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Abstrak :
Tesis ini membahas mengenai bagaimana audiens, khususnya pemelajar kebudayaan Jepang, memaknai nilai-nilai yang dianut masyarakat Jepang, yang tersemat di dalam berbagai judul shonen manga. Analisis penelitian ini berfokus pada pembaca manga sebagai audiens aktif, yang mungkin memaknai manga yang mereka baca dalam berbagai cara. Penelitian ini merupakan penelitian kualitatif dengan menggunakan paradigm interpretive-constructivism dan teori reception analysis untuk menganalisis pemaknaan pembaca manga. Hasil penelitian menyimpulkan bahwa pembaca yang memiliki pengetahuan mendalam mengenai kebudayaan Jepang memiliki kecenderungan untuk menegosiasikan nilai-nilai masyarakat Jepang dan membandingkannya dengan latar belakang sosial maupun kebudayaannya sendiri. Selain itu, penelitian ini menemukan bahwa nilai-nilai masyarakat Jepang tersebut tidak diaplikasikan secara langsung oleh pembaca yag mempelajari kebudayaan Jepang.

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This research focused on how audience, especially Japanese Studies learners, interpret Japanese ideologies that attached in many shonen manga's title. The research's aim is to find out how manga's reader as active audience interpret mangas that they read. It is a qualitative research that is using interpretive constructivism as its paradigm and reception analysis as its theory to analyze manga readers interpretation. The result of this research shows that reader who has insight about Japanese studies tends to negotiate Japanese ideologies and compares them with his/her social background or culture.

Abstrak :
ABSTRAK
Kapal termasuk dalam kategori Unmanned Surface Vehicles USV . Kendali kapal dapat dibagi menjadi tiga bagian utama, yaitu guidance system, control system, dan navigation system. Permasalahan utama pada bagian control system muncul karena lingkungan kerja USV yang dinamis, kompleks dan tidak terstruktur karena adanya gangguan seperti ombak, arus air, dan angin. Selain itu, dinamika USV sendiri pun tidak linier, time-varying dan coupled. Akibatnya, kendali berbasis model matematis menjadi terlalu kompleks. Beberapa peneliti telah mulai mengembangkan kendali kapal berbasis Neural Network NN , namun, berbagai metode yang diusulkan dalam literatur belum sepenuhnya berbasis NN. Masalah ini menjadi masalah pertama yang diselesaikan dalam disertasi. Dalam kaitannya dengan guidance system, disertasi ini membatasi masalah pada sistem kendali untuk kapal pengejar. Masalah ini menjadi masalah kedua yang diselesaikan dalam disertasi.Tujuan pertama penelitian ini adalah mengembangkan metode baru kendali berbasis supervised dan unsupervised NN untuk kapal double-propeller. Metode yang digunakan dalam pengembangan sistem kendali baru berbasis neural network adalah metode pembelajaran supervised Backpropagation Neural Networks BPNN serta metode pembelajaran unsupervised Self-Organizing Maps SOM dan Self-Organizing Incremental Neural Network SOINN . Metode SOM dan SOINN dipilih karena waktu pembelajarannya lebih cepat daripada waktu pembelajaran BPNN. Namun, SOM dan SOINN pada awalnya dikembangkan untuk image processing dan pattern recognition sehingga belum pernah digunakan untuk kendali. Pengujian sistem kendali yang dikembangkan dilakukan untuk sebuah model kapal dan purwarupa kapal berjenis double-proppeler melalui serangkaian simulasi sistem kendali, baik open-loop maupun closed-loop.Tujuan kedua penelitian ini adalah mengembangkan sistem kendali closed-loop kapal pengejar berbasis neural network menggunakan Ensemble Kalman Filter EnKF untuk memprediksi informasi radar. Sensor radar dipilih sebagai pendeteksi target karena dapat menghasilkan resolusi yang tinggi, sedangkan EnKF digunakan sebagai prediktor trayektori target dari informasi radar karena mampu meprediksi posisi target one-step ahead dan tidak memerlukan informasi state-space target. Namun, EnKF pada awalnya dikembangkan untuk prediksi cuaca sehingga belum pernah digunakan sebagai estimator trayektori pada suatu wahana pengejar.Hasil studi membuktikan bahwa metode kendali baru berbasis neural network BPNN, SOM dan SOINN yang dikembangkan berhasil digunakan sebagai kendali kapal nirawak. Simulasi yang dilakukan terhadap data asli kapal double-propeller menunjukkan bahwa kendali BPNN mampu menghasilkan error rendah, namun waktu pelatihannya lama. Masalah ini diselesaikan dengan metode kendali berbasis SOM yang memerlukan waktu pelatihan lebih singkat. Namun, kendali SOM memerlukan jumlah neuron yang optimum untuk dapat menghasilkan error yang rendah. Permasalahan ini diselesaikan dengan metode kendali berbasis algoritme pembelajaran SOINN yang dimodifikasi. Hasil simulasi menunjukkan bahwa kendali SOINN mampu menentukan jumlah neuron mapping optimum pada kendali SOM.Skema sistem kendali kapal pengejar telah dirancang menggunakan EnKF sebagai prediktor trayektori target dari data radar dan kendali closed-loop neural network. Hasil simulasi membuktikan bahwa sistem kendali closed-loop kapal pengejar berbasis neural network BPNN, SOM dan SOINN yang diusulkan telah terbukti mampu mengejar kapal target. Waktu tumbuk kapal pengejar dengan kapal target bergantung pada kecepNeural Network Controlatan maksimum kapal pengejar, di mana semakin tinggi kecepatan kapal pengejar, maka tumbukan semakin cepat terjadi. Waktu tumbuk juga bergantung pada threshold jarak tumbuk, karena semakin besar threshold jarak tumbuk, maka semakin besar kemungkinan terjadinya tumbukan. Untuk sistem kendali kapal pengejar yang dirancang, sistem kendali unsupervised SOM dan SOINN cenderung mengikuti target sedangkan sistem kendali supervised BPNN mampu memotong lintasan target. Hal ini mengindikasikan bahwa sistem kendali SOM dan SOINN cocok digunakan sebagai kendali kapal follower karena error pengendaliannya kecil dan berbasis mapping, sedangkan sistem kendali BPNN cocok digunakan sebagai kendali kapal pengejar karena prinsip kerja pengendalinya adalah minimisasi error. Dalam kasus target bermanuver dan kecepatan maksimum kapal pengejar sekitar setengah dari nilai kecepatan rata-rata kapal target, hanya sistem kendali berbasis SOINN yang mampu menumbuk kapal target.

