Judul: Policy strategy of indonesia capture fisheries in regional fisheries cooperation in Western and Central Pacific Fisheries Commission (WCPFC)
Abstrak: Management cooperation of highly migratory stock in western and central Pacific Ocean implemented through regional fisheries cooperation organization namely (WCPFC). The status of Indonesia is Cooperating Non-Member with limited rights to determine managament and conservation measures in convention area but obligations semiliar with Member. The purpose of this study are ; (1) Analyze the fisheries management provisions in high seas are managed by WCPFC, (2) Analyze the economic impact of WCPFC provisions for Indonesia fisherman, and (3) Analyze Indonesia policy formulation to strengthen participation of fisheries management in WCPFC. The study uses primary data of provisions governing the WCPFC and national regulations related fisheries and regional cooperation. The collection of secondary data in Bitung Fishing Port in 2012, using a survey research design. Sampling was conducted using census method for the purse seine fisherman who fishing in WCPFC area and landing fish in Bitung Fishing Port. Data were analyzed qualitatively and quantitatively with content analysis. Regression analysis conducted on the factors that influence purse seine fisherman income To analyze fisheries policy strategies used methods AWOT. To prepare Indonesia's participation in the WCPFC are two provisions that bind the WCPF Convention and Conservation and Management Measures (CMM). Based on the readiness of national regulations, Indonesia Government should consider : (1) Status area, (2) Monitoring and Enforcement, and (3) Preparation of Regulation Legislation. Result of WTA Analysis is average value per person willingness to accept payment of Rp 4.774.000 per year (RP 397.433 per month). Meanwhile, the average fixed income every purse seine fishermen of Rp 20.520.000 per year (Rp 1.710.000 per month). Therefore, if prohibition of baby tuna fishing is implemented, the purse seine fishing revenue per month Rp.1.313.166,67 for the loss of Rp 397,433 per month. Strategy should be done are (1) Routine fisheries research (2) Development of a fishing port facilities and services (3) Strengthening the role of the tuna fishery associations (4) Strengthening the law enforcement system (5) Strengthening regional cooperation with the WCPFC (6) Development system information and data (7) Improved MCS (8) Determination document of Fisheries Management Planning (h) Strengthening fishing fleet and (9) regulation synergy of FAD installation.
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Judul: Utilization of Bigeye Tuna Allocated to the Indonesia Longline Fisheries in the Western and Central Pacific Fisheries Commission
Abstrak: Indonesia menjadi negara anggota di Western and Central Pacific Fisheries Commission (WCPFC) pada tahun 2013. Organisasi regional memberi Indonesia alokasi tangkapan tuna mata besar sebesar 5.889 ton per tahun namun hingga tahun 2019 pemanfaatan alokasi ini belum optimal. Penelitian ini bertujuan Untuk: menentukan tingkat pemanfaatan alokasi tangkap tuna mata besar, menghitung kerugian akibat dari tidak optimumnya pemanfaatan alokasi tangkapan tuna mata besar Indonesia di WCPFC dan menghitung jumlah kapal rawai tuna yang ekonomis untuk memanfaatkan alokasi tangkapan tuna mata besar di kawasan WCPFC. Data yang digunakan dalam penelitian ini adalah statistik perikanan tuna Indonesia di wilayah kerja WCPFC, kebijakan yang diterapkan WCPFC dan kinerja perikanan Indonesia dalam periode 2012-2019, pengolahan tuna untuk ekspor, aspek teknis dan biaya operasi kapal tuna. Dalam kurun tahun 2012–2019, armada perikanan rawai tuna Indonesia hanya memanfaatkan 43% dari alokasi tuna mata besar yang diberikan WCPFC. Dengan beberapa asumsi, kerugian yang diderita Indonesia selama periode 2016 hingga 2019 adalah rata-rata Rp 337.116.100.000 per tahun. Mempertimbangkan skala bisnis yang ekonomis, alokasi tuna mata besar tersebut dapat digarap oleh 136 unit kapal yang berukuran 40 GT.
Keyword: allocation, catch limit, bigeye tuna, tuna longline, WCPFC

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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