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Immersion Cooling and Heatsink System Using Mineral Oil for Enhancing Efficiency and Performance of Polycrystalline and Monocrystalline Solar Panels Suseno T, Moch Adjie; Taqwa, Ahmad; RS, Carlos
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 3 (2024): IJRVOCAS - December
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i3.296

Abstract

Utilizing solar energy is essential for solving the world's energy and environmental problems, however efficiency concerns brought on by solar panels' high temperatures make it difficult. This study looks into alternative cooling techniques that use heatsinks and mineral oil instead of water as in earlier research. Mineral oil, which is frequently utilized in data center cooling systems, efficiently dissipates heat without producing the noise that conventional fans do. According to the findings, polycrystalline panels equipped with immersion and heatsink cooling outperform panels without cooling by 3.57% in power output and 3.28% in efficiency. They also perform 1.80% and 1.42% better, respectively, than panels that merely have heatsinks. Comparing monocrystalline panels to uncooled panels, they perform better, producing 4.46% more power and 4.63% more efficiently. They also outperform panels that merely have heatsinks by 3.33% and 3.08%. By lowering surface temperatures, these cooling methods have the potential to greatly increase the efficiency of solar panels. However, as the data was gathered during 15 sessions between December 2023 and May 2024, more thorough investigation is required for a thorough comprehension. Longer testing is also required for more dependable results.
The Impact of Using Bamboo Activated Carbon as Counter Electrode and Dye from Suji Leaf toward the Efficiency of Dye Sensitized Solar Cells Ismail, Muhammad Fakhri; Taqwa, Ahmad; Kusumanto, R.D
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 3 (2024): IJRVOCAS - December
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i3.304

Abstract

Dye-sensitized solar cells (DSSCs) have attracted great interest due to their ability to convert solar energy into electricity cost-effectively and efficiently. This study aims to create Dye-Sensitized Solar Cells (DSSCs) by utilizing bamboo activated carbon as the counter electrode and natural dyes derived from suji leaves as photosensitizers. Bamboo activated carbon was chosen because of its sustainable nature, large surface area, and excellent conductivity. Likewise, suji leaf dye was chosen because of its capacity to absorb various wavelengths of light. These materials were analyzed using UV-Vis spectroscopy, XRD, and SEM to determine their structure and characteristics. The results of the DSSC efficiency showed that using bamboo activated carbon as the counter electrode produced the highest energy conversion efficiency of 0.0000896%, surpassing the achievement of carbon black electrodes, which only reached 0.0000505%.
Multisensor monitoring system for detecting changes in weather conditions and air quality in agricultural environments Ramadhani, Dwi; Taqwa, Ahmad; Handayani, Ade Silvia; Caesarendra, Wahyu; Husni, Nyayu Latifah; Sitompul, Carlos R
Journal of Environment and Sustainability Education Vol. 3 No. 2 (2025)
Publisher : Education and Development Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62672/joease.v3i2.103

Abstract

The increasing impact of climate change and the need for precision agriculture demand reliable environmental monitoring solutions.This study aims to develop a real-time, multisensor-based environmental monitoring system that displays data via an I2C LCD and a user-friendly web interface. The system utilizes an ESP32 microcontroller connected to a range of sensors, including the DHT22 (for temperature and humidity), MQ-7 and MQ-135 (for CO and CO₂), LDR (for light intensity), a rain sensor, and an anemometer (for wind speed). Testing was conducted over eight hours under various environmental conditions, both indoors and outdoors. Validation was performed by comparing the sensor readings with those from standard measuring instruments. The results showed that the DHT22 sensor had a low error rate of 0.62% for temperature and 0.38% for humidity. Other sensors demonstrated low standard deviation values, indicating stable and consistent measurements. The system also exhibited responsive and accurate performance in detecting changes in environmental parameters. Therefore, this system is effective as an environmental monitoring tool for agricultural applications and can support early decision-making based on environmental condition changes.
Wearable IoT Device for Real-Time Heart Rate and Body Temperature Monitoring Rafiif, Muhammad; Taqwa, Ahmad; Salamah, Irma
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 7, No 2 (2025): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v7i2.3076

