Judul: Management strategies of blue dolosi (caesio caerulaurea) at guraici islands South Halmahera of North Moluccas Province
Abstrak: Exploitation of blue dolosi (Caesio caerulaurea) at Guraici Islands are longstanding. The catches of fishermen decreased, while efforts to catch (trip) is increasing. This condition is feared to exceed the optimum sustainable. therefore it is necessary to evaluate the presence of blue dolosi fish stocks as a basis for sustainable management strategies. The data was collected directly by following the catching once a month throughout the year and filling the questionnaire. The results of the study, the size of the blue dolosi caught during the study ranged 165-327 mm. The length of the first fish caught by moroami is 247.83 mm. The size of fish that mature gonads is 241.30 mm. Spawning occurs throughout the year and the peak occurred in April and June. Catching occurred all year round and peak in August. The rate of exploitation (E) = 0.58 / year indicated that over fishing has occurred but did not achieve the maximum sustainable production. Maximum production is reached when the value of exploitation rate of 0.80 / year. Dolosi blue production at Guarici sea on May 2010 till April 2011 amounted to 49 361 kg / year. Maximum sustainable yield (MSY) amounted to 52 974 kg / year. To prevent overfishing, dolosi blue fish that first caught (Lc) maintained on the size 247.83 mm equivalent to the size of the mesh used in the bag is 0.75 inches and 2 inches on the wing, by maintaining the rate of exploitation of 0.58 / year, equivalent to the effort (trip) catching as many as 1956/year.
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Judul: Strategi pengelolaan sumberdaya perikanan rajungan (Portunus pelagicus) untuk pemanfaatan berkelanjutan
Abstrak: Blue swimming crab (Portunus pelagicus) resources is one of high economic value commodity of marine products and numerous in Kolaka Regency waters. Kolaka Regency including in the Bone bay region, in which this region is the second largest contributor (21%) after the northern coast of Java (28%) of the blue swimming crab total production throughout Indonesia since 2001 until 2008. Estimated total blue swimming crab production in Kolaka Regency decreased because of increasing fishing activities, thus requiring a comprehensive study. The purpose of this study: 1) Knowing the potential resources of blue swimming crabs in the Bone bay waters, Kolaka Regency, Southeast Sulawesi Province; 2) Determine the ecological economics sustainability index of the blue swimming crab resources 3) Analyze the feasibility level of catch effort; 4) Determine the strategic management direction of the blue swimming crab resources for sustainable uses. The research shows that the alleged maximum sustainable yield (MSY) of 129 997 kg, optimum fishing effort (fMSY) equal to 21 739 trips. Sustainability index values obtained 1.63 (very good). Catch effort feasible to be developed,the value of NPV = Rp27 857 867, Net B/C = 3.15, and IRR = 60.62%. There are several fishing ground which clashed with the allocation based on local government policy. Blue swimming crab management resources require attention from governments and policymakers and all stakeholders. For that to be implemented management resources policies includes: 1) rescue policies, and (2) utilization policy, in order to create sustainability and obtained an optimal and sustainable utilization.
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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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