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"A ship usually performs maneuvers under the influence of external forces and moments, such as wind, waves, and current. Therefore, it is important to understand the maneuvering behavior of ships under the action of external forces. This paper discusses the turning maneuvers of an Indonesian roro ferry under the combined influence of constant wind and regular waves using the mathematical modelling group (MMG). The ship’s position relative to the wave trough is added to the original MMG model to estimate the exciting forces and moment induced by the waves. The results of a numerical simulation show that the effect of wave height on turning ability is more significant for a small wavelength; this effect decreases as the wavelength increases. The effect of wavelength on the sway force and yaw moment is more significant compared with its effect on the surge force. The ship’s initial position relative to the wave trough does not have a significant effect on the turning characteristic and it can be neglected for the present study’s subject ship. Overall, the results of the present work compare well with published data."

"Pesatnya perkembangan ekonomi menyebabkan kebutuhan manusia menjadi tidak terbatas. Usaha yang dapat dilakukan untuk pemenuhan kebutuhan hidup di masa yang akan datang adalah dengan melakukan investasi. Saham merupakan salah satu instrumen investasi dengan tingkat keuntungan yang menarik, namun memiliki risiko kerugian yang tinggi. Hal ini disebabkan oleh adanya pergerakan harga saham yang cenderung tak menentu selama periode waktu tertentu. Untuk meminimalkan risiko kerugian, perlu dilakukan prediksi pergerakan harga saham. Prediksi yang akurat akan membantu para investor dalam menentukan nilai saham di masa yang akan datang. Pada penelitian ini, dilakukan perbandingan untuk memprediksi pergerakan harga saham menggunakan tiga algoritma supervised machine learning yaitu Random Forest, Support Vector Regression (SVR) dan K- Nearest Neighbor (KNN) berdasarkan tingkat akurasinya. Sutau model dikatakan akurat jika memiliki nilai Root Mean Square Error (RMSE) dan Mean Absolute Error (MAE) yang lebih rendah. Pada penelitian ini, diperoleh hasil prediksi harga penutupan saham terbaik menggunakan metode Support Vector Regression dengan melihat rendahnya nilai RMSE dan MAE yang dihasilkan dibandingkan dengan dua metode lain. Dalam perhitungannya, penelitian ini menggunakan histori data harian dari website investing.com. periode Maret 2017 hingga Februari 2020 dari tiga perusahaan di Indonesia yang terdaftar dalam IDX30.

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The fast growth of economic development causes human needs to be immeasurable. One of the efforts that could be done to fulfill life needs in the future was Investation. Stock is one of the Investation instruments with interesting benefits but has high- risk loss caused by the unstable stock market trend between some period. For minimalizing the risky loss, the literati need to predicting the stock rate trend. The accurate prediction will help the investor in choosing a stock value in the future. In this study, the literati make a comparison to predict stock market trend with three kinds of algorithms supervised machine learning that are Randon Forest, Support Vector Regression (SVR), and K-Nearest Neighbor (KNN) based on their accurate level. A model could be said accurate just if they have a lower value of Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The best Stock Closing Price prediction will be obtained by the Support Vector Regression method and see how low the result of RMSE and MAE value is compared with another method. To calculate, the study uses a daily data history from investing.com website between March 2017 to February 2020 period. The object data is a three big company in Indonesia which listed in IDX30."

"Metode Conjugate Gradient merupakan salah satu cara untuk optimumkan fungsi f(x) untuk x tanpa kendala (unconstrained optimisation). Optimisasinya dijalankan secara iteratif dengan bantuan garis-garis arah yang saling conjugate. Karena metode ini sangat efisien dalam pemanfaatan storage, maka timbullah usaha untuk mengembangkannya. Salah satu pengembangannya adalah dengan menghubungkan metode CG ini dengan metode BFGS, yang kemudian menghasilkan suatu metode baru yang disebut VSGCG."

"Tulisan ini membahas taksiran negative dari variansi kesalahan-kesalahan ukuran (Measurement Errors Variance) dimana data sampel diukur dengan 2 dan 3 metode ukuran. Dalam skripsi ini diberikan pembahasan mengenai kemungkinan terdapatnya taksiran negative dari vaniansi kesalahan-kesalahan ukuran dan bagaimana mengatasi masalah taksiran negatif tersebut, baik untuk data sampel yang diukur dengan 2 metode ukuran maupun data sampel yang diukur dengan 3 metode ukuran. Masing-masing pembahasan dimulai dengan model matematika, mencari taksiran dari vaniansi kesalahan-kesalahan ukuran, dan bagaimana mengatasi masalah taksiran negatif dari variansi kesalahan-kesalahan ukuran. Dibagian akhir tulisan diberikan sebuah contoh."

""The objective of this book is for readers to learn where approximation methods come from, why they work, why they sometimes don?t work, and when to use which of the many techniques that are available, and to do all this in an environment that emphasizes readability and usefulness to the numerical methods novice. Each chapter and each section begins with the basic, elementary material and gradually builds up to more advanced topics. The text begins with a review of the important calculus results, and why and where these ideas play an important role throughout the book. Some of the concepts required for the study of computational mathematics are introduced, and simple approximations using Taylor?s Theorem are treated in some depth. The exposition is intended to be lively and "student friendly". Exercises run the gamut from simple hand computations that might be characterized are "starter exercises", to challenging derivations and minor proofs, to programming exercises. Eleven new exercises have been added throughout including: Basins of Attraction; Roots of Polynomials I; Radial Basis Function Interpolation; Tension Splines; An Introduction to Galerkin/Finite Element Ideas for BVPs; Broyden?s Method; Roots of Polynomials, II; Spectral/collocation methods for PDEs; Algebraic Multigrid Method; Trigonometric interpolation/Fourier analysis; and Monte Carlo methods. Various sections have been revised to reflect recent trends and updates in the field"-- Provided by publisher."