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All Journal IAES International Journal of Robotics and Automation (IJRA) Jurnal Buana Informatika Journal of Engineering and Technological Sciences
Putro, Nur Achmad Sulistyo
Departemen Ilmu Komputer Dan Elektronika, Universitas Gadjah Mada
Automotive Engineering Computer Science & IT Electrical & Electronics Engineering Engineering

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AN INTELLIGENT INCENTIVE MODEL BASED ON ENVIRONMENTAL ERGONOMICS FOR FOOD SMES Ushada, Mirwan; Putro, Nur Achmad Sulistyo; Khuriyati, Nafis
Journal of Engineering and Technological Sciences Vol 51, No 6 (2019)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2019.51.6.7

Abstract

In this study, an intelligent incentive model based on environmental ergonomics in food small and medium-sized enterprises (SMEs) was developed. Environmental ergonomics was defined as the impact of temperature and relative humidity within a certain range on a worker?s heart rate during work. Optimum environmental ergonomics are highly required as a basic standard for food SMEs to provide fair incentives. Recommendable parameters from a genetic algorithm and fuzzy inference modeling were used to model customized incentives based on optimum heart rate, workplace temperature and relative humidity before and after working. The research hypothesis stated that industries should optimize their workload and workstation environment prior to customizing incentives. The research objectives were: 1) to recommend optimum environmental ergonomics parameters for customized incentives; 2) to determine the incentives at workstations of SMEs based on optimum environmental ergonomics parameters and fuzzy inference modeling. The optimum values for heart rate, workstation temperature and relative humidity used were based on recommendable values from the genetic algorithm. An inference model was developed to generate decisions whether a worker should receive an incentive based on a calculated index. The results indicated that 84.4% of workers should receive an incentive. The results of this research could be used to promote the concept of ergonomics-based customized incentives.
Quadrotor Control System with Hand Movement Sign as an Alternative Remote Control Nur Achmad Sulistyo Putro; Andi Dharmawan; Tri Kuntoro Priyambodo
IAES International Journal of Robotics and Automation (IJRA) Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1239.604 KB) | DOI: 10.11591/ijra.v6i2.pp131-140

Abstract

Quadrotor is an unmanned aerial vehicle which is controlled by remote control. Unfortunately, not all of the remote control are easy to use, especially for people who have lacking abilities in piloting. This study aims to design a prototype system to control  quadrotor using hand movements, as an alternative to the conventional remote control that more simple. This system is consists of 2 parts, quadrotor and handheld. Both systems can communicate wirelessly using radio frequency 2.4 GHz. The handheld system will read the orientation angle of the hand by IMU sensor and it will be converted into a command to determine the direction motion of the quadrotor. To get the orientation angle from the IMU sensor data, we used DCM sensor fusion method. Quadrotor needs a control system that can make its respond runs optimally. In this study, the method of the control system that used is PID controller. The PID gain obtained using Ziegler-Nichols oscillation method and then fixed again by fine-tuned method.
An Intelligent Incentive Model Based on Environmental Ergonomics for Food SMEs Mirwan Ushada; Nur Achmad Sulistyo Putro; Nafis Khuriyati
Journal of Engineering and Technological Sciences Vol. 51 No. 6 (2019)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2019.51.6.7

Abstract

In this study, an intelligent incentive model based on environmental ergonomics in food small and medium-sized enterprises (SMEs) was developed. Environmental ergonomics was defined as the impact of temperature and relative humidity within a certain range on a worker's heart rate during work. Optimum environmental ergonomics are highly required as a basic standard for food SMEs to provide fair incentives. Recommendable parameters from a genetic algorithm and fuzzy inference modeling were used to model customized incentives based on optimum heart rate, workplace temperature and relative humidity before and after working. The research hypothesis stated that industries should optimize their workload and workstation environment prior to customizing incentives. The research objectives were: 1) to recommend optimum environmental ergonomics parameters for customized incentives; 2) to determine the incentives at workstations of SMEs based on optimum environmental ergonomics parameters and fuzzy inference modeling. The optimum values for heart rate, workstation temperature and relative humidity used were based on recommendable values from the genetic algorithm. An inference model was developed to generate decisions whether a worker should receive an incentive based on a calculated index. The results indicated that 84.4% of workers should receive an incentive. The results of this research could be used to promote the concept of ergonomics-based customized incentives.
Pengenalan Personal Menggunakan Citra Tampak Atas pada Lingkungan Cashierless Strore Bambang Nurcahyo Prastowo; Nur Achmad Sulistyo Putro; Oktaf Agni Dhewa; Ach Maulana Habibi Yusuf
Jurnal Buana Informatika Vol. 10 No. 1 (2019): Jurnal Buana Informatika Volume 10 Nomor 1 April 2019
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v10i1.1779

Abstract

Abstract.Personal recognition with image processing techniques from the side view has the disadvantage of being applied to the cashierless store environment, namely inaccurate recognition or identification when personal collisions occur. To overcome this, the image capture method is used from the top-view. Personal recognition method through the top-view image using the Haar Cascade Classifier method. 1420 positive images and 2170 negative images are used to find features that are considered suitable for recognizing objects using the Adaptive Boosting (Adaboost) method. Tests were carried out on 100 test data by varying the parameters of min_neighbors (3.4, and 5) and the size of the dataset window (25x25, 35x35, 45x45 pixels). Personal recognition testing gets the highest accuracy of 89.9% with the parameters used are min_neighbors 5 and the size of the 25x25 pixel dataset in the detection parameter size of min_size 140x140 pixels.Keywords: Person recognition, image processing, cashierless storeAbstrak. Pengenalan personal dengan teknik pengambilan citra dari tampak samping memiliki kelemahan untuk diterapkan pada lingkungan cashierless store yaitu tidak akuratnya pengenalan atau identifikasi saat terjadi tubrukan antar personal. Untuk mengatasi hal tersebut maka dipakailah metode pengambilan citra dari tampak atas. Metode pengenalan personal melalui citra tampak atas menggunakan metode Haar Cascade Classifier. Digunakan 1420 citra positif dan 2170 citra negatif untuk menemukan fitur-fitur yang dianggap cocok untuk mengenali objek dengan menggunakan metode Adaptive Boosting (Adaboost). Pengujian dilakukan terhadap data tes sebanyak 100 citra dengan menvariasikan parameter min_neighbors (3,4, dan 5) dan ukuran window dataset (25x25, 35x35, 45x45 piksel). Pengujian pengenalan personal mendapatkan akurasi tertinggi sebesar 89,9% dengan parameter yang dipakai yaitu min_neighbors 5 dan ukuran window dataset 25x25 piksel pada parameter ukuran pengujian min_size 140x140 piksel.Kata Kunci: pengenalan personal, pengolahan citra, cashierless store
Co-Authors Ach Maulana Habibi Yusuf Andi Dharmawan Bambang Nurcahyo Prastowo Mirwan Ushada Nafis Khuriyati Oktaf Agni Dhewa Tri Kuntoro Priyambodo