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Menampilkan 1–3 dari 3 artikel
COMPARATIVE STUDY OF MULTI CRITERIA DECISION MAKING METHODS IN A CASE STUDY OF THE BEST EMPLOYEE DECISION SUPPORT SYSTEMS
Istini, Syalis Ibnih Melati
; Ahmad Apandi
; Rama Dian Syah
International Journal Science and Technology (IJST)
Vol 3
, No 2
(2024)
Selecting the best employees is an alternative for companies to maintain and improve the quality of employee work. Being best employee is a matter of pride for every employee, so this good thing will also have an impact on the company. Having employees with good quality will certainly improve the quality of the company itself. Making decisions for the best employees is a challenge for companies because its subjective nature makes the selection inaccurate, so an objective decision-making system i...
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APLIKASI ENKRIPSI CITRA DIGITAL BERBASIS CHAOS MENGGUNAKAN ALGORITMA ARNOLD’S CAT MAP
Rama Dian Syah
; Antonius Angga Kurniawan
; Rizki Ariyani
Jurnal Ilmiah Teknik (JUIT)
Vol 1
, No 2
(2022)
The rapid development of technology can lead to vulnerabilities in data and information. Everyone can access that data and information and disseminate it easily through the internet. The data and information can be in the form of text, video, audio, and images that may be confidential. To prevent misuse and unauthorized access to this confidential data and information, a technique is needed to enhance the security of the data. One of these techniques is by encrypting data. This technique is used...
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KLASIFIKASI CITRA DIGITAL TULISAN TANGAN ANGKA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK
Antonius Angga Kurniawan
; Rama Dian Syah
; Rizki Ariyani
Jurnal Ilmiah Teknik (JUIT)
Vol 1
, No 1
(2022)
Rapid technological advances have led to the development of computer vision science in various fields. This research aims to detect handwriting using deep learning technology with the Convolutional Neural Network (CNN) method. The research stages are data sample selection, data preprocessing, data training, data testing, and evaluation of results. This research succeeded in detecting handwriting with an accuracy value of 0.9800 and a loss value of 0.0665. There are several classification errors...
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