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Autonomous boats are categorized as Unmanned Surface Vehicles USVs . Its control can be divided into into three main parts, namely guidance system, control system and navigation system. The challenges of USV control system generally occur due to the highly dynamic, complex and unstructured USV environment due to the waves, water currents and wind. In addition, the USV dynamics itself are not linear, changing over time, and coupled so that the USV control design with a mathematical approach becomes too complex. Various Neural Networks NN based control systems have been developed, however, the methods proposed in literatures are not fully based on NN. This problem is the first problem addressed in this dissertation. In relation to the guidance system, this dissertation limits the problem on the control system for a chaser boat. This problem is the second problem addressed in the dissertation.The first objective of this research is to develop a new method of supervised and unsupervised NN control for a double propeller boat. The new NN based control system are developed using the supervised learning Backpropagation Neural Networks BPNN as well as the unsupervised learning Self Organizing Maps SOM and Self Organizing Incremental Neural Network SOINN methods. The SOM and SOINN methods are chosen because their learning timea are supposedly faster than that of BPNN. However, they were originally developed for image processing and pattern recognition, thus, their utilizations as control systems are not common. Justifications for these new neural network control system are conducted for a boat model and real double propeller boat prototype through a series of control system simulations, both open loop and closed loop.The second objective of this research is to develop a closed loop NN control system for a chaser boat by using Ensemble Kalman Filter EnKF as the predictor of target boat future position from radar data. Radar sensor is chosen because it is the most promising target tracking technology that can provide the highest resolution among other available options. Meanwhile, EnKF prediction method is chosen because it can perform a one step ahead prediction and does not require any state space data from the target boat. However, EnKF was originally developed for weather prediction, thus, it has never been used as a trajectory estimator on a chaser boat.The results of the study showed that the newly developed control methods based on BPNN, SOM and SOINN neural network can be utilized as the controller of an autonomous boat. The conducted simulations on real double propeller boat data have proven that BPNN controller can produce low error, but its learning process is quite timely. This problem is solved by a controller based on SOM which requires shorter computational time. However, SOM controller requires an optimum number of neurons to produce a low error. A controller trained by using a modified SOINN algorithm is developed to solve this issue. The simulation results show that SOINN controller can determine the optimum mapping neuron in SOM controller.Neural network control system for a chaser boat has been designed by using EnKF to predict the target trajectory from radar data and a closed loop neural network controller. The simulation results showed that the chaser boat closed loop control based on BPNN, SOM and SOINN can work well in chasing hitting the target boat. Time of the first hit depends on the maximum velocity of the chaser boat. As the velocity of the chaser boat gets higher, the hit occurs faster. In addition, the first hit also depends on the pre defined hitting distance threshold, as bigger threshold increases the hit probability. For the designed chaser boat control system, the unsupervised control system based on SOM and SOINN tend to follow the target, whereas the supervised control system based on BPNN can intercept the trajectory of the target. This results indicate that the SOM and SOINN controller is suitable to be used as the controller in a follower boat due to its low control error and mapping principle. Meanwhile, BPNN controller is suitable to be utilized as the controller in a chaser boat since its basic control principle is minimizing error. In the case of maneuvering target and the maximum speed of the chaser boat is about half the average velocity of the target boat, only SOINN based controller can hit the target boat.

