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Abstrak :
ABSTRAK
Di Indonesia, salah satu penyebab tingginya biaya BBM adalah adanya tindak pencurian dan penyelewengan BBM yang sering kali terjadi di tengah lautan. Hal ini bisa terjadi karena pada saat di tengah lautan, segala kegiatan kapal tersebut tidak bisa dipantau oleh pusat operasional manajemen kapal. Selain upaya hukum, upaya pengawasan kapal melalui teknologi terbaru juga terus dilakukan, salah satunya adalah teknologi Vessel Monitoring System (VMS) berbasis Machine to machine (M2M). Perkembangan teknologi VMS dan telemetri telah memungkinkan pengawasan kondisi mesin dan pemakaian BBM kapal yang sedang berlayar secara online dan real time. Dengan menambah perangkat pengukuran pemakaian bahan bakar tersebut, diharapkan meningkatkan kecepatan koordinasi dan penanganan di lapangan saat terjadi ketidakwajaran pemakaian BBM. Kecepatan dalam mengetahui adanya ketidakwajaran ini sangat penting, karena proses pencurian minyak sering kali dilakukan dalam waktu singkat. Pencurian minyak dengan modus ilegal tapping di darat hanya memerlukan waktu 15 menit untuk 2000 liter (2 ton) BBM, sementara di laut diperlukan sekitar 5 jam untuk memindahkan 12 ton BBM, atau sekitar 2.4 ton per jam untuk sebuah kapal saja. Masalahnya untuk mengetahui ketidakwajaran tersebut masih tergantung pada analisa tenaga ahli yang memerlukan waktu yang lama untuk melakukan analisa berbagai parameter telemetri yang ada. Berdasarkan kondisi di atas, penelitian ini melakukan analisis statistik terhadap data telemetri terutama data pergerakan kapal dan aktivitas mesin untuk menentukan koefisien pergerakan kapal, lalu merancang sistem pengklasifikasi kewajaran pemakaian BBM dengan metode Naive Bayes dan Logistic Regression. Metode ini dipilih karena bisa memberikan hasil yang baik untuk prediksi data-­data numerik maupun diskrit. Hasil penelitian ini menunjukkan bahwa data telemetri dari sistem VMS dapat digunakan untuk mendeteksi adanya ketidakwajaran pemakaian BBM. Untuk kebutuhan klasifikasi kewajaran pemakaian BBM pada data telemetri kapal, algoritma pengklasifikasi Naive Bayes memiliki akurasi hingga 92% pada data sampel dan Logistic Regression mampu mendeteksi dengan akurasi hingga 96% pada data sampel.

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ABSTRACT
In Indonesia, one of the causes of high fuel costs is the occurrence of theft and misuse of fuel which often occurs in the middle of the ocean. This can happen because when in the middle of the ocean, all the activities of the ship cannot be monitored by the ship management operational center. In addition to legal efforts, efforts to monitor ships through the latest technology are also being carried out, one of which is the Machine to Machine (M2M) Vessel Monitoring System (VMS) technology. The development of VMS and telemetry technology has enabled monitoring of engine conditions and fuel consumption of ships that are sailing online and real time. By adding the fuel consumption measurement device, it is expected to increase the speed of coordination and handling in the field when there is an irregularity in the use of fuel. Speed in knowing the existence of this irregularity is very important, because the process of oil theft is often done in a short time. Theft of oil by illegal tapping on land only takes 15 minutes for 2000 liters (2 tons) of fuel, while at sea it takes around 5 hours to move 12 tons of fuel, or around 2.4 tons per hour for a ship. The problem is to find out the irregularities that still depend on the analysis of experts who need a long time to analyze various parameters of existing telemetry. Based on the above conditions, this study conducted a statistical analysis of telemetry data, especially ship movement data and machine activity to determine the coefficient of ship movements, then designed the fuel usage irregularity classification system with the Naive Bayes and Logistics Regression. This method was chosen because it can provide good results for predicting numerical and discrete data. The results of this study indicate that telemetry data from the VMS system can be used to detect any irregularities in using BBM. For the needs of the fairness classification of BBM usage on ship telemetry data, the Naive Bayes classification algorithm has an accuracy of up to 92% in sample data and Logistic Regression is able to detect with accuracy up to 96% in sample data.

