<p class="SammaryHeader" align="center"><strong>ABSTRACT</strong></p><p><em>The brain is formed from two types of cells: glia and neurons. Glia functions to support and protect neurons, while neurons carry information in the form of electrical pulses known as potential action. The brain regulates and coordinates most of the body's movements, behavior, and homeostasis functions such as heart rate, blood pressure, body fluid balance and body temperature. A brain tumor is a mass of abnormally growing brain cells. Most brain tumors can spread through brain tissue, but rarely spread to other areas of the body. But in the case of benign brain tumors, as they grow they can destroy and suppress other normal brain tissue, which can result in paralysis. Several methods are used to detect disorders of the brain nerve tissue, including: Magnetic Resonance Imaging (MRI). This research is intended to build a classification system for brain image data using Magnetic Resonance Imaging (MRI) with the category, normal, Glioma, metastatic bronchogenic carcinoma or Alzheimer's using Magnetic Resonance Imaging (MRI) so that it can assist in decision making for medical experts. While the method used in this research is Discrete Wavelet Transformation (DWT) for the feature extraction process so that the unique characteristics of an object can be recognized, as well as the classification process using the adaptive neighborhood neural network method. This research is able to integrate the two methods with the acquisition of significant accuracy.</em></p><p><strong><em>Keywords</em></strong><strong><em> </em></strong><strong><em>: </em></strong><em>feature extraction, classification, MRI, Brain</em></p><p class="SammaryHeader" align="center"><strong>ABSTRAK</strong></p><p><em>Otak terbentuk dari dua jenis sel: glia dan neuron. Glia berfungsi untuk menunjang dan melindungi neuron, sedangkan neuron membawa informasi dalam bentuk pulsa listrik yang di kenal sebagai</em><em> potensi aksi</em><em>.</em><em> </em><em>Otak mengatur dan mengkordinir sebagian besar,</em><em>gerakan</em><em>, </em><em>perilaku</em><em> dan fungsi tubuh homeostasis seperti detak jantung, tekanan darah, keseimbangan cairan tubuh dan suhu tubuh</em><em>.</em><em> Tumor otak adalah sekumpulan massa sel-sel otak yang tumbuh abnormal. Sebagian besar tumor otak dapat menyebar melalui jaringan otak, tetapi jarang sekali menyebar ke area lain dari tubuh. Namun pada kasus tumor otak yang jinak, saat mereka tumbuh dapat menghancurkan dan menekan jaringan otak normal lainnya, yang dapat berakibat pada kelumpuhan. Beberapa metode dipergunakan untuk mendeteksi gangguan pada jaringan syaraf otak, diantaranya: </em><em>Magnetic</em><em> </em><em>Resonance Imaging</em><em> (MRI)</em><em>.</em><em> </em><em>Penelitian </em><em>ini dimaksudkan untuk m</em><em>embangun sistem klasifikasi </em><em>untuk data citra otak menggunakan Magnetic Resonance Imaging (MRI) dengan kategori, normal, Glioma, metastatic bronchogenic carcinoma atau Alzheimer menggunakan Magnetic Resonance Imaging (MRI) sehingga dapat membantu  dalam pengambilan keputusan bagi tenaga ahli dibidang kedokteran. Sedangkan metode yang digunakan dalam penelitian adalah Discrete Wavelet Transformation (DWT) untuk proses ekstrasi fitur (feature extraction) </em><em>agar</em><em> karakteristik unik dari suatu objek</em><em> dapat dikenali</em><em>, serta proses k</em><em>lasifikasi</em><em> meng</em><em>gunakan metode adaptive neighborhood neural network. Penelitian ini mampu mengintegrasikan kedua metoda dengan perolehan hasil akurasi yang signifikan.</em></p><strong><em>Kata kunci : </em></strong><em>ekstrasi fitur, klasifikasi, MRI, Otak</em>

