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Journal of Applied Intelligent System
ISSN : 25020493     EISSN : 25029401     DOI : -
Core Subject :
Journal of Applied Intelligent System (JAIS) is published by LPPM Universitas Dian Nuswantoro Semarang in collaboration with CORIS and IndoCEISS, that focuses on research in Intelligent System. Topics of interest include, but are not limited to: Biometric, image processing, computer vision, knowledge discovery in database, information retrieval, computational intelligence, fuzzy logic, signal processing, speech recognition, speech synthesis, natural language processing, data mining, adaptive game AI.
Arjuna Subject : -
Articles 4 Documents
Search results for , issue " Vol 4, No 1 (2019): Journal of Applied Intelligent System (in press)" : 4 Documents clear
Improvement accuracy of recognition isolated Balinese characters with Deep Convolution Neural Network Teja Murti, Ida Bagus Teguh
Journal of Applied Intelligent System Vol 4, No 1 (2019): Journal of Applied Intelligent System (in press)
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v4i1.2289

Abstract

The numbers of Balinese script and the low quality of palm leaf manuscripts provide a challenge for testing and evaluation for character recognition. The aim of high accuracy for character recognition of Balinese script,we implementation Deep Convolution Neural Network using SmallerVGG (Visual Geometry Group) Architectur for character recognition on palm leaf manuscripts. We evaluated the performance that methods and we get accuracy 87,23% .
Upload File Security on the Server Using LSB and Hill Cipher Handoko, Lekso Budi; Umam, Chaerul; Anindita, Adelia Syifa
Journal of Applied Intelligent System Vol 4, No 1 (2019): Journal of Applied Intelligent System (in press)
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v4i1.2331

Abstract

The rapid development of technology not only has a positive impact, but also can have a negative impact such as the development of cyber crime that can cause messages to be unsafe. Message security can be protected using cryptography to convert messages into secret passwords. Steganography is a technique of hiding messages by inserting messages into images that are used to increase message security. In this study, it discusses a combination of hill cipher and LSB algorithms to secure messages. The message used is a 3-bit grayscale image for steganography and text messages with 32, 64 and 128 characters for cryptography. The measuring instruments used in this study are MSE, PSNR, Entropy and travel time (CPU time). Test results prove an increase in security without too damaging the image. This is evidenced by the results of the MSE trial which has a value far below the value 1, the PSNR is> 65 dB with a range of entropy values of 5 to 7, and travel times are almost the same.
A Study on Named Entity Recognition with OpenNLP at English Texts Bilgin, Metin
Journal of Applied Intelligent System Vol 4, No 1 (2019): Journal of Applied Intelligent System (in press)
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v4i1.2096

Abstract

Named entity recognition is a subject, inside of information retrieval which is a subdomain of natural processing. It pertains to identifying and labeling of location, person, organization, etc., inside of text content. Named entity recognition provides identifying and classifying of person, area, etc. inside of formal and informal text content and it can be used for different purposes as question answering systems and removal of the relation between events. In this work, named entity recognition is performed and one method is suggested and results are discussed for assignment to unlabeled name entities by using OpenNLP library with the help of KNIME program in the data set.
Implementation of Fuzzy Logic Controller for Wall Following and Obstacle Avoiding Robot Soetedjo, Aryuanto; Ashari, M. Ibrahim; Septian, Cosnas Eric
Journal of Applied Intelligent System Vol 4, No 1 (2019): Journal of Applied Intelligent System (in press)
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v4i1.2168

Abstract

This paper presents the development of wall following and obstacle avoiding robot using a Fuzzy Logic Controller. The ultrasonic sensors are employed to measure the distances between robot and the wall, and between the robot and the obstacle. A low cost Raspberry Pi camera is employed to measure the left/right distance between the robot and the obstacle. The Fuzzy Logic Controller is employed to steer the mobile robot to follow the wall and avoid the obstacle according to the multi sensor inputs. The outputs of Fuzzy Logic Controller are the speeds of left motor and right motor. The experimental results show that the developed mobile robot could be controlled properly to follow the different wall positions and avoid the different obstacle positions with the high successful rate of 83.33%.

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