sistem sebesar nilai Delta CoVaR nya saat bank mengalami distress.Sebaliknya dari hasil pengukuran MES diketahui bahwa bank yang akanmemberikan kontribusi risiko sistemik terbesar saat sistem mengalami distressadalah BBRI. Hasil penelitian menunjukan bahwa karakteristik individu bankseperti ukuran bank dan VaR memiliki pengaruh yang signifikan terhadap besarkontribusi risiko sistemik bank di Indonesia. Kondisi makroekonomi seperti inflasisecara signifikan mempengaruhi nilai kontribusi risiko sistemik dari masingmasingbank di Indonesia.

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ABSTRACTThis thesis discusses the contribution of systemic risk and its relationshipwith the individual characteristics of banks in the Indonesian banking with theobservation period from 2003 until 2013. The method used to measure systemicrisk contribution is CoVaR (Girardi and Ergun, 2013) and MES (Acharya, 2010).CoVaR looks ay the returns of the financial system when an institution is infinancial distress while MES looks at the returns of an institution when thefinancial system is in distress. From the results of measurements we found that thebank has the largest value of Delta CoVaR areBMRI , BBRI , BBCA and BBNI .All of the bank are the largest bank in Indonesia.This shows that the bank will contribute to the system at its current value ofDelta CoVaR bankswhile experiencing distress. On the other hand, the resultmeasurement of the MES is that BBRI will provide the largest contribution tosystemic risk when the system it experiencing distress.The results showed thatindividual characteristics such as bank size and VaR has a significant effect on thebank contribution to systemic risk in Indonesia. Macroeconomic conditions suchas inflation significantly affect the value of systemic risk contribution of each bankin Indonesia.;This thesis discusses the contribution of systemic risk and its relationshipwith the individual characteristics of banks in the Indonesian banking with theobservation period from 2003 until 2013. The method used to measure systemicrisk contribution is CoVaR (Girardi and Ergun, 2013) and MES (Acharya, 2010).CoVaR looks ay the returns of the financial system when an institution is infinancial distress while MES looks at the returns of an institution when thefinancial system is in distress. From the results of measurements we found that thebank has the largest value of Delta CoVaR areBMRI , BBRI , BBCA and BBNI .All of the bank are the largest bank in Indonesia.This shows that the bank will contribute to the system at its current value ofDelta CoVaR bankswhile experiencing distress. On the other hand, the resultmeasurement of the MES is that BBRI will provide the largest contribution tosystemic risk when the system it experiencing distress.The results showed thatindividual characteristics such as bank size and VaR has a significant effect on thebank contribution to systemic risk in Indonesia. Macroeconomic conditions suchas inflation significantly affect the value of systemic risk contribution of each bankin Indonesia., This thesis discusses the contribution of systemic risk and its relationshipwith the individual characteristics of banks in the Indonesian banking with theobservation period from 2003 until 2013. The method used to measure systemicrisk contribution is CoVaR (Girardi and Ergun, 2013) and MES (Acharya, 2010).CoVaR looks ay the returns of the financial system when an institution is infinancial distress while MES looks at the returns of an institution when thefinancial system is in distress. From the results of measurements we found that thebank has the largest value of Delta CoVaR areBMRI , BBRI , BBCA and BBNI .All of the bank are the largest bank in Indonesia.This shows that the bank will contribute to the system at its current value ofDelta CoVaR bankswhile experiencing distress. On the other hand, the resultmeasurement of the MES is that BBRI will provide the largest contribution tosystemic risk when the system it experiencing distress.The results showed thatindividual characteristics such as bank size and VaR has a significant effect on thebank contribution to systemic risk in Indonesia. Macroeconomic conditions suchas inflation significantly affect the value of systemic risk contribution of each bankin Indonesia.]"

"Natural-based surfactant such as methyl esther sulfonate, which is derived from palm oil, has increasingly become the focus of study for the last decade to improve oil recovery due to the abundant raw materials availability and the need for oil as a source of energy. Surfactant MES development with the targeted fluid reservoir characteristics has been conducted in the laboratory scale as well as in the field scale. In this study, the addition of polyethylene glycol mono-oleate as co-surfactant to enhanced oil recovery in the "L" oillfield in Central Java was investigated in the laboratory scale through compatibility observation, IFT measurement, thermal stability and core flooding tests. The result showed that the presence of PMO improved the solubility of surfactant mixture in the water which formed one phase milky solution. Decreasing IFT as the crucial factor for surfactant flooding was also achieved until 10-3 dyne/cm and thermally stable for two months. Furthermore, core flooding experiments to study the performance of surfactant to recover oil production showed that the mixture of MES and PMO are able to enhance oil recovery until 55.35%S and have potential to be used as chemicals for chemical flooding in the targeted oilfield."

"Tujuan dari penelitian ini adalah untuk menganalisis peringkat risiko sistemik dari enam metodologi pengukuran risiko sistemik yang dikenal serta mengembangkan peringkat risiko sistemik komposit menggunakan metode Principal Component Analysis (PCA), mengacu pada Nucera et al. (2016). Systemically Important Financial Institutions (SIFIs) didefinisikan sebagai 10 perusahaan yang memiliki risiko sistemik tertinggi dalam setiap pemeringkatan dari total sampel 60 lembaga keuangan yang go public selama periode 2008-2016. Dari hasil studi, peringkat komposit yang kami kembangkan lebih konsisten dalam menjelaskan komposisi SIFIs dari kebanyakan pemeringkatan risiko sistemik individu lainnya. Dari hasil PCA, ditemukan bahwa peringkat komposit yang kami hasilkan terutama dijelaskan oleh metode pemeringkatan berbasis data pasar. Lebih lanjut, kami menemukan perbedaan yang substantial antara pemeringkatan berbasis data pasar dan pemeringkatan berbasis data fundamental dalam menjelaskan peringkat risiko komposit. Oleh karena itu, dapat diduga bahwa peringkat risiko sistemik komposit, yang menggabungkan aspek pasar dan fundamental, akan memberikan informasi yang lebih lengkap bagi pengambil kebijakan dalam membuat keputusan di masa depan.

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The aim of this study is to incorporate systemic risk ranking from six generally accepted metrics and develop a single composite ranking using Principle Component Analysis, based on Nucera et al. (2016). We analyze the Systemically Important Financial Institutions (SIFIs) to gather information difference between systemic risk metrics. We identify SIFIs as the top 10 companies in each systemic risk metrics ranking, using a sample of 60 listed financial institutions in Indonesia over the period 2008-2016. We find that our single composite ranking is more consistent in term of SIFIs composition than most individual risk rankings. Furthermore, according to factor loadings of the first component, our single composite ranking is mainly based on market-based instead of fundamental. Based on second factor loading, we find that market-based metrics and fundamental-based metrics deviated substantially in constructing our composite ranking. Therefore, we suspect that our single composite ranking, that combines both market and fundamental aspect, will provide better insight for the regulator to make a decision."