<p class="Abstrak">Masalah keamanan jaringan semakin menjadi perhatian saat ini. Sudah semakin banyak <em>tools</em> maupun teknik yang dapat digunakan untuk masuk kedalam sistem secara ilegal, sehingga membuat lumpuh sistem yang ada. Hal tersebut dapat terjadi karena adanya celah dan tidak adanya sistem keamanan yang melindunginya, sehingga sistem menjadi rentan terhadap serangan. Pengenalan pola serangan di jaringan merupakan salah satu upaya agar serangan tersebut dapat dikenali, sehingga mempermudah administrator jaringan dalam menanganinya apabila terjadi serangan. Salah satu teknik yang dapat digunakan dalam keamanan jaringan<em> </em>karena dapat mendeteksi serangan secara <em>real time</em> adalah <em>Intrusion Detection System</em> (IDS), yang dapat membantu administrator dalam mendeteksi serangan yang datang. Penelitian ini menggunakan metode <em>signatured based </em>dan mengujinya dengan menggunakan simulasi. Paket data yang masuk akan dinilai apakah berbahaya atau tidak, selanjutnya digunakan beberapa <em>rule</em> untuk mencari nilai akurasi terbaik. Beberapa <em>rule</em> yang digunakan berdasarkan hasil <em>training </em>dan uji menghasilakan 60% hasil <em>training </em>dan 50% untuk hasil uji <em>rule</em> 1, 50% hasil <em>training </em>dan 75% hasil uji <em>rule</em> 2, 75% hasil <em>training</em> dan hasil uji rule 3, 25% hasil <em>training </em>dan hasil uji <em>rule </em>4, 50% hasil <em>training</em> dan hasil uji untuk <em>rule</em> 5. Hasil pengujian dengan metode <em>signatured based</em> ini mampu mengenali pola data serangan melaui protokol TCP dan UDP, dan <em>monitoring </em>yang dibuat mampu mendeteksi semua serangan dengan tampilan <em>web base.</em></p><p class="Abstrak"><em><br /></em></p><p class="Abstrak"><strong><em>Abstract</em></strong></p><p class="Abstract"><em>Network security issues are becoming increasingly a concern these days. There are more and more tools and techniques that can be used to enter the system illegally, thus paralyzing the existing system. This can occur due to loopholes and the absence of a security system that protects it so that the system becomes vulnerable to attacks. The recognition of attack patterns on the network is an effort to make these attacks recognizable, making it easier for network administrators to handle them in the event of an attack. One of the techniques that can be used in network security because of a timely attack is the Intrusion Detection System (IDS), which can help administrators in surveillance that comes. This study used a signature-based method and tested it using a simulation. The incoming data packet will be assessed whether it is dangerous or not, then several rules are used to find the best accuracy value. Some rules used are based on the results of training and testing results in 60% training results and 50% for rule 1 test results, 50% training results and 75% rule 2 test results, 75% training results and rule 3 test results, 25% training results and the result of rule 4 test, 50% of training results and test results for rule 5. The test results with the signature-based method can recognize attack data patterns via TCP and UDP protocols, and monitoring is made to be able to detect all attacks with a web-based display.</em></p><p class="Abstrak"><strong><em><br /></em></strong></p>

Searching for a lot of materials are materials which is needed quickly and accurately. are by ranking them. Ranking is one branch of science of information retrieval. Information document search Vector Space Model (VSM). VSM uses the concept which is included in linear algebra is a vector space. Based on the concept that is used, the development of blended learning application uses space vector modeling method as an alternative for students in searching of relavan material toward materials needed, reducing the error level in the return of information and students can achieve goals quickly. Column vector representation is used in the conversion of document input, processing and output. Another concept that is used to determine the proximity between two vectors, are by calculating the angle formed between the two vectors and then it is sequenced from the data which has a large angle of the smallest to the largest of which indicates the sequence data of the ranking from the most relevant to irrelevant. In this study is described about the will produce quality to each document to determine how relevant the document to the query. Quality method which is used in the implementation can be a combination of TF (Term Frequency), IDF (Inverse Document Frequency), and the corresponding normalized input from the user. Index Terms— Content Search, Blended learning, the Vector Space Model.

