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MODUL PRAKTIKUM RANCANGAN PERCOBAAN
Modul Praktikum Rancangan Percobaan ini kami susun sebagai pedoman bagi pelaksanaan mata praktikum Rancangan Percobaan, khususnya bagi mahasiswa pada Prodi Matematika dan Statistika Universitas Sulawesi Barat (Unsulbar).
BUKU AJAR STATISTIKA UNTUK PERGURUAN TINGGI
Judul : BUKU AJAR STATISTIKA UNTUK PERGURUAN TINGGI Penulis : Elva Susanti, S.Si.,M.Si Dr.Nurjanna Ladjin, SE, M,Si Laila Qadrini, M.Stat Vera Selviana Adoe, S.P., M.M Moh. Supratman, M. Pd Dr. Faula Arina,S.Si,M.Si Ukuran : 20,5 x 29 cm Tebal : 135 Halaman No ISBN : 978-623-56872-3-0 SINOPSIS Puji syukur kami panjatkan kehadirat Allah SWT atas karunia dan hidayah-Nya, kami dapat menyusun Buku Ajar Statistika untuk Perguruan Tinggi, yakni mata kuliah Statistika. Buku Ajar ini disusun berdasarkan RPS Statistika. Buku Statistika teridiri dari beberapa penulis/dosen Perguruan tinggi ternama. Isi Buku membahas mengenai Distribusi Frekuensi, Ukuran Pemusatan, Dispersi, Probabilitas, Populasi dan ...
DARI PANDE BASSI HINGGA PARIWISATA DESA PAMBOBORANG, SULAWESI BARAT
Pendirian Pusat Studi Pedesaan yang dinaungi oleh Universitas Sulawesi Barat patut diapresiasi. Kelahiran pusat studi ini dapat menjadi oase bagi dahaga kegiatan riset yang terkait dengan desa. Pembangunan desa yang terdapat di Sulawesi Barat harus didukung oleh penelitian ilmiah yang baik sehingga menghasilkan strategi pembangunan yang terukur dan memperhatikan kepentingan masyarakat desa. Terlebih jika melihat pada berbagai data tentang pembangunan yang tersedia, kemajuan yang dimiliki berbagai desa di Sulbar tidaklah setara satu dengan yang lain. Agar dapat mengakselerasi desa-desa yang masuk kategori tertinggal, dan meningkatkan kualitas pembangunan di desa-desa yang sudah lebih dulu maju, dibutuhkan sebuah ikhtiar ilmiah yang dapat menjadi dasar kebijakan bagi pembangunan di desa tersebut maupun kebijakan di level pemerintah daerah dan provinsi. Dan Pusat Studi Pedesaan Unsulbar memiliki beban tersebut di bahu para penelitinya.
Design and Analysis of Simulation Experiments
This is a new edition of Kleijnen’s advanced expository book on statistical methods for the Design and Analysis of Simulation Experiments (DASE). Altogether, this new edition has approximately 50% new material not in the original book. More specifically, the author has made significant changes to the book’s organization, including placing the chapter on Screening Designs immediately after the chapters on Classic Designs, and reversing the order of the chapters on Simulation Optimization and Kriging Metamodels. The latter two chapters reflect how active the research has been in these areas. The validation section has been moved into the chapter on Classic Assumptions versus Simulation Pra...
The Life and Times of Muhammad
The first English-language biography of Muhammad (571-632 A.D.), depicting the great prophet and founder of Islam, his life and achievements, and his enormous influence on the modern world.
Learning from Imbalanced Data Sets
This book provides a general and comprehensible overview of imbalanced learning. It contains a formal description of a problem, and focuses on its main features, and the most relevant proposed solutions. Additionally, it considers the different scenarios in Data Science for which the imbalanced classification can create a real challenge. This book stresses the gap with standard classification tasks by reviewing the case studies and ad-hoc performance metrics that are applied in this area. It also covers the different approaches that have been traditionally applied to address the binary skewed class distribution. Specifically, it reviews cost-sensitive learning, data-level preprocessing metho...
Machine Learning in Action
Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. About the Book A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill neede...
Elements of Mathematical Ecology
Elements of Mathematical Ecology provides an introduction to classical and modern mathematical models, methods, and issues in population ecology. The first part of the book is devoted to simple, unstructured population models that ignore much of the variability found in natural populations for the sake of tractability. Topics covered include density dependence, bifurcations, demographic stochasticity, time delays, population interactions (predation, competition, and mutualism), and the application of optimal control theory to the management of renewable resources. The second part of this book is devoted to structured population models, covering spatially-structured population models (with a focus on reaction-diffusion models), age-structured models, and two-sex models. Suitable for upper level students and beginning researchers in ecology, mathematical biology and applied mathematics, the volume includes numerous clear line diagrams that clarify the mathematics, relevant problems thoughout the text that aid understanding, and supplementary mathematical and historical material that enrich the main text.
Extinction and Quasi-Stationarity in the Stochastic Logistic SIS Model
This volume presents explicit approximations of the quasi-stationary distribution and of the expected time to extinction from the state one and from quasi-stationarity for the stochastic logistic SIS model. The approximations are derived separately in three different parameter regions, and then combined into a uniform approximation across all three regions. Subsequently, the results are used to derive thresholds as functions of the population size N.
Introduction to Mathematical Modeling and Chaotic Dynamics
Introduction to Mathematical Modeling and Chaotic Dynamics focuses on mathematical models in natural systems, particularly ecological systems. Most of the models presented are solved using MATLAB®. The book first covers the necessary mathematical preliminaries, including testing of stability. It then describes the modeling of systems from natural science, focusing on one- and two-dimensional continuous and discrete time models. Moving on to chaotic dynamics, the authors discuss ways to study chaos, types of chaos, and methods for detecting chaos. They also explore chaotic dynamics in single and multiple species systems. The text concludes with a brief discussion on models of mechanical systems and electronic circuits. Suitable for advanced undergraduate and graduate students, this book provides a practical understanding of how the models are used in current natural science and engineering applications. Along with a variety of exercises and solved examples, the text presents all the fundamental concepts and mathematical skills needed to build models and perform analyses.
