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All Journal PROtek : Jurnal Ilmiah Teknik Elektro bit-Tech Devotion: Journal of Research and Community Service Jurnal Ilmiah Telsinas Elektro, Sipil dan Teknik Informasi Journal Of World Science Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) ITEJ (Information Technology Engineering Journals)
Juju Juhaeriyah
Universitas Swadaya Gunung Jati
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences

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RANCANG BANGUN HEALTH MONITORING SYSTEM BERBASIS INTERNET OF THINGS (IoT): ESP8266 DAN BLYNK Juju Juhaeriyah; Edo Agung N; Rindi Wulandari
bit-Tech Vol. 6 No. 2 (2023): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v6i2.1036

Abstract

Health monitoring is important for living creatures. There are many things that are important factors in the health of living creatures, especially humans, including heart rate, body temperature and oxygen saturation. IoT technology is very helpful in the development of health technology so that it becomes possible to monitor patient health in real time and patient emergency information can be accessed easily. This research also aims to design an Android-based heart rate monitoring system using ESP8266 as a microcontroller. The sensor used is Max30102. The research method used is applied research, with experimental research methods. The research stages carried out were literature study, software design, hardware design, system testing, and analysis. The results of the research are the design of a patient health monitoring tool with three measured indicators, namely the patient's heart rate, body temperature and oxygen levels. The system can monitor in real time based on Internet of Things and can be accessed by Android and iOS. From the study results, it was found that the Android-based health monitoring system has an accuracy rate of 97.63% and it can be said that the system can be used for patient measurements. With details, 96.71% is the accuracy level for measuring heart rate, 96.45% accuracy level for measuring oxygen levels in the patient's body, and 99.75% accuracy level for measuring patient temperature.
A Comparative Analysis of Sugeno and Tsukamoto Fuzzy Logic for Temperature Stability in SCAMIS Hidayat, Rizky Nugraha; Idris, Fahmi; Juhaeriyah, Juju
PROtek : Jurnal Ilmiah Teknik Elektro Vol 12, No 3 (2025): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v12i3.10514

Abstract

The digital poultry sector faces challenges in maintaining stable incubation temperatures. Comparative evaluation between Sugeno and Tsukamoto methods has not been conducted in real-world IoT systems. This research is essential to identify the most effective fuzzy logic control approach for smart incubators. This study aims to compare the effectiveness of Sugeno and Tsukamoto fuzzy logic methods through implementation in the SCAMIS platform. A comparative experimental design was employed using Sugeno and Tsukamoto models in SCAMIS. Temperature data were collected via DHT22 sensors and analyzed quantitatively. Code validation and sensor accuracy tests ensured data reliability and the credibility of fuzzy decision-making processes. The accuracy level of the DHT22 sensor when detecting temperature is 98.31%. The comparison of response time from initial temperature to target temperature (30°C - 38°C) between the Tsukamoto and Sugeno fuzzy logic methods is 1 : 3. Tsukamoto takes 1 hour 52 seconds (3,652 seconds), while Sugeno takes 3 hours 1 second (10,801 seconds). The response time required by Tsukamoto for each 1°C temperature increase is 1–7.5 minutes, while Sugeno is 1–10.3 minutes. However, in terms of temperature stability, Sugeno is more stable with an accuracy rate of 98.40% approaching the target temperature, while Tsukamoto has an accuracy rate of 96.93%. These results indicate a significant trade-off between the speed of reaching the target temperature and stability at the target temperature. Control method selection should align with specific operational priorities in smart incubation systems. These findings recommend choosing fuzzy methods based on system priorities. Future studies should evaluate energy consumption and hatching success efficiency.
Design and Build an Internet of Things (IoT) Based Wastewater Monitoring System at Cirebon Pelabuhan Hospital Muhaimin, Muhammad; Dony, Abdul Rochman; Juhaeriyah , Juju
Devotion : Journal of Research and Community Service Vol. 6 No. 9 (2025): Devotion: Journal of Community Research
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/devotion.v6i9.25539

