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"The notion of abgeles is known in a vector space equipped with an inner product,but not well estabilished in a vector space equipped only with a norm....."

"This book constitutes the refereed proceedings of the 4th International Workshop on the Arithmetic of Finite Field, WAIFI 2012, held in Bochum, Germany, in July 2012. The 13 revised full papers and 4 invited talks presented were carefully reviewed and selected from 29 submissions. The papers are organized in topical sections on coding theory and code-based cryptography, Boolean functions, finite field arithmetic, equations and functions, and polynomial factorization and permutation polynomial."

"This book serves as an introduction to calculus on normed vector spaces. It includes many non-trivial applications of the theory and interesting exercises."

"Stroke merupakan penyakit yang menempati urutan ketiga sebagai penyebab kematian terbesar di dunia setelah penyakit jantung dan kanker. Stroke juga menduduki posisi pertama sebagai penyakit yang dapat menyebabkan kecacatan, baik ringan maupun berat. Salah satu jenis stroke yang umum terjadi adalah infark serebri. Di Indonesia, jumlah penderita stroke, terutama infark serebri, semakin meningkat setiap tahunnya. Tidak hanya terjadi pada seseorang yang berusia lanjut, namun infark serebri juga dapat terjadi pada seseorang yang masih muda dan produktif. Oleh sebab itu, pendeteksian dini terhadap infark serebri sangatlah penting. Berbagai metode medis selalu digunakan untuk mengklasifikasi infark serebri, namun dalam penelitian ini, akan digunakan metode machine learning. Metode yang diusulkan yaitu Multiple Support Vector Machine dengan Seleksi Fitur Information Gain (MSVM-IG). MSVM-IG merupakan metode baru yang menggunakan support vector sebagai data baru untuk selanjutnya dilakukan seleksi fitur dan evaluasi performa. Data yang digunakan berupa data numerik hasil CT Scan yang diperoleh dari RSUPN dr. Cipto Mangunkusumo, Jakarta. Berdasarkan hasil uji coba, metode yang diusulkan mampu mencapai nilai akurasi sebesar 88,71%. Sehingga, metode MSVM-IG ini dapat menjadi salah satu alternatif untuk membantu praktisi medis dalam mengklasifikasi infark serebri.

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Stroke is a disease that ranks third as the biggest cause of death in the world after heart disease and cancer. Stroke also occupies the first position as a disease that can cause disability, both mild and severe. One type of stroke that is common is cerebral infarction. In Indonesia, the number of stroke patients, especially cerebral infarction, is increasing every year. Not only occurs in someone who is elderly, but cerebral infarction can also occur in someone who is young and productive. Therefore, early detection of cerebral infarction is very important. Various medical methods are always used to classify cerebral infarction, but in this study, machine learning methods would be used. The proposed method is Multiple Support Vector Machine with Information Gain Feature Selection (MSVM-IG). MSVM-IG is a new method that uses support vector as a new dataset, then feature selection step and performance evaluation are performed. The data used in the form of numerical data results of CT scan obtained from RSUPN Dr. Cipto Mangunkusumo, Jakarta. Based on the results, the proposed method is able to achieve an accuracy value of 88.71%. Thus, the MSVM-IG could be an alternative to assist medical practitioners in classifying cerebral infarction."