Judul: Penambahan modul pembentukan Word Graph kata kerja pada aplikasi BogorDelftConstruct
Abstrak: Knowledge Graph (KG) is one of natural language processing methods that is able to represent the result of semantic analysis of a text in a graph form. Until now, there are only a few researches using KG to do semantic analysis for texts in Indonesian language. They were mainly focus on analyzing text, constructing rules to analyze text and engineering to understand the text. Some other researches have done semantic analysis from various part-of-speech. Nevertheless, the results of the research have not been implemented yet. To realize a long term goal of doing text abstraction automatically, BogorDelftConstruct has been developed as an early stage prototype. In line with that, this research implemented semantic analysis for one part-of-speech in BogorDelftConstruct.
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Judul: Pengembangan Modul untuk Kamus Word Graph Kata Sifat Pada Sistem Aplikasi BogorDelftConstruct
Abstrak: One of natural language processing methods that represents the result of semantic analysis of a text in a graph form is Knowledge Graph (KG). Until now, there are only a few researches using KG to do semantic analysis for texts in Indonesian language. Those researches were mainly focus on analyzing text, constructing rules to analyze text and engineering to understand the text. Some other researches have done semantic analysis from various part-of-speech. Nevertheless, the results of the research have not been implemented yet. To realize a long term goal of doing text abstraction automatically, BogorDelftConstruct has been developed as an early stage. In line with that, this research implemented semantic analysis for one part-of-speech in BogorDelftConstruct. The objective of the research is to develop an adjective word graph dictionary module in BogorDelftConstruct system. The adjective to be analyzed have 19 word graph patterns formed by affixation. Process of forming word graph started by getting root word and affix that contained in input word using stemming based on Kamus Besar Bahasa Indonesia (KBBI). Root word is used to search part-of-speech in KBBI. Part-of-speech of root word and affix is used as parameter to determine which pattern of adjective word graph that is appropriate. The appropriate pattern which contains the meaning of the word is generated in the system. The process of determining the appropriate pattern can be considered as a testing stage. In this module, from 19 patterns of adjective word graph, only 18 patterns that can be identified. A pattern of adjective word graph that unidentified is me-kata benda-kan. Adjective word graph me-kata dasar-kan and me-kata benda-kan have a similar former affix. Because of that, the system was not able to distinguish the two patterns. From 250 input words which used in testing module, there were 13 errors which resulted in accuracy of 94,80%. The occurrences of the error, was due to incapability of stemming function to produce intended root word and the uncompleteness of KBBI.
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Judul: Kerentanan Strain Ikan Nila Terhadap Infeksi Streptococcus Agalactiae Penyebab Penyakit Streptococcosis
Abstrak: Strain ikan nila (Oreochromis niloticus) unggulan hasil pemuliaan telah banyak dilepas untuk meningkatkan produksi perikanan budidaya di Indonesia. Namun ada kendala yang dihadapi yaitu kasus kematian ikan akibat penyakit Streptococcosis yang dikhawatirkan akan menjadi penghambat keberhasilan budidaya ikan nila. Penyakit ini disebabkan oleh infeksi bakteri Streptococcus agalactiae. Penanganan yang kurang baik, padat tebar yang tinggi, lingkungan pemeliharaan yang buruk, manajemen pemberian pakan yang kurang baik menyebabkan terjadinya ketidakseimbangan lingkungan dan akhirnya ketahanan tubuh ikan menjadi menurun sehingga rentan terhadap serangan penyakit. Bakteri S. agalactiae memiliki kisaran inang (host range) yang luas dan kemampuan adaptasi lingkungan yang cukup baik. Berdasarkan potensi infeksi S. agalactiae yang cukup tinggi dan potensial inang yang besar, maka diperlukan informasi mengenai kerentanan antar strain ikan nila unggulan dan variasi respon imun antara ikan nila (cichlidae) dan ikan mas (non-cichlidae). Pertama, melakukan uji kerentanan empat strain ikan nila terhadap infeksi S. agalactiae NK1. Strain ikan nila yang dipergunakan adalah ikan Nila Srikandi, ikan Nila Nirwana, ikan Nila BEST dan ikan Nila Sultana. Keempat strain nila diinfeksi dengan S. agalactiae NK1 pada dosis kepadatan bakteri 103, 104, 105, 106 CFU/ekor dan satu kontrol yang diinjeksi dengan PBS, masing-masing 2 kali ulangan. Nilai LD50 yang diperoleh berkisar antara 103,20-103,45 CFU/ekor . Kedua, melakukan analisis parameter imunologis strain ikan nila dan ikan mas terhadap infeksi S. agalactiae NK1. Dipergunakan ikan Nila Srikandi yang memiliki nilai LD50 tertinggi dan ikan mas yang mewakili kelompok noncichlidae (sebagai kontrol). Ikan diinfeksi dengan S. agalactiae NK1 menggunakan dosis 103 CFU/ekor. Hasil penelitian menunjukkan bahwa ikan nila memperlihatkan perubahan pola renang (berdiam didasar, berenang tidak beraturan dan berenang berputar), perubahan anatomi makroskopis (pigmentasi, eksoptalmi, mata keruh, operkulum jernih, hemoragi pada pangkal sirip). Sintasan ikan Nila Srikandi sebesar 50% dan ikan mas 100% pada 15 hari masa pemeliharaan. Ikan mas tidak menunjukkan perubahan pola renang dan perubahan anatomi. Kematian tercepat terjadi pada ikan Nila Srikandi terjadi pada 96 jam pasca infeksi. Aktivitas lisozim menunjukkan perbedaan yang signifikan antara ikan Nila Srikandi dan ikan mas. Berdasarkan pengamatan terhadap preparat histopatologi diketahui bahwa otak ikan Nila Srikandi yang terinfeksi S. agalactiae mengalami meningoensefalitis, sedangkan pada ikan mas hanya mengalami meningitis. Streptococcus agalactiae merupakan patogen spesifik pada ikan nila, hal ini terbukti dengan sintasan ikan mas yang mencapai 100%.
Keyword: Kerentanan, strain nila, Streptococcus agalactiae