Abstrak :
Selama Piala Dunia 2002 berlangsung, media massa di Jepang, khususnya televisi memusatkan perhatian pemberitaan kepada hal-hal yang berhubungan dengan turnamen tersebut. Berbagai macam berita dan informasi menghiasi layar televisi Jepang selama kompetisi berlangsung. Salah satu hal yang tidak lepas dari pemberitaan televisi di Jepang adalah informasi mengenai tim nasional Jepang, mulai dari profil pemain sampai pelatih yang berpartisipasi dalam kejuaraan empat tahunan tersebut. Melalui berita-berita mengenai tim nasional Jepang selama Piala Dunia 2002 tersebut, televisi berperan dalam membentuk nasionalisme masyarakat Jepang selama turnamen diadakan. Melalui teori ruang nasional, skripsi ini membahas peran televisi terhadap pembentukan nasionalisme masyarakat Jepang melalui studi kasus pemberitaan tim nasional Jepang selama Piala Dunia 2002 yang diselenggarakan di Jepang dan Korea Selatan. When FIFA World Cup 2002 being held in Japan and South Korea, Japan?s mass media, especially television, focused their attention to anything that related to the tournament. Any kind of news and information about World Cup 2002 are emblazoned Japan?s television as long as the competition is on the run. One thing that can?t be separated from Japan?s television?s attention is the news and information about their own soccer national team, started from profile about players to coach that participated on that tournament. Through the news about Japan?s soccer national team as the tournament was being held, television played it?s role to form Japanese?s nationalism. By using nation space theory, this study investigate television?s role toward figuration of Japanese?s nationalism through case study of news about Japan?s soccer national team as the FIFA World Cup 2002 is being held in Japan and South Korea.

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This report deals with the heat exchanger modeling for the Cummins engine. The engine is used in dual fuel project that ongoing at Queensland University of Technology, interested in developing and optimizing a dual fuel engine developed by Uli Kruger. The design being calculated and designed to achieved appropriate heat exchanger that will be used at the engine. The heat exchanger need to provide sufficient heat transfer energy that required to vaporize the ethanol. The limited space that available to install the heat exchanger also needs to be considered. To overcome the requirement, student tried to calculate and design a copper tube coil heat exchanger. Beside heat exchanger, this report also determines the hazard and safety issues not only during the dual fuel engine test campaign but also when services and modification are carry out.