Intrusion Detection with Classification and On-Line Clustering Using Reinforcement Learning

Today, information technology is growing rapidly,all information can be obtained much easier. It raises some new problems, one of them is unauthorized access to the system. We need a reliable network security system that is resistant to a variety of attacks against the system. Therefore, Intrusion Detection System (IDS) required to overcome the problems of intrusions. Many researches have been done on intrusion detection using classification methods. Classification methodshave high precision, but it takes efforts to determine an appropriate classification model to the classification problem. In this paper, we propose a new reinforced approach to detect intrusion with On-line Clustering using Reinforcement Learning. Reinforcement Learning is a new paradigm in machine learning which involves interaction with the environment.It works with reward and punishment mechanism to achieve solution. We apply the Reinforcement Learning to the intrusion detection problem with considering competitive learning using Pursuit Reinforcement Competitive Learning (PRCL). Based on the experimental result, PRCL can detect intrusions in real time with high accuracy (99.816% for DoS, 95.015% for Probe, 94.731% for R2L and 99.373% for U2R) and high speed (44 ms). The proposed approach can help network administrators to detect intrusion, so the computer network security systembecome reliable

Batik Image Search System with Extracted Combination of Color and Shape Features

Batik is a culture-dependent technique and symbolism surrounding hand-dyed cotton and silk garments from Indonesia It an cultural art that has a long history of acculturation, with diverse patterns influenced by a variety of cultures. Each region in Indonesian has specific colors and shapes reflecting the identity of the region. Due to many diverse Batik' patterns and colors, it is difficult to retrive the Batik images from both the color and pattern. In this paper we propose a new system for Batik image search with providing an analytical function for feature extraction by involving color and shape features and combining the extracted features. We use 3D-Vector Quantization for color feature extraction. It can uniformly represent the distribution of image colors and reduce complexity of the colors. Beside the color features, we also use shape features of the Batik by applying Hu's moment. The extracted shape features from the Hu's moment consists of orthogonal moment invariants those can be used for scale, position, and rotation invariant pattern identification for the Batik patterns. Finally, the distribution of color moments are used to aggregate the extracted color and shape features. For experimental study, we apply our proposed system to 210 Batik image dataset from 3 common Batik kinds of pattern: Kawung, Parang and Mega Mendung. The system performs the easy-to-use application for the users in which they may easily search the Batik images with involving both the color and shape features

Centronit: Initial Centroid Designation Algorithm for K-Means Clustering

Clustering performance of the K-means highly depends on the correctness of initial centroids. Usually initial centroids for the K- means clustering are determined randomly so that the determined initial centers may cause to reach the nearest local minima, not the global optimum. In this paper, we propose an algorithm, called as Centronit, for designation of initial centroid optimization of K-means clustering. The proposed algorithm is based on the calculation of the average distance of the nearest data inside region of the minimum distance. The initial centroids can be designated by the lowest average distance of each data. The minimum distance is set by calculating the average distance between the data. This method is also robust from outliers of data. The experimental results show effectiveness of the proposed method to improve the clustering results with the K-means clustering

Impression Generation of Indonesian Cultural Paintings for Mobile Application with Culture Dependent Color-Impression Metric Creation Contents

Painting is one of complex image reflecting observations and feelings of the artist to the environment. This condition extends the need of painting impression generation system since common people with lack of art experience would have difficulties to interpret the painting. From this point of view we presents a new model to provide representative impressions of paintings by providing a color-impression metric taken from public survey and implement it for mobile application. The new model provides analytical functions to generate the representative impression of the image query. The functions consist of two main section: (1) The cultural-dependent color-impression metric creation which consist of conducting survey, applying normalized 3D color vector quantization to image dataset, generating image-impression metric, and generating color- impression metric; and (2) Impression generation of image query which consist of applying normalized 3D color vector quantization to image query and measuring the similarity between image query and color-impression metric. To perform our proposed impression generation system, we examine our system with Indonesian cultural image dataset and 5 different mobile devices. Our proposed system performs main color impression precision result with average precision of more than 60%. Brightness intensity and zooming affects the retrieved impressions. Rotating captures of an image generate the same retrieved impressions. The system also performs average response time vary in range 41263 to 117434 milliseconds from all devices

