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Gembong Edhi Setiawan
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Sistem Deteksi Dan Perhitungan Otomatis Bakteri Salmonella dengan Pengolahan Citra Menggunakan Metode Object Counting Lashot Ria Ingrid Melanika; Hurriyatul Fitriyah; Gembong Edhi Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Salmonella is one of the pathogenic bacteria that can cause disease in human digestive tract. The microscopic size makes the Salmonella bacteria invisible without the aid of a microscope. Detection and calculation of bacterial colonies during microscopic observations are still done manually until now. Therefore designed a system that can detect and perform calculations on Salmonella bacteria colonies automatically using the method of color segmentation and object counting. Samples of Salmonella bacteria isolated from chicken meat were made on glass preparations and gram staining was done to make it easier to observe. Bacteria shooting is using the camera on a digital microscope with a resolution of 5 mega pixels. The first process in image processing is image enhancement, then converting RGB image to HSV image. After that performed closing morphological operation, then bacterial colonies were calculated by object counting method. The processing of image processing algorithms is performed on MATLAB, and the system will be displayed on an interface to make it easier for user. The accuracy of input and image information to obtain results with successful status. The average time required during the execution of the system is 4.59 seconds, and the accuracy of detection and calculation of the number of bacterial colonies has an accuracy by 80.81%.
Pengontrolan Derajat Keasaman (pH) Air Secara Otomatis Pada Kolam Ikan Gurame Menggunakan Metode Fuzzy Mamdani Dimas Guntoro; Gembong Edhi Setiawan; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Water treatment is the main thing that must be considered when gurame fish culture and the degree of acidity plays a very important role for the health of underwater ecosystems, because if the degree of acidity is not available as needed then it can be toxic to fish. Based on these problems, the need for research related to the automation system to control the value of acidity degree in accordance with the needs of gurame fish. In this research there are 2 sensors namely pH meter SEN0161 sensor and Ultrasonic sensor HC-SR04 with arduino microcontroller using Fuzzy Mamdani method. The Fuzzy Mamdani method was chosen to control the acidity of the water according to the needs of the gurame fish by adding as much water as determined from Fuzzy Mamdani calculation as the center point z. From the results of several tests performed known error percentage reading pH meter SEN0161 is 2,569% and the error percent reading Ultrasonic sensor HC-SR04 is equal to 2,992%. In testing the water acidity control system using Fuzzy Mamdani done 10 times, 80% accuracy with average computation time of 0,693 seconds.
Sistem Kendali Navigasi Robot Beroda dengan Gestur Tangan Menggunakan Metode Kalman Filter Amelio Eric Fransisco; Gembong Edhi Setiawan; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Research on wheeled robot navigation control has been developed by using human commands directly, one of which is by using hand gestures. The aim is to overcome problems related to the navigation control system. The implementation of an inertial measurement unit (IMU) sensor was developed on the hand gesture control device to detect all forms of movement produced. However, the measurement results by sensors are often inaccurate. The Kalman Filter algorithm is the ideal approach to optimize the estimation of the inaccuracy of signals produced by sensors. Manually tuning the covariance filter is done by changing the matrix covariance noise process with the try and error method based on the predetermined test scenario. The Kalman Filter signal test results show the determination of the variable Q_angle = 0.001, Q_bias = 0.003 and the value of R_measure = 0.03 is optimal in estimating measurements to minimize the effects of noise.
Co-Authors Amelio Eric Fransisco Dimas Guntoro Fitriyah, Hurriyatul Lashot Ria Ingrid Melanika Rizal Maulana