Abstract

Wastewater at the Cirebon City Port Hospital that is not treated properly can cause environmental damage. In this case, technological advances are very rapidly developing in the manufacture of sophisticated tools, namely tools that can work automatically and have high precision. Therefore, in this study, we will conduct a prototype for monitoring the Wastewater Management Installation (WWTP), so hereby the author develops his research by directly applying the Wastewater Management Installation (WWTP) at Cirebon Port Hospital. In this prototype we used an esp 8266 microcontroller to read commands, a turbidity sensor to measure water turbidity, a DS18B20 sensor to measure the temperature of the water, a pH sensor to measure the acidity level of the water and an MIT App to read the output that is read by the sensor input that has been read by the firebase in real-time. The calibration results showed that all sensors were able to read the values with fairly good accuracy. The pH sensor shows an average accuracy of about 97.8%. The turbidity sensor shows an average accuracy of about 97.1%. The temperature sensor DS18B20 shows an average accuracy of about 97.7%. In the test results of the samples from the 4 readings in tubs 1 to 3, an error was shown because the results of the turbidity sensor reading were above 30 because the 1 to 3 tubs had not been filtered.
IoT- Based Smart Security System Using Infrared Sensor as Motion Detector Muhamad Riyad Ariwibowo; Juju Juhaeriyah; Edo Agung Nugroho; Rendi Mutaqim
ITEJ (Information Technology Engineering Journals) Vol. 8 No. 1 (2023): June
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v8i1.109

Abstract

Today’s security system requires the support of new technology to make it easier to monitor remotely and maintain valuables stored at home in real time. Internet of things technology has now been widely developed with various types of electronic components applied. So, from these problems providing innovation with the development of a remote security system applied to the FC-51 infrared sensor and ESP8266 as it’s control. The infrared sensor receives input signals in the form of objects detected and received by ESP8266 to be sent information to the server to be notified of messages from the Blynk platform to mobile devices. The results of this study prove, that the smart security system with IoT – based infrared sensor is able to detect the optimal distance obtained < 30cm and the shape of different objects determines the level of accuracy of the sensor.
Design and Development of Heart Vest for Heart health Monitoring Based on Internet of Things (IoT) Muhammad Iqbal Saputra P; Muhammad Miftahul Robih; Juju Juhaeriyah
Journal of World Science Vol. 4 No. 10 (2025): Journal of World Science
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jws.v4i10.1525

Abstract

IoT-based cardiac monitoring systems face the challenges of accuracy and convenience. The integration of real-time wearable based on AD8232 and ESP8266 has not been widely explored functionally. This research is important to develop a cheap, portable, and reliable heart monitoring solution. This research aims to design and test Heart Vest as a real-time heart monitoring system based on IoT and mobile applications. Experimental research was conducted by testing IoT devices based on AD8232 and ESP8266 sensors. Data is sent to Firebase and visualised through an Android application. Tests of sensor accuracy, data synchronisation, and BPM status classification are carried out to ensure system reliability. The test results show that the AD8232 sensor has an average accuracy of 97.8% (2.20% error). Data synchronisation between the Heart Vest LCD and the mobile application reached 100%. The system successfully classified the heart status (normal, alert, danger) with 100% accuracy and provided alerts via LED and buzzer. These findings demonstrate the reliability of the Heart Vest as an efficient, economical, and responsive real-time monitoring system in the context of non-clinical use. These findings strengthen the adoption of IoT wearable systems for cardiac monitoring. Further research needs clinical trials and multi-sensor integration.
Analisis Eksperimental Supervisory Adaptive Fuzzy Control untuk Kestabilan Nutrisi dan Ketersediaan Air pada Sistem Hidroponik Cerdas Juju Juhaeriyah; Muhamad Riyad Ariwibowo; Ahmad Syahruli
Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) Vol. 4 No. 1 (2026): JURNAL PENGEMBANGAN TEKNOLOGI INFORMASI DAN KOMUNIAKSI (JUPTIK)
Publisher : Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/juptik.v4i1.4244