Abstract

Heart disease remains one of the primary causes of death worldwide, largely due to sedentary lifestyles and the lack of continuous health monitoring. Many existing wearable health systems fail to provide real-time alerts or offer seamless integration between hardware, cloud platforms, and user interfaces. This study proposes a fully integrated Internet of Things (IoT)-based wearable device for real-time monitoring of heart rate and body temperature. The system utilizes an ESP32 microcontroller combined with MAX30102 and DS18B20 sensors and transmits physiological data via Wi-Fi to the Adafruit IO cloud platform using the MQTT protocol. A custom Android application developed using a low-code environment provides real-time visualization and alert notifications when user-defined thresholds are exceeded. Comparative testing against standard medical devices showed an average error of 1.99% for heart rate and 2.32% for body temperature, demonstrating reliable performance for non-clinical, preventive health monitoring. Unlike previous works, this system offers end-to-end integration, enabling real-time feedback, continuous data access, and user-friendly interaction. Future developments will focus on improving sensor calibration, enhancing ergonomic design, and incorporating advanced features such as historical data tracking and AI-based health alerts.
Implementation of Convolutional Neural Network in Mobile Applications for Solar Panel Crack and Efficiency Prediction Sodiq, Wisnu Kurniawan; Taqwa, Ahmad; Kusumanto
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 5 No. 2 (2025): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v5i2.430

Abstract

Solar panels, as a renewable energy source, are susceptible to efficiency degradation due to cracks in solar cells. Manual crack detection has many limitations, while the use of specialized tools like electroluminescence imaging is not economical for small-scale users. Therefore, this research aims to develop an image-based automatic detection system using the Convolutional Neural Network (CNN) method, specifically the YOLOv8 architecture, integrated into a web-based mobile application using the Flask framework. Solar panel image datasets were collected and annotated using Roboflow, then trained in Google Colab with the help of a GPU. The trained model is integrated into a web-based mobile application, allowing users to upload panel images, detect cracked areas, and estimate panel efficiency based on linear regression of the crack area. Testing results show that the system can function in real-time, although the accuracy of efficiency estimation can still be improved due to limitations in data quantity and variation. This research is expected to be an economical and practical solution for solar panel monitoring.
Integrasi Kamera dan YOLOv5 pada Sistem Keamanan Safety Box Berbasis IoT Rizky Tarmizi, Kgs.M.Dian Akbar; Taqwa, Ahmad; Rakhman, Abdul
Jurnal Teknik Elektro dan Komputasi (ELKOM) Vol 7, No 2 (2025): ELKOM
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/elkom.v7i2.22636167

Abstract

Peningkatan keamanan terhadap akses fisik menjadi isu penting dalam pengembangan sistem berbasis Internet of Things (IoT), khususnya pada aplikasi autentikasi biometrik. Penelitian ini bertujuan untuk mengembangkan sistem keamanan safety box berbasis IoT yang mengintegrasikan kamera digital, algoritma YOLOv5 untuk autentikasi wajah real-time, dan mikrokontroler ESP32 sebagai pengendali aktuator pengunci elektronik. Sistem ini dirancang untuk mengenali wajah secara lokal tanpa ketergantungan pada layanan cloud guna meningkatkan efisiensi, privasi, dan kecepatan respons. Evaluasi dilakukan melalui pengujian fungsional dan analisis metrik performa, termasuk precision, recall, confusion matrix, dan mean Average Precision (mAP). Hasil pengujian menunjukkan bahwa sistem mampu mengidentifikasi wajah terdaftar dan menolak wajah yang tidak terdaftar secara akurat, dengan nilai mAP sebesar 66,3% pada threshold IoU 0,5. Sistem juga menunjukkan ketahanan terhadap variasi pencahayaan, sudut pandang, dan ekspresi wajah. Temuan ini menunjukkan bahwa kombinasi YOLOv5 dan ESP32 dapat diterapkan secara efektif dalam sistem autentikasi wajah real-time untuk aplikasi keamanan berbasis IoT berskala kecil hingga menengah.
Comparative Analysis of LSTM and GRU for River Water Level Prediction Faris, Fakhri Al; Taqwa, Ahmad; Handayani, Ade Silvia; Husni, Nyayu Latifah; Caesarendra, Wahyu; Asriyadi, Asriyadi; Novianti, Leni; Rahman, M. Arief
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5054