Environmental Change Detection and Visualization by Differential Computing for Satellite Images with 5D World Map System

This paper presents a differential computing system for satellite images called SIDE, which automatically extracts areas, boundaries and lines on earth from any type of general images using image processing technology. Unlike other general GIS software, SIDE can process any type of images without geo information (lat, long) as input and convert to geo information with template. The feature of SIDE is that it enables users to extract the differences between images using color information of areas on earth such as forest, ice, ocean, river, soil and desert, and compare the differences in time-series analysis. Also, SIDE provides a function to modify the position, size and angle of detected area, border and lines, and adjust the positions to geo information to overlap output images onto the base-map such as Google Maps or ArcGIS maps. By using this system with a multimedia sharing system called 5D World Map System, users can analyze the impacts of environmental change to the other phenomena by global viewpoints with other related multimedia

Earthquake Density Measurement using Automatic Clustering

The government and earthquake associations have recorded the seismic data in spatial-temporal usually used to measure the earthquake intensity, but such information has not been processed to obtain the earthquake density. This condition makes it difficult to map all the risk, so it creates the lack of participatory development to the earthquake areas that have a high density. This research proposes a new approach for measuring the density of earthquake and performing automatic clustering with valley tracing method to detect the number of group spatial regions automatically from analysis of cluster moving variances. The density is obtained with a new approach that involves the area and the amount of data on clusters. This system follows the steps: (1) display the spatial-temporal earthquake dataset into a map, (2) create vector space data consist of temporal, spatial, and magnitude, (3) detect number of cluster with valley tracing method on automatic clustering, (4) calculate the earthquake density, and (5) display special temporal visualization with the cluster density measurement result. To perform the proposed idea, this system is examined with an experimental study for a series of quake about Indonesia and Japan during the last 50 years from ANSS catalog

Intrusion Detection with On-line Clustering Using Reinforcement Learning

Today, information technology is growing rapidly, we can obtain all the information much easier. Almost all the important information can be accessed by the users. These conditions raise some new problems, one of them is unauthorized access to the system. We need a reliable network security system that is resistant to a variety of attacks against the system. Therefore, Intrusion Detection System (IDS) required to overcome the problems of intrusions. Many researches have been done on intrusion detection using classification methods. Classification method has high precision, but to get a high precision required a determination of the proper classification model. In this paper, we propose a new approach to detect intrusion with On-line Clustering using Reinforcement Learning. Based on the experimental result, our proposed technique can detect intrusions with high accuracy (99.996% for DoS, 99.939% for Probe, 99.865% for R2L and 99.948% for U2R) and high speed (65 ms)

