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Richki Hardi
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Mulia International Journal in Science and Technical
Published by Universitas Mulia
ISSN : -     EISSN : 26227754     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering
The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Science and Technical. MULTICA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. MULTICA invites submissions in all areas of Science and Technical.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 3 Documents
 1 
Search results for , issue "Vol 2 No 2 (2019): December" : 3 Documents clear
Simulation of Automatic Rail Portal Closing Doors Using Regular Straight Movement Form Sri Winar
Mulia International Journal in Science and Technical Vol 2 No 2 (2019): December
Publisher : Universitas Mulia

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Abstract

A train station is an essential tool, but the services provided to train passengers are still not optimal. At present, there are still some weaknesses, including the arrival and departure of trains that always rely on telephone communication with other station officials. Notification of train arrival will be conveyed by telephone by officers at the station beforehand to the destination station. When receiving an information on entry, the station clerk will close the railroad portal. The process can have a weakness, and if officer negligence occurs, it can cause an accident. Also, for train passengers who will board at the train station, there is no formal notification related to the arrival of the train. This is due to the absence of an automatic operating system at the railroad crossing portal. Because the manual system must use human power or operators to operate open and close railroad crossing portals. So the operator error and the failure of portal operations that can manually lead to the higher possibility of a train accident at the crossing entrance. The above problems can be overcome by implementing a portal closure system automatically. With an automated portal system, the portal will automatically close if there will be a train crossing the crossing. And the portal will automatically reopen if the passenger has passed the bridge. So it is expected that with this automatic portal closure system, traffic accidents due to not closing the portal when the train crosses the bridge can be avoided.
Image Processing For Improving Image Quality Using The Improvement Method Of Image And Improvement Image Fitri Rizani
Mulia International Journal in Science and Technical Vol 2 No 2 (2019): December
Publisher : Universitas Mulia

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Abstract

Better computer skills in various fields, better in the field of image processing through a process of increasing image quality that is once received. Help empower the computer at any time needs to be improved. Image Quality Improvement can be made with various techniques; one of them is by Improving Image Quality with Image Brightness and Image Sharpening methods. The process begins with capturing images followed using increasing competence, image contrast, and sharpening. The results of image processing are generated by changes in the resulting image and changes in image histograms.
Cardiovascular Disesases Treatment Prediction Using Support Vector Machine Apri Junaidi; Jerry Lasama
Mulia International Journal in Science and Technical Vol 2 No 2 (2019): December
Publisher : Universitas Mulia

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Abstract

­The number 1 diseases that take up to 17 million lives annually are Cardiovascular diseases (CVDs).  CVDs mistreatment would increase the risk dramatically to the point that saving the patient deemed impossible. The dataset used in this research originated from RSUP DR. M Djamil Padang from January 2014, until July 2014 with 426 entries and seven columns, the data also digitized in CSV form from the log journal with a lot of wrong data input because the data has not been standardized yet. The proposed method analyses the pattern of patient diagnosis, age, insurance, origin, and gender using Support Vector Machine (SVM) and predicts the appropriate treatment for the patient. In the process,  SVM drew a hyperplane for each target class in the transformed training set by the radial basis function (RBF), and classify the target data. Simulation results on CVDs treatment prediction show 50% accuracy, which then improved by Gaussian Process optimizer and the score increased to 66%.

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