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Warohma, Ayu Mawadda
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering

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Rancangan Sistem Monitoring Greenhouse Hidroponik Berbasis IoT Hersydano, Muhammad Rayhan; Pamungkas, Syahdam Gibran; Putra, I Gusti Lanang Dwitya; Rahman, Abdul; Warohma, Ayu Mawadda
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11234

Abstract

Hydroponic methods are becoming increasingly popular as a modern agricultural solution, especially in urban areas with limited land. However, maintaining optimal environmental conditions is a major challenge in hydroponic systems. This study designs an Internet of Things (IoT)-based greenhouse monitoring system to improve the efficiency of plant monitoring and management. The system uses ESP32 microcontroller as the main controller, integrated with a DS18B20 sensor for temperature, a pH sensor, a TDS sensor for nutrient concentration, and a floater sensor to measure water level. Sensor data is transmitted in real-time via a WiFi network to a web-based monitoring platform, enabling more practical and accurate remote monitoring. The results indicate that this system can provide accurate information about plant environmental conditions and support automation in nutrient management and irrigation. Thus, this system offers an innovative solution for more efficient, controlled, and technology-based hydroponic farming.
Sistem Deteksi Masker Wajah Menggunakan CNN untuk Akses Pintu Otomatis Firizki, Muh.; Brilliant, Brian; Warohma, Ayu Mawadda
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.14413

Abstract

This research discusses the development of a face mask detection system using a Convolutional Neural Network (CNN) for automatic door access in hospitals. Considering the high risk of infectious disease transmission in hospital environments, the implementation of strict health protocols, including mandatory mask usage, is essential. Manual supervision of mask compliance has limitations; therefore, an automated system is required to improve monitoring effectiveness. The dataset used in this study was collected using an ESP32 Cam, consisting of 1,186 images of masked and unmasked faces. The CNN model achieved an average training accuracy of 96.60%, with Precision and Recall values of 0.98. The automatic door system was evaluated through real-time testing involving six subjects, each undergoing 15 trials with masks and 15 trials without masks, resulting in a total of 180 trials. The system achieved a detection accuracy of 90.00% for masked faces and 74.44% for unmasked faces, with an overall system accuracy of 82.22%. These results indicate that the proposed system is capable of reliably supporting automatic door access control based on face mask compliance in hospital environments.
Sistem Pemadam Api Berbasis Internet of Things (IoT) dengan Integrasi Aplikasi Telegram Hadji, Farid Muhammad; Daffa Putra, Muhammad Reihan; Kusuma, Rizky Ade; Warohma, Ayu Mawadda
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.14529

Abstract

Residential fires are critical incidents that often result in severe material losses and casualties due to delayed detection and manual mitigation limitations. This study aims to design an Internet of Things (IoT)-based fire extinguishing system integrated with the Telegram application. The system utilizes an ESP32 microcontroller as the main processing unit, connected to a DHT11 temperature sensor, MQ-2 smoke sensor, and Flame Sensor. The research methodology involves hardware prototyping and implementing automatic control logic. The results demonstrate that the system successfully detects fire and smoke in real-time. Specifically, the Flame Sensor showed a rapid response time of 1.15 seconds, while the MQ-2 sensor detected smoke within 3.18 seconds. Upon detecting fire, the system automatically activates a 12V mini pump via a relay to simulate fire suppression and simultaneously sends immediate alert notifications to the user's smartphone via Telegram. This integrated solution offers a reliable rapid response mechanism to minimize fire damage.
Alat Pemilah Sampah Otomatis Kategori Logam, Plastik dan Kertas Menggunakan Arduino Uno Aldi, Aldi; Warohma, Ayu Mawadda
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.15424

Abstract

The issue of waste remains a challenge due to the suboptimal sorting of waste at source, which results in the sorting process still being largely manual and inefficient. This study aims to design and implement an automatic waste sorting device capable of classifying metal, plastic, and paper waste using an Arduino Uno microcontroller. This system integrates an infrared sensor to detect the presence of waste, a capacitive proximity sensor as an initial detector, and an inductive proximity sensor for selective identification of metal waste. A servo motor is used to direct waste to the appropriate compartment, while an ultrasonic sensor monitors the capacity of the waste bin. Testing was conducted using 30 waste samples, with the system achieving an accuracy rate of 90%. These results indicate that the device operates reliably and effectively in performing automatic waste sorting.
Perancangan Sistem Pendeteksi Kebakaran Berbasis IoT Menggunakan ESP-32 Setiawan, Jimy; Warohma, Ayu Mawadda
MDP Student Conference Vol 5 No 2 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i2.15496

Abstract

Fire is a serious threat to the home environment because it has the potential to cause material losses and casualties if not detected early. This study aims to design and implement an Internet of Things (IoT)-based fire detection system using an ESP-32 microcontroller. The system utilizes a fire sensor as an input device to detect the presence of flames and send warning notifications to users via the Telegram application in real-time. The success of the system was evaluated based on three main parameters, namely sensor detection distance, notification delivery response time, and system power consumption efficiency. Test results show that the system is capable of detecting flames at an effective distance of 10–100 cm with an average notification response time of 2–3 seconds. In addition, the concept of green computing is applied through the selection of low-power devices and the activation of output components only in emergency conditions. Based on these results, this system can be used as an effective and energy-efficient early fire warning solution for the home environment.
Co-Authors Abdul Rahman Aldi, Aldi Brilliant, Brian Daffa Putra, Muhammad Reihan Firizki, Muh. Hadji, Farid Muhammad Hersydano, Muhammad Rayhan Kusuma, Rizky Ade Pamungkas, Syahdam Gibran Putra, I Gusti Lanang Dwitya Setiawan, Jimy