Judul: Pengembangan sistem koreksi frasa bahasa indonesia berbasis konteks
Abstrak: This research proposes a new method, phrase pair together with opportunity value to give a proposed word as a correction result. Conditional probability formula is used to determine the value of opportunities of each phrase pair. Formation of phrase in this study is determined among words that are in a sentence and considered to have similar contexts. The corpus used consist of 2000 documents originating from the Laboratory of Information Retrieval, Department Computer Science, Bogor Agricultural University. Processing of document produces 90,077 pairs of phrases together with the opportunity values. Testing of this correction system uses two types of queries (common query and specific query) and two type of errors (context error and Damerau error). The context based correction system is appropriate to implement on the type of specific query. Accuracy values produced by system are 60% on spesific query and 56.67% on spesific query with context error and Damerau error. Restriction of system by giving 10 proposed words causing there is a correct proposed word but which is not included in 10 proposed words. The solution is by increasing the proposed word produced by the system. In common query, the system has poor performance. The poor accuracy emerges due to the lack of method in determination of correcting word, there are pair phrases that have high opportunity value but do not have similar context and are not included in Big Dictionary of Indonesian (KBBI) and there are pair phrases that have similar context but have low opportunity value.
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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: Heavy Metal Content of Hg, Pb, and Cd in Skipjack Tuna Katsuwonus pelamis (Linnaeus, 1758) in Waters of Bacan Island, North Maluku
Abstrak: Pulau Bacan memiliki sumberdaya perikanan yang sangat potensial. Namun, di Pulau Bacan berlangsung aktivitas antropogenik seperti pertambangan, pertanian, perkebunan, dan pelabuhan yang berpotensi menimbulkan pencemaran logam berat di perairan. Penelitian ini bertujuan menganalisis tingkat bioakumulasi logam berat Hg, Pb, dan Cd pada ikan cakalang (Katsuwonus pelamis Linnaeus, 1758) di perairan Pulau Bacan, Halmahera Selatan, Maluku Utara. Pengambilan sampel air dan pengukuran parameter kualitas air serta pengambilan bagian daging, insang, dan hati ikan cakalang berlangsung pada bulan Februari 2022. Pada air, kandungan logam berat Hg, Pb, dan Cd telah melampaui baku mutu. Kandungan logam berat Hg, Pb, dan Cd tertinggi pada ikan cakalang ditemukan pada hati, sedangkan terendah pada daging. Pada daging ikan cakalang, tingkat akumulasi Hg, Pb, dan Cd tergolong rendah., Bacan Island has a high potential of fishery resources. However, anthropogenic activities such as mining, agriculture, and ports taking place on Bacan Island cause heavy metal pollution in the waters. This study aimed to analyze the bioaccumulation level of heavy metals such as Hg, Pb, and Cd in skipjack tuna (Katsuwonus pelamis Linnaeus, 1758) in the waters of Bacan Island, South Halmahera, North Maluku. Water sampling, measurement of water quality parameters and fish sampling was conducted in February 2022. In the water, the heavy metals concentration of Hg, Pb, and Cd has exceeded the quality standard. The highest concentration of Hg, Pb, and Cd was found in the liver, while the lowest was in the muscle. In skipjack tuna muscle, the accumulation level of Hg, Pb, and Cd is low.
Keyword: Bacan Island, heavy metal, skipjack tuna