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Heri Nurdiyanto
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Heri Nurdiyanto
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internationaljournalair@gmail.com
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Kota metro,
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INDONESIA
International Journal of Artificial Intelligence Research
Published by STMIK Dharma Wacana
ISSN : -     EISSN : 25797298     DOI : -
International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) majors areas of research that includes 1) Machine Learning and Soft Computing, 2) Data Mining & Big Data Analytics, 3) Computer Vision and Pattern Recognition, and 4) Automated reasoning. Submitted papers must be written in English for initial review stage by editors and further review process by minimum two international reviewers.
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Articles 5 Documents
Search results for , issue "Vol 2, No 1 (2018): June 2018" : 5 Documents clear
An Embedded Fuzzy Logic Based Application for Density Traffic Control System Adewale, Ajao Lukman; Jumoke, Ajao Falilat; Adegboye, Mutiu; Ismail, Abideen
International Journal of Artificial Intelligence Research Vol 2, No 1 (2018): June 2018
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1090.228 KB) | DOI: 10.29099/ijair.v2i1.44

Abstract

The control of density traffic at cross junction road usually manned by human efforts or implementation of automatic traffic light system. This system seem and proves to be inefficient with some challenges. The major constraints of this traffic control are as a result of the inability of most traffic control systems to assign appropriate waiting time for vehicles based on the lane density. Also with little or no consideration for pedestrians, emergency and security agents priorities. In view of this, an intelligent density traffic control system using  (fuzzy logic) which is capable of providing priority to the road users based on the density and emergency situations was developed and presented in this paper. This system will obtain the approximate amount of vehicle and presence of pedestrians respectfully on each lane with help of Infrared Sensors (IR) and siren detection system for emergency and security road users. The working principle of this system depending on the logic inputs rules given into the processing unit by the (sensors, S1 and S2) which helps the system to generates a timing sequence that best suit the number of vehicles and pedestrians available on the lane at point in time.
The Comparison of Signature Verification Result Using 2DPCA Method and SSE Method Anita Sindar R M Sinaga
International Journal of Artificial Intelligence Research Vol 2, No 1 (2018): June 2018
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (651.523 KB) | DOI: 10.29099/ijair.v2i1.38

Abstract

The rate of speed and validation verify to be a reference of quality information and reliable results. Everyone has signature characteristics but it will be difficult to match original signatures with a clone. Two Dimensional Principal Component Analysis (2DPCA) method, Sum Equal Error (SSE) method includes a method that can provide accurate data verification value of 90% - 98%. Results of scanned signatures, converted from RGB image - grayscale - black white (binary color). The extraction process of each method requires experimental data as a data source in pixel size. Digital image consists of a collection of pixels then each image is converted in a matrix. Preprocessing Method 2 DPCA each data is divided into data planning and data testing. Extraction on SSE method, each data sought histogram value and total black value. This study yields a comparison of the suitability of the extraction results of each method. Both of these methods have a data accuracy rate of 97% - 98%. When compared to the results of the accuracy of image verification with 2DPCA method: SSE is 97%: 96%. With the same data source will be tested result of 2DPCA method with SSE method.
Comparative Analysis Of Dempster Shafer Method With Certainty Factor Method For Diagnose Stroke Diseases Erwin Kuit Panggabean
International Journal of Artificial Intelligence Research Vol 2, No 1 (2018): June 2018
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (371 KB) | DOI: 10.29099/ijair.v2i1.53

Abstract

The development of artificial intelligence technology that has occurred has allowed expert systems to be applied in detecting disease using programming languages. One in terms of providing information about a variety of disease problems that have recently been feared by Indonesian society, namely stroke. Expert system method used is dempster shafer and certainty factor method is used to analyze the comparison of both methods in stroke.Based on the analysis result, it is found that certainty factor is better than demster shafer and more accurate in handling the knowledge representation of stoke disease according to the symptoms of disease obtained from one hospital in medan city, uniqueness of algorithm that exist in both methods.
Computer Vision and Image Processing: A Paper Review Wiley, Victor; Lucas, Thomas
International Journal of Artificial Intelligence Research Vol 2, No 1 (2018): June 2018
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (570.471 KB) | DOI: 10.29099/ijair.v2i1.42

Abstract

Computer vision has been studied from many persective. It expands from raw data recording into techniques and ideas combining digital image processing, pattern recognition, machine learning and computer graphics. The wide usage has attracted many scholars to integrate with many disciplines and fields. This paper provide a survey of the recent technologies and theoretical concept explaining the development of computer vision especially related to image processing using different areas of their field application. Computer vision helps scholars to analyze images and video to obtain necessary information,    understand information on events or descriptions, and scenic pattern. It used method of multi-range application domain with massive data analysis. This paper provides contribution of recent development on reviews related to computer vision, image processing, and their related studies. We categorized the computer vision mainstream into four group e.g., image processing, object recognition, and machine learning. We also provide brief explanation on the up-to-date information about the techniques and their performance.
The Design of Optimal PID Control Method for Quadcopter Movement Control Arrosida, Hanum; Echsony, Mohammad Erik
International Journal of Artificial Intelligence Research Vol 2, No 1 (2018): June 2018
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.65 KB) | DOI: 10.29099/ijair.v2i1.32

Abstract

Nowadays, quadcopter motion control has become a popular research topic because of its versatile ability as an unmanned aircraft can be used to alleviate human labor and also be able to reach dangerous areas or areas which is unreachable to humans. On the other hand, the Optimal PID control method, which incorporates PID and Linear Quadratic Regulator (LQR) control methods, has also been widely used in industry and research field because it has advantages that are easy to operate, easy design, and a good level of precision. In the PID control method, the main problem to be solved is the accuracy of the gain value Kp, Ki, and Kd because the inappropriateness of those value will result in an imprecise control action. Based on these problems and referring to the previous study, the optimal PID control method was developed by using PID controller structure with tuning gain parameter of PID through Linear Quadratic Regulator (LQR) method. Through the integration of these two control methods, the optimum solutions can be obtained: easier controller design process for quadcopter control when crossing the determined trajectories, steady state error values less than 5% and a stable quadcopter movement with roll and pitch angle stabilization at position 0 radians with minimum energy function.

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