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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) ILKOM Jurnal Ilmiah Internet of Things and Artificial Intelligence Journal
Adi, Puput Dani Prasetyo
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Design and Implementation of IoT-Based Monitoring Battery and Solar Panel Temperature in Hydroponic System Rahmatullah, Rizky; Kadarina, Trie Maya; Irawan, Bagus Bhakti; Septiawan, Reza; Rufiyanto, Arief; Sulistya, Budi; Santiko, Arief Budi; Adi, Puput Dani Prasetyo; Plamonia, Nicco; Shabajee, Ravindra Kumar; Atmoko, Suhardi; Mahabror, Dendy; Prastiyono, Yudi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 3 (2023): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i3.26729

Abstract

Hydroponics is currently widely used for the effectiveness of farming in narrow areas and increasing the supply of food, especially vegetables. This hydroponic technology grew until it collaborated with the internet of things technology, allowing users to monitor hydroponic conditions such as temperature and humidity in the surrounding environment. This technology requires electronic systems to obtain cost-effective power coverage and have independent charging systems, such as power systems using solar panels, where the power received by solar panels from the sun is stored in batteries. It must ensure that the condition of the battery and solar panels are in good condition. The research contribution is to create a solar panel temperature monitoring system and battery power using Grafana and Android Application. Apart from several studies, solar panels are greatly affected by temperature, which can cause damage to the panels. If the temperature is too high, the battery and panel temperature monitoring system can help monitor the condition of the device at Grafana and Android application with sensor data such as voltage, current, temperature and humidity that have been tested for accuracy. Accuracy test by comparing AM2302 sensor with Thermohygrometer and INA219 sensor with multimeter and clampmeter, both of which have been calibrated. The sensor data gets good accuracy results up to 98% and the Quality-of-Service value on the internet of things network is categorized as both conform to ITU G.1010 QOS data based on network readings on the wireshark application. QOS results are 0% Packet loss with very good category, 14ms delay with very good category and Throughput 71.85 bytes/s.  With the results of sensor accuracy and QOS, the system can be relied upon with a high level of sensor accuracy so that environmental conditions are monitored accurately and good QOS values so data transmission to the server runs smoothly.
Design Human Object Detection Yolov4-Tiny Algorithm on ARM Cortex-A72 and A53 Muwardi, Rachmat; Faizin, Ahmad; Adi, Puput Dani Prasetyo; Rahmatullah, Rizky; Wang, Yanxi; Yunita, Mirna; Mahabror, Dendi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27402

Abstract

Currently, many object detection systems still use devices with large sizes, such as using PCs, as supporting devices, for object detection. This makes these devices challenging to use as a security system in public facilities based on human object detection. In contrast, many Mini PCs currently use ARM processors with high specifications. In this research, to detect human objects will use the Mini PC Nanopi M4V2 device that has a speed in processing with the support of CPU Dual-Core Cortex-A72 (up to 2.0 GHz) + Cortex A53 (Up to 2.0 GHz) and 4 Gb DDR4 Ram. In addition, for the human object detection system, the author uses the You Only Look Once (YOLO) method with the YoloV4-Tiny type, With these specifications and methods, the detection rate and FPS score are seen which are the feasibility values for use in detecting human objects. The simulation for human object recognition was carried out using recorded video, simulation obtained a detection rate of 0,9845 or 98% with FPS score of 3.81-5.55.  These results are the best when compared with the YOLOV4 and YOLOV5 models. With these results, it can be applied in various human detection applications and of course robustness testing is needed.
Analysis of IoT-LoRa to Improve LoRa Performance for Vaname Shrimp Farming Monitoring System Adi, Puput Dani Prasetyo; Ardi, Idil; Plamonia, Nicco; Wahyu, Yuyu; Mariana L, Angela; Novita, Hessy; Mahabror, Dendy; Zulkarnain, Riza; Wirawan, Adi; Prastiyono, Yudi; Waryanto, Waryanto; Susilo, Suhardi Atmoko Budi; Rahmatullah, Rizky; Kitagawa, Akio
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i1.27598

Abstract

Shrimp farming requires a touch that must be right on the side of water quality; water is a fundamental factor that must be met to achieve maximum yields. Many factors affect the quality of the water, but some things cause changes in water quality caused by external and internal factors causing death in shrimp. Disease conditions in shrimp can attack at any time, coupled with external factors such as extreme climate change, and cause changes in water components such as water pH, CaMg or hardness, and other factors that cause death in shrimp. Water turbidity oxygen demand (DO) in water determines the life of shrimp. It is coupled with microorganisms that must be maintained to maintain water quality for the growth of a Vaname shrimp. This research raises the Aquaculture System, specifically in the process of intelligent monitoring of water quality in shrimp nurseries to the shrimp harvest process, especially vaname shrimp from the results of observations use three sensors connected to LoRaWAN is able to provide real-time data from pond water and transmit it to LoRa Server or Internet Server, and the realtime data can be read through a Smartphone. This research analyzes in detail the ability of LoRaWAN to send multi-sensor data and Quality of Service LoRaWAN communication at different distances. This research also discusses how the LoRa antenna design can be developed to improve the performance of LoRa as transmitting devices or Radio Frequency 920-923 MHz for sending sensor data for Aquaculture.The contribution of this research is shown in the real-time monitoring system of the water environment, namely water pH, ammonia, turbidity, DO, salinity, water temperature, and nitrate in vaname shrimp ponds. The following contribution is the development of LoRaWAN with Tago IO servers capable of being used in Smart Aquaculture for contributions to The Things Network community or LoRaWAN Community.
Co-Authors Abdul Wahid Adi Wirawan Adiprabowo, Tjahjo Agusti, Nelly Ahmad Faizin, Ahmad Ajib Hanani Ardi, Idil Arief Budi Santiko, Arief Budi Atmoko, Suhardi Ganis Chandra Puspitadewi Harry Soepandi Hsb, Elysa Rohayani Irawan, Bagus Bhakti Irmayani, Deci Johan Ericka Wahyu Prakasa Jumadi Mabe Parenreng Kitagawa, Akio KUNCORO, EKO Kusnandar, Welly Chandra Kusumah Lesmana, Yandri Lukman Hakim Mahabror, Dendi Mahabror, Dendy Mariana L, Angela Mirna Yunita Muhammad Yassir Mustamu, Novilda Elizabeth Novita, Hessy Nurdiana, Dian Pane, Rahmadani Plamonia, Nicco Prastiyono, Yudi Rachmat Muwardi Rahmatullah, Rizky Rufiyanto, Arief Saharuna, Saharuna Sariningrum, Ros Sastya Hendri Wibowo Satyawan, Arief Suryadi Septiawan, Reza Shabajee, Ravindra Kumar Sihombing, Volvo siregar, Victor M.M. Sulistya, Budi Susilo, Suhardi Atmoko Budi Trie Maya Kadarina Wang, Yanxi Waryanto, Waryanto Yulianto, I Putu Eka Yuyu Wahyu Zulkarnain, Riza