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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer TANJUNGPURA LAW JOURNAL Journal of Robotics and Control (JRC)
Ari Hernawan
Fakultas Hukum Universitas Gajah Mada
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering

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Penjadwalan Perkuliahan dengan Pendekatan Evolutionary Algorithm (Studi Kasus : Sistem Informasi Akademik (SIAKAD) Program Teknologi Informasi dan Ilmu Komputer Universitas Brwijaya) Wicaksono, Satrio Agung; Setiyawan, R. Arief; Setiyawan, Budi Darma; Hernawan, Ari; Perdana, Rizal Setya
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 1, No 2 (2014)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (763.832 KB)

Abstract

Abstrak Untuk menyusun jadwal kuliah bukanlah sesuatu yang mudah karena terkait aturan-aturan yang ada. Penjadwalan perkuliahan jika dilakukan dengan cara manual tentu saja akan memakan waktu cukup lama. Oleh karena itu pada penelitian ini mencoba untuk melakukan pendekatan menggunakan evolutionary algorithm untuk mempermudah dalam pembuatan jadwal kuliah dengan menerapkan aturan yang berlaku. Kromosom disusun dalam bentuk representasi string dengan susunan yang mewakili hari, jam perkuliahan, ruang dan gedung. Dari beberapa percobaan paremeter yang digunakan, diperoleh hasil optimal pada jumlah individu 100 dan peluang crossover sebesar 75%. Kata kunci: algoritma evolusi, algoritma genetik, penjadwalan mata kuliah. Abstract It is not an easy task to arange academic schedule because it is affected by many constraints. If this scheduling is done manually, it will consume many times. Therefore, this research tries to use the evolutionary algorithm approach to do schedulling by applying the applicable rules. Chromosomes are represented as string, which each of them consist of days, times, rooms, dan the buildings. From some experiments whisch are used in this research, optimal result obtained when use 100 individu in one population and 75% chance of crossover. Keywords: evolution algorithm, genetic algorithm, class scheduling
THE PRESENCE OF PENALTY CLAUSE UNDER EMPLOYMENT AGREEMENT Hernawan, Ari
TANJUNGPURA LAW JOURNAL Vol 2, No 1 (2018): VOLUME 2 ISSUE 1, JANUARY 2018
Publisher : Faculty of Law, Tanjungpura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (674.677 KB) | DOI: 10.26418/tlj.v2i1.32674

Abstract

The research has the objectives of identifying and analyzing the presence of penalty clause under Employment Agreement from Employment Law perspective and identifyng as well as analyzing the implementation of penalty clause under Employment Law by Mediator on Employment within their recommendation.This is a normative and empirical research. The data is obtained from library and field research by way of document review and interview of the subject of research. The data are analyzed qualitatively while the result is presented descriptively. The result research shows that the presence of penalty clause under Employment Agreement is not regulated explicitly under Employment Law, but since one of the aspects of Employment Law is subject to Civil Law through Employment Law, the provision of Contract Law regulated under Book III of The Indonesian Civil Code remains applicable. In this regard, Civil Law must be deemed as law in general, unless otherwise determined by Employment Law. A mediator’s recommendation on Employment Law does not fully implement penalty clause which is presence in The Employment Agreement since it is considered as contradictory to the reasonableness and justice. Mediator prioritizes good faith principle over pacta sunt servanda principle in providing their recommendation.
Real-Time Human Detection Using Deep Learning on Embedded Platforms: A Review Rahmaniar, Wahyu; Hernawan, Ari
Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November (Forthcoming Issue)
Publisher : Universitas Muhammadiyah Yogyakarta

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Abstract

The detection of an object such as a human is very important for image understanding in the field of computer vision. Human detection in images can provide essential information for a wide variety of applications in intelligent systems. In this paper, human detection is carried out using deep learning that has developed rapidly and achieved extraordinary success in various object detection implementations. Recently, several embedded systems have emerged as powerful computing boards to provide high processing capabilities using the graphics processing unit (GPU). This paper aims to provide a comprehensive survey of the latest achievements in this field brought about by deep learning techniques in the embedded platforms. NVIDIA Jetson was chosen as a low power system designed to accelerate deep learning applications. This review highlights the performance of human detection models such as PedNet, multiped, SSD MobileNet V1, SSD MobileNet V2, and SSD inception V2 on edge computing. This survey aims to provide an overview of these methods and compare their performance in accuracy and computation time for real-time applications. The experimental results show that the SSD MobileNet V2 model provides the highest accuracy with the fastest computation time compared to other models in our video datasets with several scenarios.
Co-Authors Budi Darma Setiyawan Murti Pramuwardhani Dewi Ninik Darmini R. A. Antari Innaka R. Arief Setiyawan Rahmaniar, Wahyu Rizal Setya Perdana Satrio Agung Wicaksono Tata Wijayanta Taufiq El Rahman