Breast cancer is a type of malignant tumor which is still the number one killer where the process of spread or metastasis takes a long time. The number of breast cancer sufferers increases every year so that if detected or caught early, prevention can be done early so as to reduce the number of breast cancer sufferers. To reduce the risk of increasing the number of cancer patients, it is necessary to do early detection, several methods can be used to assist the early detection process such as cancer screening, or computational methods. Several machine learning methods that have been chosen to solve cases of breast cancer prediction, especially the classification algorithm, including Naive Bayes have the advantage of being simple but having high accuracy even though they use little data. Weaknesses in Naive Bayes, namely the prediction of the probability result is not running optimally and the lack of selection of relevant features to the classification so that the accuracy is low. This research is intended to build a classification system for detecting breast cancer using the Naive Bayes method, by adding a forward selection method for feature selection from the many features that exist in breast cancer data, because not all features are features that can be used in the classification process. The result of combining the Naive Bayes method and the forward selection method in feature selection can increase the accuracy value of 96.49% detection of breast cancer patients.Â

The brain is formed from two types of cells: glia and neurons. Glia functions to support and protect neurons, while neurons carry information in the form of electrical pulses known as potential action. The brain regulates and coordinates most of the body's movements, behavior, and homeostasis functions such as heart rate, blood pressure, body fluid balance and body temperature. A brain tumor is a mass of abnormally growing brain cells. Most brain tumors can spread through brain tissue, but rarely spread to other areas of the body. But in the case of benign brain tumors, as they grow they can destroy and suppress other normal brain tissue, which can result in paralysis. Several methods are used to detect disorders of the brain nerve tissue, including: Magnetic Resonance Imaging (MRI). This research is intended to build a classification system for brain image data using Magnetic Resonance Imaging (MRI) with the category, normal, Glioma, metastatic bronchogenic carcinoma or Alzheimer's using Magnetic Resonance Imaging (MRI) so that it can assist in decision making for medical experts. While the method used in this research is Discrete Wavelet Transformation (DWT) for the feature extraction process so that the unique characteristics of an object can be recognized, as well as the classification process using the adaptive neighborhood neural network method. This research is able to integrate the two methods with the acquisition of significant accuracy.Keywords : feature extraction, classification, MRI, BrainABSTRAKOtak terbentuk dari dua jenis sel: glia dan neuron. Glia berfungsi untuk menunjang dan melindungi neuron, sedangkan neuron membawa informasi dalam bentuk pulsa listrik yang di kenal sebagai potensi aksi. Otak mengatur dan mengkordinir sebagian besar,gerakan, perilaku dan fungsi tubuh homeostasis seperti detak jantung, tekanan darah, keseimbangan cairan tubuh dan suhu tubuh. Tumor otak adalah sekumpulan massa sel-sel otak yang tumbuh abnormal. Sebagian besar tumor otak dapat menyebar melalui jaringan otak, tetapi jarang sekali menyebar ke area lain dari tubuh. Namun pada kasus tumor otak yang jinak, saat mereka tumbuh dapat menghancurkan dan menekan jaringan otak normal lainnya, yang dapat berakibat pada kelumpuhan. Beberapa metode dipergunakan untuk mendeteksi gangguan pada jaringan syaraf otak, diantaranya: Magnetic Resonance Imaging (MRI). Penelitian ini dimaksudkan untuk membangun sistem klasifikasi untuk data citra otak menggunakan Magnetic Resonance Imaging (MRI) dengan kategori, normal, Glioma, metastatic bronchogenic carcinoma atau Alzheimer menggunakan Magnetic Resonance Imaging (MRI) sehingga dapat membantu  dalam pengambilan keputusan bagi tenaga ahli dibidang kedokteran. Sedangkan metode yang digunakan dalam penelitian adalah Discrete Wavelet Transformation (DWT) untuk proses ekstrasi fitur (feature extraction) agar karakteristik unik dari suatu objek dapat dikenali, serta proses klasifikasi menggunakan metode adaptive neighborhood neural network. Penelitian ini mampu mengintegrasikan kedua metoda dengan perolehan hasil akurasi yang signifikan.Kata kunci : ekstrasi fitur, klasifikasi, MRI, Otak