Judul: Application of Microwave Heating in Cocoa Pod Husk (CPH) Biomass Hydrolysis for Bioethanol Production
Abstrak: Cocoa Pod Husk (CH) is one of the most abundant biomass in Indonesia, but its use is still limited to making fertilizer and animal feed. The abundant amount of CPH and its contents are considered suitable to be used as raw material in the second generation ofethanol production. The high concentration of lignin in CPH can inhibit the rate of hydrolysis, so it is necessary to pre-treat CPH samples. It is also necessary to pay attention to the method used in the process of hydrolyzing CPH samples prior to fermentation so that they can produce high ethanol during the fermentation process. Fermentation stress can affect the growth and productivity of yeast isolates, so it is necessary to characterize the isolates in terms of their resistance to various fermentation stresses. This research began with the process of preparing CPH samples and continued with the process of hydrolyzing the samples using microwave heating. Rejuvenation of yeast isolates was carried out by growing isolates on YPD medium. Yeast isolates were then selected based on their ability to ferment xylose using oxidative fermentative media. Isolate characterization was carried out on selected yeast isolates including resistance to temperature stress (30 °C, 37 °C, and 40 °C), pH stress (3, 4, and 5), and ethanol stress (6%, 8%, 10%, 12%, and 14%) using the spot assay method. Growth curves were prepared by measuring the optical density (OD) value of the yeast isolates Y001 and Y003 at a wavelength of 600 nm per 6 hours for 72 hours. The final stage of this study was to measure the ethanol produced during the fermentation process using HPLCevery 24 hours for 96 hours. Analysis of the chemical components of the two P H samples before and after treatment using hydrogen peroxide showed a decrease in lignin levels of34% of the total lignin samples. Hydrolysis of ICS 60 variety CPH samples using the microwave-assisted hydrolysis method produced hydrolysate with a high concentration of glucose-xylose with a heating time of 12 minutes. Selection of ethanol fermenting yeast using oxidative fermentative media showed that isolates Y001 and Y003 were able to ferment xylose and were resistant to various fermentation stresses including being able to grow up to 40 °C, resistant to ethanol stress up to 14% and able to grow at pH .3 The highest ethanol was produced at the E3 (liquid hydrolysate + 1% yeast extract + 2% peptone + 2% glucose + 2% xylose) treatment was 11.3 g/L with ethanol yield of 0.31 g/g., Cocoa Pod Husk (CPH) merupakan salah satu biomassa yang melimpahdi Indonesia, akan tetapi pemanfaatannya mash terbatas pada pembuatan pupuk dan pakan ternak. Melimpahnya jumlah CPH dan kandungan yang dimilikinyadinilai c o o k untuk dijadikan bahan baku dalam produksi etanol generasi kedua. Konsentrasi lignin yang tinggi pada CPH dapat menghambat laju hidrolisis sehingga perlu dilakukannya pra-perlakuan sampel CPH. Metode yang digunakan dalam proses hidrolisis sampel P H sebelum difermentasi juga perlu diperhatikan sehingga dapat menghasilkan etanol yang tinggi s a t proses fermentasi. Cekaman fermentasi dapat mempengaruhi pertumbuhan dan produktivitas isolat khamir sehingga perlu dilakukan karakterisasi isolat berupa
Keyword: Pretreatment, hydrolysis, microwave-heating, fermentation-related stresses, ethanol

Judul: Pemanfaatan Pod Kakao untuk Produksi Etanol melalui Hidrolisis Menggunakan Kapang Aspergillus niger dan Trichoderma viride
Abstrak: Indonesia is one of the largest cocoa producing country in the world, and according to harvest data from 2005, Indonesia produces 13% cocoa from the total world cocoa demand. Fresh cocoa fruit consists of 75.50% of the fruit shells, 21.18% of seeds and 2.60% of placenta. Cocoa pod is one of lignoselulosic waste containing of 31.25% cellulose. The cellulose composition large enough to make cocoa pod potential to be processed into ethanol. So far, ethanol production is more focused on raw materials such as cassava, sweet potatoes, sugar cane, sago, and several types of starch which is less effective because these materials compete with food. This research aimed to find out the effects of substrate’s type of cocoa pod, the type of mold, and time of hydrolysis optimized to produce high levels of reducing sugar and producing ethanol from the best hydrolisate. This research were performed into three stages. The first stage was the preliminary stage that includes the characterization of cocoa pods and pretreatment on cocoa pod including reduction in size, degumming, and delignification. The second stage was the hydrolysis of cocoa pod using two types of fungus (Aspergillus niger and Trichoderma viride), two types of substrates (non-delignified and delignified cocoa pods), hydrolysis time (11 days), sampling on days 1, 3, 5, 7, 9, and 11. Last stage was the fermentation using the best hydrolisate, using Saccharomyces cerevisiae culture. This research utilized completely randomized factorial design with three factors and two replications. The first factor was the type of fungus, which consists of two levels of Aspergillus niger and Trichoderma viride. The second factor was the hydrolysis time with 6 degree of day (1, 3, 5, 7, 9, and 11). The third factor was the type of substrate with two levels of the substrate non-delignified and delignified cocoa pods. Material characterization results obtained the cellulose content of cocoa pods is 28.78% (wb), Hemicellulose 8.70% (wb) and 42.90% lignin (wb). After delignification the results obtained cellulose content is 32.23% (wb) and 31.00% lignin (wb). The delignification efficiency was 27,74%. Based on the results of range analysis with α <0.05 at the hydrolysis stage substrate types affected significantly on reducing sugar concentration, whereas the type of fungus and hydrolysis time does not affect real.
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Judul: Implementation of Spatio-Temporal Change Query in Relational Database.
Abstrak: Geographic object changes in various views. Object changes are recorded using a model of static storage. No historical connection between old version data and new version data has been built. For that, a storage model of spatio-temporal queries that can analyze spatio-temporal changes has been developed. The object changes the geometry are grouped according to the taxonomy of Spatio-Temporal Pattern Change. This research has been able to apply the query patterns change including born, expand, merge, contract, split, normal and die. This query based on geometric (area) changes. The implementation of spatio-temporal change queries represents an object changes continuously with easy, change detection is done by comparing two versions of data. Keyword: spatio-temporal change query, spatio-temporal change pattern.
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