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All Journal JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) INTECOMS: Journal of Information Technology and Computer Science Majalah Ilmiah UNIKOM Jurnal Pengabdian kepada Masyarakat Nusantara Brilliance: Research of Artificial Intelligence

Benny Yustim

Universitas Widyatama

Author-ID : 3598132

Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Social Sciences Other

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IMAGE PROCESSING BASED TILAPIA SORTATION SYSTEM USING NA Sukenda Sukenda; Ari Purno Wahyu; Benny Yustim; Sunjana Sunjana; Yan Puspitarani
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 7 No. 1 (2020)
Publisher : Universitas Widyatama

Tilapia has a value of export quality and is imported from America and Europe, tilapia is cultivated in freshwater, the largest tilapia producing areas are Java and Bali for the export market in the Middle East, value fish with a size of 250 grams / head (4 fish / kg ) in their intact form is in great demand. According to news circulating, fish of this size in the Middle East are ordered to meet the consumption of workers from Asia. the fish classification process is a very difficult process to find the quality value of the fish to be sold to meet export quality. Fish classification techniques can use the GLCM technique (Gray Level Oc-Currance Matrix) classification using images of fish critters with the GLCM method.The fish image data is analyzed based on the value of Attribute, Energy, Homogenity, Correlation, Contrash, from the attribute the density data matrix is ??generated for each. Fish image data and displayed in the form of a histogram, the data from the GLCM results are then classified with the Naive Bayes algorithm, from the results of the classification of data taken from 3 types of tilapia from the types of gift, Red, and Blue.

MODELING OF DIGITALIZATION AND VISUALIZATION OF LABOR COMPLAINTS USING OCR, FEATURE EXTRACTION AND BUSINESS INTELLIGENCE Yan Puspitarani; Sukenda Sukenda; Ari Purno Wahyu; Benny Yustim; Sunjana Sunjana
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 7 No. 2 (2021)
Publisher : Universitas Widyatama

The handling of labor complaints is one of the performance factors for Disnakertrans. This performance is related to the decisions that must be taken to determine policies so that violations of labor norms can be reduced. Making this decision will be easier if the data on complaints can be recapitulated quickly and accurately. This recapitulation will be a tool to monitor the leadership in seeing the progress report on the status of incoming complaints. However, the manual administrative process makes the recapitulation slower. Therefore, this study will model the complaint reporting digitization system by utilizing OCR and information extraction as well as modeling the visualization of the results of the recapitulation using Business Intelligence. With the creation of this model, it is hoped that the performance of Disnakertrans in resolving labor complaints will be more effective

Co-Authors Adi Purnama Ari Purno Wahyu Wibowo Deden Sutisna Eka Angga Laksana Hariyanto, Budi Helmy Faisal Mutaqien Muttaqin, Helmy Faisal Nugroho J Setiadi Suharno, Mochammad Syahrindra Akbar Sukenda . Sukenda Sukenda Sunjana * Sunjana Sunjana Ulil Surtia Zulpratita Yan Puspitarani

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Journal : JITTER (Jurnal Ilmiah Teknologi Informasi Terapan)