Abstrak :
Karya Akhir ini membahas mengenai pencegahan illegal fishing melalui vessel monitoring system yang di fokuskan di Kepulauan Natuna. Kasus illegal fishing di wilayah Kepulauan Natuna merupakan salah satu yang tertinggi di indonesia dan berdampak pada rusaknya sumber daya perikanan dan kelautan. Studi ini akan menjelaskan illegal fishing sebagai bagian dari kejahatan lingkungan yang dicegah dengan menggunakan vessel monitoring system yang termasuk ke dalam bentuk pendekatan regulasi sosial yang merupakan bagian dari pencegahan kejahatan lingkungan. Pencegahan kejahatan illegal fishing melalui vessel monitoring system akan dianalisis dengan menggunakan konsep situational crime prevention dan teori pilihan rasional.

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This Thesis is about crime prevention against illegal fishing through Vessel Monitoring System which focused on Natuna Islands. The case of illegal fishing in the Natuna Islands region is one of the highest in Indonesia and has an impact on the destruction of fishery and marine resources. This study will explain illegal fishing as part of environmental crime that is prevented by using vessel monitoring system that is included in the form of social regulation approach is part of a neighborhood crime prevention. Crime prevention against illegal fishing through vessel monitoring system will be analyzed by using concept of the situational of crime prevention and theory of rational choice.

Abstrak :
Directorate General of Monitoring and Controlling Marine Resources and Fishery, Ministry of Marine and Fishery since 2004 had developed Vessel Monitoring System (VMS) aiming at supporting the monitoring and controlling towards illegal fishing that violated the prevailing rules of laws of sea territorial or Exclusive Economic Zones in a state. The Policy Implementation of VMS should be done in line with the Law Number 3 year 2004 and the Minister's Decree that had been enforced, i.e., the form of monitoring system in fishing using stipulated VMS. To view the implementation of successive policies, the Hierarchy of Broomley Policies with their influential factprs based on implementation theory of Edward III policy was used. The policy was observed since at its policy, organizational and operational level: Just it was-at its operational level; the policy was measured. The development of VMS was done to improve the management of fishery resources through implementing monitoring and controlling towards fishing vessel activities as well as increasing the management of the fishery industry done by fishery companies and particularly to raise the law-abiding fishing vessel that fished and/or transported the fish towards the prevailing rules and regulations of managing the preserved, sustainable and accountable fishery. The research of the success of the implementation of VMS was conducted to evaluate the policy implementation and to know the extent to its impacts towards the accomplishments of VMS policy implementation using VMS method. It was done by taking the object of the implementation in Fishery Harbour of Samudera Nizam Zachman Jakarta. The method of the research used was survey method to 48 fishing vessel industries as the respondents. As for the data analysis, the regression analysis method was adopted and the adopted application to analyse the data was SPSS (Statistical Package for Social Science). The aspects used to evaluate the policy implementation were policy effectiveness, fairness, responsiveness, and procedure; whereas the policy accomplishments were measured with three aspects, i.e., obedience, goals accomplishments and efficiency. Based on the findings of the research, the policy implementation of the fishing vessel monitoring system with the VMS method had well been performed, and the aspects that obtained the highest score was the procedure aspects, meaning that procedurally the policy implementation had been well carried out. It went the same for the accomplishment of the policy implementation, i.e., the efficiency aspect which was the most successful aspect. Statistically, the application of the policy of fishing vessel monitoring system with the adoption of VMS method gave significant impacts towards the accomplishments of the policy. The implementation aspect that had the biggest impacts towards the accomplishments of the policy was the effectiveness aspects. It mean that, the policy application of the fishing vessel monitoring system with the adoption of VMS method that could be implemented effectively had great impacts towards the accomplishments of such policy. The conclusion of the research findings was the fact that the VMS was found effective in surveying the fishing activities in the Exclusive Economic Zone in the sea areas in Indonesia in creating the preservation of the fishery resources. By the result of the research, it was suggested the procedural implementation of the fishing vessel monitoring system had been properly applied, but this aspect gave no significant implication upon the accomplishment of the policy, the government should make an evaluation toward aspect of implementation that had significant influence toward the implication of the policy.