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All Journal INOVTEK Polbeng - Seri Informatika Jurnal Segara
Akhmad Hendriawan
Politeknik Elektronika Negeri Surabaya
Computer Science & IT Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology

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Salinity Sensor Development for Pond Water Utilizing Ultrasonic Wave Dananjaya Endi Pratama; Agus Indra Gunawan; Rusminto Tjatur Widodo; Akhmad Hendriawan
Jurnal Segara Vol 18, No 2 (2022): August
Publisher : Politeknik Kelautan dan Perikanan Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/segara.v18i2.10932

Abstract

Shrimp farming is one of the most popular aquaculture activities in Indonesia. This activity is carried out in a pond. Therefore, there are many ponds as a place for shrimp farming in Indonesia. Several factors affect the results of shrimp farming in ponds. One of the factors is water quality. Four parameters that are commonly used to indicate water quality i.e. dissolve oxygen, salinity, PH, and temperature. In this study, we discussed salinity measurement. Most salinity sensors use the probe principle in measurement. When the sensors are used to measure the water that contains mineral salts, the probe will be susceptible to rust and cause measurement errors. Based on these conditions, we conducted a study of salinity measurements by using the acoustic technique. The measurement was carried out by using an ultrasonic wave. The water salinity was determined based on the acoustic intensity and acoustic speed. In this research, we developed a conversion curve based on the measurement of acoustic intensity from NaCl, KCl, and MgCl2 saline solutions with certain concentrations. The conversion curve is used to measure salinity in pond water. We also calculated salinity based on the measurement result of acoustic speed. From the experiment, the NaCl conversion curve became the most suitable for salinity measurement. The measurement result of salinity in pond water from the NaCl saline solution conversion curve was very close to the results of Del Grosso formula, Chen Millero formula, and refractometer.
Sistem Deteksi Lampu Lalu Lintas Sebagai Asisten Pengemudi Menggunakan Convolutional Neural Network Akhmad Hendriawan; Muhammad Iqbal Millyniawan Pradana; Ronny Susetyoko
Jurnal Inovtek Polbeng Seri Informatika Vol 8, No 1 (2023)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v8i1.3155

Abstract

Accident cases in Indonesia are increasing along with the increase in the number of motorized vehicles. From 2016 to 2017, speed limit violations increased by 96.20% and violations of road markings or signs also increased by 5.54%. Intelligent transportation system is one solution to reduce the number of accidents. Currently Driver Assistance Systems (DAS) are being developed in the automotive world. The purpose of this research is to design a watershed based on three input parameters for determining recommended actions, namely: 1) distance to the vehicle behind; 2) vehicle speed; and 3) traffic light status with recommendation action using fuzzy rule base. Lidar sensor for distance detection and GPS for monitoring vehicle speed. The YOLOv4 Algorithm method is used to detect traffic lights. The results of this study, the accuracy of sign color recognition is 92.831% with a detection speed of up to 8.94 FPS. The most stable reading distance is between 1 – 8-meters with a light intensity of 10 – 3200 lux and a tilt angle of up to 90 degrees. There is a drop in processing speed of up to 1.5 FPS during system integration. This DAS is effective enough to be applied to two-wheeled and fourwheeled motorized vehicles.
Co-Authors Agus Indra Gunawan Dananjaya Endi Pratama Muhammad Iqbal Millyniawan Pradana Ronny Susetyoko Rusminto Tjatur Widodo