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Palang Pintu Kereta Api Otomatis Berbasis Arduino Pratama, Shendy; Taqwa, Ahmad; Salamah, Irma
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (680.931 KB) | DOI: 10.30645/j-sakti.v3i2.137

Abstract

This automatic train doorstop is made by using two infrared sensors and the sensor's piezeotronic sensor will be controlled by Arduino, this sensor will be useful if it detects the arrival of a train, if the train has passed this sensor then automatically the doorstop will be closed, when the train passes one more sensor then the doorstop will open automatically. For information to the community that there will be a train passing, it must be equipped with a bazzer and other indicator lights. With this automatic doorstop, the level of accident at the railroad crossing will decrease.
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%.
Rancang Bangun Sistem Penyiram dan Pemupuk Otomatis Menggunakan Fuzzy Logic Berbasis Internet of Things (IoT) Miranda, Nadia; Ahmad Taqwa; Abdul Rakhman
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 8 No. 1 (2025): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to design and build an automatic watering and fertilization system for moon orchids (Phalaenopsis) based on the Internet of Things (IoT) using the Fuzzy Logic method. Moon orchids have slow growth and are affected by environmental factors such as temperature and humidity, where the optimal temperature ranges from 25-27°C and air humidity between 60-85%. The system is designed to monitor and control the plant's environmental conditions in real time, as well as perform automatic watering when the soil humidity is below 35% and stop it when it is above 35%. Tests showed error rates between the various sensors used, such as a difference of 1.61% between the DHT22 temperature sensor and a thermometer, 1.78% for humidity between the DHT22 sensor and a hygrometer, and 8.32% between the soil moisture sensor and a soil moisture meter. The Purple Bloom application used in this system experienced an average delay of 6.11 seconds caused by the speed of the internet. Although there is a slight delay, this system provides convenience and efficiency in the maintenance of moon orchids. The use of IoT technology and artificial intelligence shows great potential in improving the productivity and efficiency of plant care.
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.
DESIGN AND CONSTRUCTION OF INTERNET BASED MONITORING DEVICES THINGS(IOT) FOR MONITORING METHANE GAS IN MINES COAL USING MQ-4 SENSOR Aditia Prathama; Ahmad Taqwa; Adewasti
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 5 No. 4 (2025): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/morfai.v5i4.3175

Abstract

Methane gas (CH₄) is a flammable gas and has the potential to cause an explosion if it accumulates in high concentrations. Therefore, an effective monitoring system is needed to detect the presence of methane gas to prevent the danger of gas leaks. This research aims to design and build a methane gas monitoring tool based on the MQ-4 sensor which is capable of detecting the presence of methane gas in real-time. This system uses a microcontroller as the main processing unit and is equipped with a wireless communication module for sending data to the monitoring platform. The MQ-4 sensor was chosen because of its high sensitivity to methane gas and its ability to measure gas concentrations in ppm (parts per million). Measurement data is displayed via a user interface that enables remote monitoring and provides early warning if gas levels exceed specified thresholds. Test results show that this system is able to detect methane gas with good accuracy and provides a fast response to changes in gas concentration. Thus, this tool can be used as an early warning system to improve safety in environments that are at high risk of methane gas leaks.
INTERNET OF THINGS (IOT) BASED SMART CHOPPER SYSTEM WITH WEIGHT MONITORING TO IMPROVE PRODUCTIVITY Rudy Mustaqim; Irma Salamah; Ahmad Taqwa
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 5 No. 4 (2025): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/morfai.v5i4.3225

Abstract

The food processing industry faces challenges in enhancing efficiency and productivity, particularly in raw material processing. This research addresses the limitations of manual cutting processes, which lead to inconsistencies, human error, and prolonged production times. By integrating Internet of Things (IoT) technology into a smart chopper system with weight monitoring, the study aims to automate cutting speed, reduce waste, and improve product quality. The developed system incorporates sensors for weight measurement and voltage monitoring, controlled by an ESP32 microcontroller for real-time adjustments and monitoring. The system’s performance was evaluated based on material hardness and weight, demonstrating its ability to optimize cutting processes and provide consistent results. The IoT integration enables remote control and monitoring, enhancing productivity, reducing waste, and ensuring seasoning quality in the food processing industry.
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.
IoT-Based Alcohol Presence Detection in Soy Sauce Using MQ-3 and ESP32 Almirah, Narita Tria; Taqwa, Ahmad; Salamah, Irma
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2811

Abstract

Ethanol is a compound that naturally forms during the fermentation process of products such as soy sauce, raising concerns about their halal status for Muslim consumers. This research develops an alcohol detection system based on the Internet of Things (IoT) that integrates an MQ-3 sensor, ESP32 microcontroller, and the Blynk mobile application. The MQ-3 sensor detects ethanol vapor, and the ESP32 processes the sensor data and transmits it via Wi-Fi, enabling real-time monitoring through both a 16x2 LCD display and the Blynk app. The system’s calibration process involves standard ethanol solutions with concentrations ranging from 0% to 10%. The sensor output is converted from analog-to-digital (ADC) values to voltage, parts per million (ppm), and percentage estimates. A regression analysis of the sensor data yielded the equation y = 684.59x + 3198.9, with an R2 value of 0.7288, indicating a moderate correlation between ethanol concentration and sensor readings. Using solutions with ethanol concentrations of 1% and 3%, a detection threshold of 5300 ppm was established. Testing on commercial soy sauce samples (0% and 3.08% ethanol) confirmed the system's ability to distinguish between products with and without detectable ethanol, validating its effectiveness. While not designed for precise quantitative analysis, this system offers a practical, economical, and portable solution for initial screening of alcohol in fermented food products, making it a valuable tool for halal product monitoring.