SINKRONISASI KECEPATAN PUTARAN ELEKTRONIK SOFT SWITCH GEAR BERBASIS PID KONTROL PADA MOBIL HIBRIDA

Pada sistem penggerak mobil hibrida dalam penelitian digunakan penggerak motor elektrik dengan motor induksi tiga fasa dan penggerak mesin pembakaran dalam berbahan bakar minyak (BBM) sebagai penggerak cadangan. Untuk perpindahan kedua penggerak tersebut diperlukan sistem perpindahan transmisi penggerak yang lembut pada saat transisi perpindahan transmisi kedua penggerak tersebut. Untuk itu diperlukan teknik kendali pada elektronik switch gear pada transmisi penggerak mobil. Teknik kendali yang digunakan dengan kontrol PID untuk mensinkronkan kedua kecepatan putaran penggerak, sehingga pada saat perpindahan kedua transmisi dihasilkan switch gear yang soft. Langkah yang dilakukan adalah dengan pengaturan kecepatan putaran mesin BBM dan putaran kecepatan motor elektrik. Mesin BBM sebagai Master dan motor elektrik sebagai Slave karena pengaturan motor elektrik lebih mudah dari pada pengaturan mesin BBM, sehingga yang menyesuaikan kecepatan transmisi adalah motor elektrik. Pada saat akan dilakukan perpindahan transmisi kecepatan motor akan menyesuakan kecepatan mesin BBM dan apabila sudah dicapai sinkronisasi dengan teknik kendali PID maka dilanjutkan dengan perpindahan transmisi. Penggerak utama mobil hibrida ini adalah motor elektrik, apabila terjadi kelemahan daya pada baterai, dilakukan pemindahan transmisi ke penggerak BBM dan secara bersamaan dilakukan pengisian baterai sampai penuh. Apabila pengisian baterai sudah penuh maka dilakukan perpindahan transmisi ke penggerak motor elektrik. Hasil simulasi menunjukkan bahwa kendali PID sesuai untuk diterapkan pada mobil hibrida ini karena mempunyai respon yang baik dan bekerja secara autotuning pada perubahan kecepatan mobil. Kata Kunci: motor induksi tiga fasa, kontrol PID, elektronik switch gear, autotuning

Portabel Text to Speech yang Terintegrasi dengan Telepon Seluler untuk Tunawicara

Penelitian terhadap implementasi metode text to speech telah banyak dilakukan. Namun demikian, penelitian yang ada mempunyai kekurangan pada kemampuan pengenalan suku kata serta kapasitas database suara yang digunakan. Oleh karena itu, penelitian ini bermaksud mengatasi kelemahan penelitian sebelumnya dalam melakukan pengenalan suku kata. Informasi suku kata suara disimpan dalam Database suara yang berjumlah 4700 buah dengan masing- masing pola V, VK, VKK, K, KV, KVK, KVKK, KVKKK, KKV, KKVK, KKVKK, KKVKKK, KKKV, KKKVK (V adalah vokal dan K adalah konsonan). Teks yang ada dinormalisasi menjadi teks baru yang berupa deretan karakter huruf kapital dan kemudian dikonversi menjadi deretan suku kata menggunakan metode Finite State Automata (FSA). Deretan suku kata tersebut kemudian diproses menggunakan syllable concatenation dengan cara mencocokkan setiap database suara suku kata yang sesuai kemudian digabungkan satu sama lain sehingga diperoleh hasil akhir berupa suara sintesis. Berdasarkan hasil pengujian, sistem telah mampu memenuhi kontribusi yang diharapkan yaitu mampu mengenali suku kata dan mengkonversinya menjadi suara dengan tingkat keberhasilan 90% dari 10 macam teks yang diujikan. Hasil pengujian sistem dalam pengonversian suku kata menjadi suara juga diperoleh tingkat keberhasilan maksimal 75% dari 20 responden

Pemodelan Temperatur Ruang Menggunakan Regresi Non Linier Berdasarkan Hasil Estimasi FEM 3-D Linier

Dalam makalah ini dilakukan pemodelan temperatur ruang menggunakan pendekatan regresi non linier dalam dimensi spasial dan waktu. Sebagai ruang percobaannya yaitu prototipe mesin pengering gabah elektronik. Dari phisycal model, diletakkan 8 sensor temperatur untuk mengukur dinamika temperatur dan satu sensor di tengah sebagai node pengujian (test node). Sedangkan mathematical model yang digunakan adalah Finite Element Method (FEM) dengan fungsi basis linier tiga dimensi (3-D). Matriks stiffness lokal berukuran (8x8) diperoleh dari persamaan panas berdasarkan fungsi basis yang ditentukan. Matriks stiffness global disusun berdasarkan matriks stiffness lokal, yang selanjutnya digunakan untuk mengestimasi temperatur node-node disekitarnya berdasarkan 8 node temperatur yang telah diketahui. Selanjutnya hasil estimasi temperature tersebut dibandingkan dengan hasil estimasi menggunakan regresi non linier. Node pengujian merupakan node yang digunakan untuk menguji kinerja dari pemodelan yang dibua