Judul: Perbandingan Metode Knowledge Graph dan Metode Conceptual Graph sebagai Teknik Representasi Teks Berbahasa Indonesia
Abstrak: Knowledge graph (KG) and conceptual graph (CG) methods are mathematical concepts that can be simplified to understand the content of a text. To determine the effectiveness of both methods, this thesis compares both of them. The objective of this research is to compare the knowledge graph and conceptual graph methods in representing the Indonesian text. The Research carried out by analyzing sentences and creating graph on the sample sentences using both methods. The study states that the knowledge graph and conceptual graph methods can be applied as the Indonesian text representation techniques. Based on the aspect of the process, KG is easier than CG because KG has limited number of concepts and relationships. In the aspect of the results, KG has focused on the concept which is explained, meanwhile CG has focused on the concept which is explaining. Based on the aspect of long time goal, KG supports the automatical abstraction of text, effectively and efficiently, whereas CG does not yet support for abstraction. Knowledge graph method is more feasible for an automatic procedure.
Keyword: conceptual graph, graph, knowledge graph, text

Judul: Perbandingan Metode Knowledge Graph dan Semantic Network untuk Analisis Teks Berbahasa Indonesia.
Abstrak: Knowledge is something that related to the learning process. Knowledge is obtained from various sources, for example from text. In many cases the text contains ambiguity. Knowledge graph and semantic network are mathematical concepts that can be used to resolve the ambiguity. The objective of this research was to compare the two methods to analyze an Indonesian text. The comparison was done by emphasizing on the aspect of process and on the aspect of graph structure. Research done by making graph on sample sentences in Indonesian text using both methods. Based on the aspect of the process, steps of the knowledge graph is more complex, but its automatic procedure is easier than the semantic network. It is easier because the knowledge graph has limited number of concepts, whereas the semantic network has an unlimited number of concepts. Based on the aspect of graph structure, relation labels of the knowledge graph has no meaning, it refers to the eight binary relationships, whereas the relation labels of the semantic network have meaning to describe relation of the concepts. Both methods have advantages and disadvantages but from this research it has been known that the knowledge graph is more feasible for an automatic procedure.
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Judul: Ketahanan Benih Udang Vaname Litopenaeus vannamei SPF (Specific Pathogen Free) Terhadap Infeksi Buatan TSV (Taura Syndrome Virus)
Abstrak: White shrimp culture had suffered from losses due to the outbreak of TSV in which mortality could achieved 95%. Therefore SPF shrimp is required as a preventive effort. This research was conducted to evaluate the resistance of white shrimp seed obtained from several SPF broodstock to TSV. Infection of TSV was carried out by feeding flesh of TSV-infected shrimp to PL 30 for 2 days at a feeding rate of 50%. After that, shrimp was fed commercial diet at 10% feeding rate till the end of experiment (11 days of culture). Parameters observed included survival rate, clinical symptoms, and weigth gain. After 11 days of culture, all the tested shrimps were infected, showing clinical symptom namely black spot on the body and the tail became red. The highest survival rate was obtained at S6 code (77,33±3,51%), while the lowest was observed at S4 code but statistically was different significantly (P<0,05) compared to other.
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