Abstract

Accurate river water level prediction is essential for flood management, especially in tropical areas like Palembang. This study systematically analyzes the performance of two deep learning models, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), for real-time water level forecasting using hourly rainfall and water level data collected from automatic sensors. A series of experiments were conducted by varying window sizes (10, 20, 30) and the number of layers (1, 2, 3) for both models, with model performance assessed using RMSE, MAE, MAPE, and NSE. The results demonstrate that both window size and network depth significantly influence prediction accuracy and computational efficiency. The LSTM model achieved its highest accuracy with a window size of 30 and a single layer, while the GRU model performed best with a window size of 20 and two layers. This work contributes by systematically analyzing hyperparameter configurations of LSTM and GRU models on hourly rainfall and water level time series for flood-prone regions, offering empirical insight into parameter tuning in recurrent neural architectures for hydrological forecasting. These findings highlight the importance of careful parameter selection in developing reliable early warning systems for flood risk management.
Multisensor monitoring system for detecting changes in weather conditions and air quality in agricultural environments Ramadhani, Dwi; Taqwa, Ahmad; Handayani, Ade Silvia; Caesarendra, Wahyu; Husni, Nyayu Latifah; Sitompul, Carlos R
Journal of Environment and Sustainability Education Vol. 3 No. 2 (2025)
Publisher : Education and Development Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62672/joease.v3i2.103

Abstract

The increasing impact of climate change and the need for precision agriculture demand reliable environmental monitoring solutions.This study aims to develop a real-time, multisensor-based environmental monitoring system that displays data via an I2C LCD and a user-friendly web interface. The system utilizes an ESP32 microcontroller connected to a range of sensors, including the DHT22 (for temperature and humidity), MQ-7 and MQ-135 (for CO and COâ‚‚), LDR (for light intensity), a rain sensor, and an anemometer (for wind speed). Testing was conducted over eight hours under various environmental conditions, both indoors and outdoors. Validation was performed by comparing the sensor readings with those from standard measuring instruments. The results showed that the DHT22 sensor had a low error rate of 0.62% for temperature and 0.38% for humidity. Other sensors demonstrated low standard deviation values, indicating stable and consistent measurements. The system also exhibited responsive and accurate performance in detecting changes in environmental parameters. Therefore, this system is effective as an environmental monitoring tool for agricultural applications and can support early decision-making based on environmental condition changes.
Cat Feeding Using Microcontroller Arduino Uno TCS3200 Sensor and Internet of Things Wardana, Handava; Salamah, Irma; Taqwa, Ahmad
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.v9i3.26529

Abstract

Petting animals is one way for humans to reduce stress levels and entertain themselves. When coming home from work, a person needs entertainment at home, namely by keeping cute animals; one of the attractive and widely kept pets is a cat. The presence of cats in the house can help restore mood or feelings, and animals that like to be invited to play. For that, the owner must love his own pet without reducing affection for his pet; a cat's diet must be maintained even though the owner is busy working, especially outside the city, because cats need a good diet. Therefore, the purpose of doing this research is to facilitate cat owners in feeding while doing other activities outside the home. In addition, previous research still cannot feed the cat automatically but can monitor the state of cat activity. This tool uses several sensors, namely the RTCDS3231 sensor, TCS3200, Load Cell, HX711, ESP32CAM. The results obtained are Cat Feeding Using Arduino Uno Microcontroller TCS3200 Sensor, and Internet of Things is a tool system that can notify that the feed has run out, can feed the cat automatically, and can find out the activity of the cat by using the sensor. Several pet shop parties strongly agree that this tool is very helpful, namely to reduce the worry of the owner in feeding the cat. 
Implementation of Fuzzy Logic Method to Get Estimation of Fluid Depletion on Smart Infusion Permata Sari, Mira; Taqwa, Ahmad; Silvia Handayani, Ade
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 1 (2024): March 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i1.25589

Abstract

Technology plays an important role in improving healthcare, especially in the field of medical care, particularly in infusion. Infusions are essential in hospitals, requiring constant monitoring by healthcare professionals to ensure patient safety.  The system tracks the remaining infusion fluid and displays this data on the nurse's mobile device, enabling remote control of infusion levels in each patient room. The solution incorporates a load cell sensor to measure infusion weight and an optocoupler sensor to measure infusion drip speed. In addition, the solution uses a fuzzy logic control system to make decisions based on drip speed and infusion weight, estimating when the infusion will run out.Applying this automatic infusion drip monitoring device significantly improves the accuracy and reliability of infusion management, leading to substantial improvements in patient care and safety.In this test, the results can be seen that there is a difference between the weight weighed manually and the weight on the device. with the largest weight difference of 2.49%.