Judul: Kapasitas jerapan kromat dari bahan tanah andisol dan oksisol serta bentonit dan organobentonit
Abstrak: Pencemaran krom (Cr) pada lingkungan terutama berasal dari proses- proses industri dan penggunaan produk-produk krom. Krom (Cr) dalam bentuk logam dan kromat diterapkan secara meluas sebagai pencegah karat yang banyak digunakan untuk alat-alat rumah tangga dan industri-industri dengan tujuan agar alat-alat yang diciptakan menjadi tahan lama. Krom dalam bentuk teroksidasi di dalam tanah merupakan masalah lingkungan yang penting, karena Cr (VI) bersifat lebih meracun dibanding dengan Cr (III). Cr (VI) biasanya muncul dalam bentuk anion seperti hidrokromat (HCrO4), dikromat (Cr2O72), kromat (CrO42) dan biasanya bersifat mobil dalam kondisi netral sampai alkalin. Karena kromat merupakan anion, maka jerapan kromat hanya mungkin dilakukan oleh bahan- bahan yang memiliki muatan positif. Penelitian ini bertujuan untuk mempelajari kapasitas bahan tanah andisol dan oksisol serta bentonit dan organobentonit dalam menjerap kromat. Bahan tanah Andisol dan oksisol merupakan tanah yang memiliki muatan tergantung pH, sedangkan bentonit merupakan bahan tambang yang memiliki kapasitas tukar kation tinggi dengan muatan berasal dari substitusi isomorfik. Sedangkan organobentonit adalah bentonit yang telah disisipi oleh senyawa alkil amonium untuk mengubah sifatnya dari hidrofilik menjadi organofilik. ...
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Judul: Adsorpsi dan desorpsi ion kromium(VI) pada bentonit yang dimodifikasi Heksadesiltrimetilamonium bromida
Abstrak: Bentonite is abundant mineral in Indonesia and potentially as adsorbent. Bentonite has negatively charge, so bentonite has high capability to adsorp cations, while the capability of bentonite to adsorp anion was very low. This research was modified bentonite from Leuwiliang with hexadecyltrimethylammonium bromide (HDTMABr). The result of bentonite modification was changes bentonite surface character from hidrofilic become hidrofobic or organofilic, so that can adsorp anion, like Cr(VI). This research made organobentonite 25, 50, and 100 % CEC. Some methodes were done in this research, they were determination of CEC, acidity, and adsorption optimum condition of Cr(VI) that covered determination of adsorption pH, contact time, isotherm, and desorption of Cr(VI) from organobentonite. Capacity Exchange Cation of bentonite, organobentonite 25 %, organobentonite 50 %, and organobentonite 100 % were 54.53, 45.14, 37.37, and 20.72 me/100 g, respectively. Acidity of bentonite, organobentonite 25 %, organobentonite 50 %, and organobentonite 100 % were 4.95, 3.62, 0.90, and 0.60 mmol/g, respectively. Optimum adsorption condition of Cr(VI) onto bentonite, organobentonite 25 %, organobentonite 50 %, and organobentonite 100 % were consist of pH 2 until 4, contact time 3 until 4 hours, on concentration 200 until 500 ppm. Adsorbtion capacity of bentonite, organobentonite 25 %, organobentonite 50 %, and organobentonite 100 %, respectively were 4.44, 11.96, 22.09, and 20.53 mg/g. Ability of HCl, aquadest, and CaCl2 to desorbed Cr(VI) from organobentonite was low, this matter showed that Cr(VI) was trapped strongly on organobentonite.
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Judul: Pemodelan Nilai Tukar Rupiah terhadap Dollar Amerika Menggunakan Deret Waktu Hidden Markov Empat Waktu Sebelumnya
Abstrak: The exchange rate of Rupiah to US Dollar fluctuates according to time in a long period. An existing exchange rate might happen again in the future. Assume that the causes of the fluctuation are not observed directly and form a Markov chain, then the exchange rate of Rupiah to US Dollar can be modeled by the hidden Markov time series. In this research, the model used to describe the exchange rate of Rupiah to US Dollar is the four previous time in hidden Markov time series. This model assumes that the exchange rate of Rupiah to US Dollar depends on Markov chain explained by the cause of occurence and the four previous exchange rates of Rupiah to US Dollar. The model parameter is estimated by using the maximum likelihood method, while the estimation itself is calculated using the expectation maximization algorithm, which is implemented using Mathematica. After estimating the parameter, the exchange rate of Rupiah to US Dollar are calculated. The results are as follows. The symmetric mean absolute percentage error (SMAPE) is 2,1%, the maximum absolute error is 19,16%, the minimum absolute error is 0,0036%, and only 1,95% of the whole absolute percentage error that is bigger than 10%. These results show that the four previous time in hidden Markov time series can describe the exchange rate of Rupiah to US Dollar very well.
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