Judul: The Development of Word Graph Formation System For Indonesian Text.
Abstrak: Knowledge graph is a new method which is used to describe and model natural language or human language. A word is a basic unit of natural language processing. Word graph is a graph which has connected structure of words. Ontology between word and token in word graph is represented by a node, 8 binary relationships, 4 frame relationships, and a focus. In this research, a system to construct a word graph from Indonesian text is developed. The software was initially developed by Mark van Koningsveld, which is called DelftCoStruct. On the previous version, knowledge graph method is not fully implemented. The first step in this research is analyzing the outline description and the requirement system. There are three principal requirements: formation and modification of word graph, analyzing text in word graph, and saving the dictionary capabilities. The second step in this research is designing specification system. The third step is developing and implementing the system designed. And the last step is validating system, to ensuring that all the requirements is fully implemented on this system. Keywords : natural language processing, knowledge graph, word graph, token, ontology, frame
Keyword: 

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.
Keyword: 

Judul: Potensi Aspirin Dalam Mengatasi Cekaman Panas Berdasarkan Kualitas Telur dan Total Protein Darah Puyuh (Coturnix coturnix Japonica)
Abstrak: Penelitian ini dilaksanakan untuk menguji potensi aspirin dalam mengatasi cekaman panas berdasarkan kualitas telur dan total protein puyuh. Asprin adalah jenis obat antipiretik yang bisa menghambat prostaglandin. Penelitian ini menggunakan 32 ekor puyuh, terdiri dari 16 ekor untuk perlakuan yang diberi cekaman panas 3 ºC selama 24 jam dan 16 ekor diberi perlakuan cekaman panas 35 ºC selama 8 jam setiap hari dalam waktu 2 minggu. Percobaan dibagi menjadi 4 kelompok, kelompok A (aspirin 0 mg/kgBB), kelompok B (aspirin 2.5 mg/kgBB), kelompok C (aspirin 5 mg/kgBB), dan kelompok D (aspirin 7.5 mg/kgBB). Pemberian aspirin dilakukan setiap pagi hari dan pengambilan sampel telur dilakukan setiap hari sejak awal penelitian dilaksanakan serta pengambilan sampel darah dilakukan pada minggu kedua. Hasil penelitian menunjukkan bahwa aspirin tidak dapat memulihkan kualitas telur puyuh dan total protein pada 24 jam cekaman panas. Akan tetapi, puyuh yang diberikan cekaman panas selama 8 jam dapat mengatasi cekaman panas dengan meningkatkan nilai kualitas telur dan mengembalikan nilai total protein ke keadaan normal pada dosis 7.5 mg/kgBB.
Keyword: aspirin, egg quail, heat stress, quail, total protein