Abstract

Sistem hidroponik modern menghadapi masalah ketidakstabilan kadar nutrisi dan ketersediaan air. Penelitian sebelumnya belum mengintegrasikan Supervisory Adaptive Fuzzy Control (SAFC) dengan pemantauan IoT secara terpadu dan adaptif. Penelitian ini penting untuk mendukung pertanian presisi yang berkelanjutan melalui kontrol hidroponik otomatis yang efisien dan responsif, yang dapat beradaptasi dengan dinamika lingkungan pertanian modern. Studi ini bertujuan untuk mengembangkan sistem hidroponik cerdas berbasis IoT dengan menggunakan SAFC untuk menstabilkan nutrisi dan ketersediaan air. Pendekatan eksperimental diterapkan, mencakup desain arsitektur IoT, perakitan prototipe, implementasi algoritma SAFC, serta pengujian dan analisis. Pengujian mencakup akurasi sensor, validasi aturan, dan analisis real-time terhadap stabilitas nutrisi dan ketersediaan air. Hasil pengujian menunjukkan bahwa sensor TDS mencapai akurasi 96,49% dengan kesalahan 3,51%, sedangkan sensor ultrasonik mencapai akurasi 95,66% dengan kesalahan 4,34%. Sistem secara konsisten memenuhi sembilan aturan SAFC pada semua variasi pengujian. Eksperimen stabilitas yang berlangsung selama 33 menit untuk setiap variasi menunjukkan bahwa rasio aliran 1:2 menghasilkan stabilitas terbaik yakni kategori cukup, dengan rata-rata TDS 762,83 ppm dan tingkat kedalaman air 6,05 cm. Integrasi IoT memungkinkan sinkronisasi data secara real-time antara prototipe, aplikasi seluler, dan aplikasi desktop dengan akurasi transmisi 100%, mendukung pemantauan dan pengendalian jarak jauh yang efisien dan berkelanjutan pada sistem hidroponik. Temuan ini memperkuat pengembangan pertanian presisi cerdas berbasis kontrol adaptif. Penelitian lebih lanjut sebaiknya mengintegrasikan pembelajaran mesin ringan dan validasi dalam lingkungan rumah kaca dunia nyata.
A Raspberry Pi Local Server-Based Wearable Device System for Heart Health Monitoring Alamul iman; Juju Juhaeriyah
Jurnal Ilmiah Telsinas Vol 9 No 2 (2026)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/telsinas.v9i2.7779

Abstract

Cardiovascular diseases, including arrhythmia and heart failure, remain major causes of death worldwide. Cloud-based ECG monitoring systems may face challenges related to dependence on internet connectivity and data transmission. This study aimed to develop a prototype of a local-network-based wearable ECG monitoring system using a Raspberry Pi as a local server without relying on public internet connectivity. A modified Research and Development (R&D) method was applied through requirements analysis, system design, prototype development, and system evaluation. The system integrated an AD8232 ECG sensor, an ESP8266 microcontroller, and a Raspberry Pi. ECG data were transmitted in real time through a local Wi-Fi network using HTTP over TCP/IP and stored in a MySQL database. BPM measurements were validated against a pulse oximeter using 10 measurements for each of six participants aged 14–87 years, resulting in 60 measurements in total. The system achieved an average accuracy of 97.75% and an average error of 2.25%. The prototype successfully acquired and recorded raw ECG and BPM data, classified heart rate into predefined normal, bradycardia, and tachycardia categories, and provided corresponding LED indicators. The system is intended for ECG and heart-rate monitoring and does not provide clinical diagnosis of cardiac conditions.
Smart Irrigation System And Grow Lights For Tomato Plants Based On The Internet Of Things Using The Fuzzy Logic Method Lutvi Aji Setiawan; Juju Juhaeriyah
PROtek : Jurnal Ilmiah Teknik Elektro Vol 13 No 3 (2026): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v13i3.11753

Abstract

This study was conducted to develop and test an Internet of Things (IoT)-based automated irrigation and lighting system for tomato plants using the Tsukamoto Fuzzy Logic method. The system utilizes an ESP32 microcontroller, with data collected from a CJMCU-TEMT6000 light sensor and a soil moisture sensor, which is then used to control a water pump and UV LED lights via PWM. Monitoring and control can be performed directly via the Firebase platform and an Android app. Test results show that the light sensor has an average error rate of 1.83% with an accuracy of 98.15%, and the soil moisture sensor has an average error rate of 2.15% with an accuracy of 97.85%. The IoT system responds stably with a latency ranging from 3.32 to 5.03 seconds. A 5-week experiment on three plants showed that the natural environment treatment exposed to direct sunlight (Plant C) resulted in stable vegetative growth, while the terrace treatment without direct sunlight exposure (Plant B) triggered rapid but inconsistent initial growth. Meanwhile, the special treatment combining irrigation and grow lights (Plant A) proved most effective in supporting optimal fruit development compared to the other treatments.
Co-Authors Ahmad Syahruli Alamul iman Dony, Abdul Rochman Edo Agung N Edo Agung Nugroho Hidayat, Rizky Nugraha Idris, Fahmi Lutvi Aji Setiawan Muhamad Riyad Ariwibowo Muhammad Iqbal Saputra P Muhammad Miftahul Robih Muhammad Muhaimin Mutaqim, Rendi Nugroho, Edo Agung Rendi Mutaqim Rindi Wulandari