Article Per Year (5 Year)
p-Index From 2021 - 2026
3.753
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal technoscientia Prosiding SNATIF Journal of Engineering and Technological Sciences SMATIKA IJFAC (Indonesian Journal of Fundamental and Applied Chemistry) Sistemasi: Jurnal Sistem Informasi Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Teknologi Sistem Informasi dan Aplikasi Patria Artha Technological Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science bit-Tech Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Teknik Elektro dan Komputasi (ELKOM) JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Teknik Informatika (JUTIF) Fokus Elektroda: Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal of Research in Vocational Studies (IJRVOCAS) Makara Journal of Technology Journal of Environment and Sustainability Education Multidisciplinary Indonesian Center Journal
Ahmad Taqwa
Unknown Affiliation
Religion Aerospace Engineering Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Other

Published : 38 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 38 Documents
Search

 1   2   3   4 
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.
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.
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.
Co-Authors -, sholihin Abdul Rakhman Ade Silvia Handayani Adi Tri Wibowo AIDA SYARIF Almirah, Narita Tria Amperawan, Amperawan Anisah, Masayu Asriyadi Asriyadi Bow, Yohandi Chairunnisa, Dita Ayu Ciksadan, Ciksadan DWI RAMADHANI Emilia Hesti Endri, Jon Evelina, Evelina Faradila, Lusi Risky Faris, Fakhri Al Farozi, Ahmad Fatima, Siti Fibriliyanti, Yanita Ihsan, Muhammad Nabil Irma Salamah Irma Salamah Ismail, Muhammad Fakhri Jaksen M.A Jullia Fatriana Putri Kusumanto Kusumanto, R.D Lanang, Jabbar Kala Leni Novianti Lindawati Lindawati Mardiani, Mega Mila mila Miranda, Nadia Mohammad Fadhli Muhammad Ihsan Muhammad Iqbal Mursalin, Zaldy Gumilang Nursaid, Muhammad Ibrahim Nyayu Latifah Husni, Nyayu Latifah Permata Sari, Mira Putri Nur Azizah, Putri Nur R. Rusdianasari Rafiif, Muhammad Rahman, M. Arief Rahmat Darmawan, Rahmat Rasyad, Sabilal RD Kusumanto Rizky Tarmizi, Kgs.M.Dian Akbar Robby Setiadi RS, Carlos Rusdianasari Rusdianasari Shendy Pratama Sitompul, Carlos R Sodiq, Wisnu Kurniawan Soegijardjo Soegijoko Soegijardjo Soegijoko Sudarso, Hairad Sugihartono Sugihartono Sugihartono Sugihartono Suhartono Tjondronegoro Suhartono Tjondronegoro Suroso Suroso Suseno T, Moch Adjie Syakdani, Adi Wahyu Caesarendra Wardana, Handava Yohandri Bow