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JAIS (Journal of Applied Intelligent System)
Published by Universitas Dian Nuswantoro
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 5 Documents
 1 
Search results for , issue "Vol 3, No 2 (2018): Journal of Applied Intelligent System" : 5 Documents clear
Translation System from Arabic Text to Arabic Sign Language Nadia Aouiti; Mohamed Jemni
Journal of Applied Intelligent System Vol 3, No 2 (2018): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v3i2.2041

Abstract

This research paper presents our ongoing project aiming at translating in real time an Arabic text to Arabic Sign Language (ArSL). This project is a part of a Web application [1] based on the technology of the avatar (animation in the virtual world). The input of the system is a text in natural language. The output is a real-time and online interpretation in sign language [2]. Our work focuses on the Arabic language as the text in the input, which needs many treatments due to the particularity of this language. Our solution starts from the linguistic treatment of the Arabic sentence, passing through the definition and the generation of Arabic Annotation Gloss system and coming finally to the generation of an animated sentence using the avatar technology.
Intelligence Performance in Students’ Absence System with Predicted Information by Data mining Algorithms Ali Fattah Dakhil; Waffa Muhammad Ali; Asseel Jabbar Almahdi
Journal of Applied Intelligent System Vol 3, No 2 (2018): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v3i2.2057

Abstract

There are many databases projects used by numerous number of organizations. However, embedding business intelligence, BI, technique is a qualitative impact and quite important factor to improve such project’s results and performance. Modern data mining algorithms have dramatically changed our business work, data model and the way we develop software projects. A database application that manages students’ attendance used in university classes is the objective scope that we adopt and work on in this paper. The main key of interest in this research is to improve such attendance system by participating one of data mining classification technique in which we then have a useful learned information and predicted reports about future students’ attendance. Beside this intelligent trait, our work would be crowned with pictorial analytic results that encourage us to have modern and well-mannered intelligent database application.  
Optimization of Region of Interest (ROI) Image of Malaria Parasites Rika Rosnelly; Linda Wahyuni; Jani Kusanti
Journal of Applied Intelligent System Vol 3, No 2 (2018): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v3i2.2060

Abstract

The stage of region of interest (ROI) is the determining part to the next stage in image processing. ROI is a process of taking certain parts or regions in an image. ROI can be done by manual and automatic cropping. Some previous studies still use cropping manually for detection of malaria parasites. This study uses cropping automatically for detection of malaria parasites. The types of malaria parasites used were falciparum, vivax and malariae with ring stages, tropozoite, schizon and gametocytes. Data from malaria parasites were obtained at the North Sumatra Provincial Health Laboratory. The results show that the ROI image can crop the malaria parasite region. Keyword - malaria parasite, ROI.
Pattern Recognition Of Javanese Letter Using Template Matching Correlation Method Irham Ferdiansyah Katili; Fairuz Dyah Esabella; Ardytha Luthfiarta
Journal of Applied Intelligent System Vol 3, No 2 (2018): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v3i2.1954

Abstract

In this modern age, the impact of globalization is increasingly entering and expanding into most societies. One impact of globalization makes people prefer to learn the language and use a foreign language rather than the local language, especially the Java language. It is very influential on the knowledge of the community about the existence or the existence of Javanese Letter, especially in the field of education. In this study, In this research will be made an application to recognize the writing of Javanese Letter based on Optical Character Recognition (OCR). Matching templates correlation can be used as pattern recognition methods. How the Template Matching Algorithm works by matching the template image with the test image after going through the Pre-processing and segmentation process. From the research that has been done by using 10 character template and 20 data testing get accuracy equal to 93.44% and error rate 6.56%. So the Matching Template Algorithm can well recognize the Javanese Letter pattern.
A Classification of Batik Lasem using Texture Feature Ecxtraction Based on K-Nearest Neighbor Cahaya Jatmoko; Daurat Sinaga
Journal of Applied Intelligent System Vol 3, No 2 (2018): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v3i2.2151

Abstract

In this study, batik has been modeled using the GLCM method which will produce features of energy, contrast, correlation, homogenity and entropy. Then these features are used as input for the classification process of training data and data testing using the K-NN method by using ecludean distance search. The next classification uses 5 features that provide information on energy values, contrast, correlation, homogeneity, and entropy. Of the two classifications, which comparison will produce the best accuracy. Training data and data testing were tested using the Recognition Rate calculation for system evaluation. The results of the study produced 66% recognition rate in 50 pieces of test data and 100 pieces of training data.

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