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All Journal JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA)
Koko Joni
Trunojoyo University Madura
Electrical & Electronics Engineering

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Design of Automatic Pesticide Sprayers on Internet-Based Chilli Plants M. Azka Mujaddidin; Miftachul Ulum; Diana Rahmawati; Koko Joni
JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Vol 4 No 2 (2020): October
Publisher : Muhammadiyah University, Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jeeeu.v4i2.312

Abstract

Chili (Capsicum annum L.) is one of the priority needs for consumption by the Indonesian people in general. With these factors, the soaring price of chilies can not be avoided anymore, one of the factors is the attack of pests and diseases of chili plants. Therefore it is necessary to take appropriate and quick action so that pests and diseases attack on chili plants do not spread widely. However, manual spraying has a weakness that is the time needed by farmers for longer, physical fatigue and exposure to pesticides can endanger the health of farmers in the short and long term. Therefore spraying pesticides electronically can be a solution to this problem. The testing process can be seen from the top of the leaves affected by the disease, then the results of this study can design a system for automatic spraying of pesticides based on the type of disease that attacks by using the Internet of Things and the wifi module ESP8266. The overall results of the trial can be concluded that in testing 10 trials determine the automatic spraying of pesticides 100% success indicator. And Quality of Service for sending value during the trial with index value 3 (satisfactory).
Identification and Classification of Pathogenic Bacteria Using the K-Nearest Neighbor Method Diana Rahmawati; Mutiara Puspa Putri I; Miftachul Ulum; Koko Joni
JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Vol 5 No 1 (2021): April
Publisher : Muhammadiyah University, Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jeeeu.v5i1.1221

Abstract

Bacteria are a group of living things or organisms that do not have a core covering. In the grouping, some bacteria are pathogenic. With a microscopic size, many pathogenic bacteria are found around and spread through the food eaten or by touching objects around them, then cause diseases such as diarrhea, vomiting, and others. As a more effective effort to help the government and society prevent disease caused by pathogenic bacteria, a system for the identification and classification of pathogenic bacteria K-Nearest Neighbor was created. This system uses a biological microscope that is attached to a webcam camera above the ocular lens as a tool to see bacterial objects and assist in bacterial capture. Rough player rotates automatically (auto-focus) in image capture. In the process of classification and identifying bacteria, the K-Nearest Neighbor method is used, which is a method with the calculation of the nearest neighbor or calculation based on the level of similarity to the dataset. In this study, the bacteria vibrio chlorae, staphylococcus aereus, and streptococcus m. with the highest accuracy is the K = 9 value of 97.77% using the Chebyshev method.
Planning and Manufacturing of Four Axis Solar Panels With Reflector Angle Adjustments Miftachul Ulum; Adi Kurniawan Saputro; Koko Joni; Riza Alfita; Rosida Vivin Nahari; Siti A’isya; Achmad Ubaidillah
JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Vol 6 No 1 (2022): April
Publisher : Muhammadiyah University, Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jeeeu.v6i1.1628

Abstract

Solar thermal energy is one type of renewable energy, so this type of energy can be converted into other energy. This study uses a four-axis solar tracker with angle settings on the reflector to get optimal sunlight, scanning to determine the optimal lighting angle, measurement results are stored in real-time in the data logger. This study uses an LDR (Light Dependent Resistor) as a sunlight detector, equipped with several sensors, namely: current, voltage and power sensor (INA219), light sensor (MAX4409), and temperature sensor (DS18B20), and reflector angle as a parameter of solar efficiency panels. . The results showed that a four-axis solar tracker equipped with a reflector was able to increase the output power. The maximum power production produced by solar panels is: At a reflector angle of 300, the maximum power generated by a static panel is 143.43 W while a solar tracker is 175.15 W. At a reflector angle of 450 the maximum power generated by a static panel is 170.01 W and solar tracker 236.36 W. At an angled reflector of 600 the full power generated by a static panel is 87.77 W, and a solar tracker is 123.36 W. This study concludes that a solar tracker panel with an angle setting of 300 is more capable of maximizing power output than a static solar panel.
Co-Authors Achmad Ubaidillah Adi Kurniawan Saputro Diana Rahmawati M. Azka Mujaddidin Mutiara Puspa Putri I Riza Alfita ROSIDA VIVIN NAHARI Siti A’isya Ulum, Miftachul