Judul: Kajian proses pembekuan dan daya simpan kultur bakteri laktat asal dadih untuk produksi kultur starter
Abstrak: Dadih is a traditional fermented milk of West Sumatra - Indonesia, fermented in bamboo tube. Some srains of lactic acid bacteria isolated from Dadih possess probiotic properties; hence, it is important to study the effect of preservation of the lactic acid culture on their viability and biochemical properties during frozen storage. Four strains of lactic acid bacteria isolated from Dadih which have good antimutagenic properties are Lactococcus lactis subsp lactis R-22, Leuconostoc paramesenteroides R-51, Lactobacillus casei subsp casei R-52 and Leuconostoc paramesenteroides R-62. The lactic culture were preserved by freezing at -20°C by different freezing methods, frozen in deep freezer (slow freezing) and frozen in dry ice-ethanol mixture (fast freezing). Glycerol 10%, dimethylsulfoxide (DMSO) 10% and skim milk 10% were used as cryoprotectant with phosphat buffer pH 7,0 as control. The cultures were stored in deep freezer at -20°C as well as -70°C. The addition of glicerol 10% in Lactobacillus casei subsp, etc
Keyword: Dadih cultur, Lactobacillus casei, Deep freezer

Judul: Studies On Freezing and Frozen Storage Of Lactic Bacteria Isolated from Dadih For Producing Starter Culture
Abstrak: Dadih is a traditional fermented milk of West Sumatra - Indocesia, fermented in bamboo tube. Some srains of lactic acid bacteria isolated fiom Dadih possess probiotic properties; hence, it is important to study the effect of preservation of the lactic acid culture on their viability and biochemical properties during frozen storage. Four strains of lactic acid bacteria isolated from Dadih which have good antimutagenic properties are Lactococcus Iactis subsp lactis R-22, Leuconostoc pmamesenteroides R-5 1, Lactobacillus casei subsp casei R-52 and Leuconostoc paramesenteroides R-62. The lactic culture were preserved by fieezing at -20°C by different freezing methods, frozen in deep freezer (slow fieezing) and frozen in dry ice-ethanol mixture (fast freezing).
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Judul: Sistem Pengklasifikasian Entitas pada Pesan Twitter Menggunakan Ekspresi Regular dan Naïve Bayes
Abstrak: The widespread use of social networks like Twitter encourages some institutions to find out the entities that are discussed and the sentiment toward the entities. This research aims to build a system that can extract entities in tweets and classify the sentiment from the tweets. Entity extraction process is done using regular expressions. Writing regular expressions can capture the diverse entities. Sentiment classification is performed using naïve Bayes classification with Multinomial and Bernoulli models. Sentiment in this research consists of three classes, namely positive, negative, and neutral. Before entering the classification, tweets are normalized by replacing the non-standard words with the standard ones. The test results show that regular expression is quite effective for the entity extraction process. As for the results of the classification, naïve Bayes method produces high accuracy (96.75% for Multinomial and 96.33% for Bernoulli). However, the accuracy obtained depends on the neutral class which amounts to 97.88% for Multinomial and 99.95% for Bernoulli, while the positive class are 85.66% and 33.13% and negative class are 33.67% and 0%.
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