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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Jurnal Ilmiah MITSU (Media Informasi Teknik Sipil Universitas Wiraraja) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Eksakta : Berkala Ilmiah Bidang MIPA JE-Unisla InPrime: Indonesian Journal Of Pure And Applied Mathematics Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat ELECTRA : Electrical Engineering Articles Tarbiyah Wa Ta'lim: Jurnal Penelitian Pendidikan dan Pembelajaran Jurnal Fortech Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Jurnal FORTECH
Rifky Aisyatul Faroh
Universitas Islam Lamongan
Agriculture, Biological Sciences & Forestry Humanities Astronomy 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 Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Sistem Keamanan Sepeda Motor menggunakan Modul GPS Neo-7M, Selenoid Key Berbasis ESP8266 Abdur Rohman Wakhid; Ulul Ilmi; Affan Bachri; Rifky Aisyatul Faroh; Eko Wahyu Santoso; Gilbran Bintang Erlangga
JURAL RISET RUMPUN ILMU TEKNIK Vol. 5 No. 1 (2026): April: Jurnal Riset Rumpun Ilmu Teknik
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurritek.v5i1.7432

Abstract

Motorcycle theft remains a widespread issue that demands improved security solutions supported by modern technology.This research discusses the development and implementation of a motorcycle security system design using an ESP8266 microcontroller integrated incorporating the GPS Neo-7M positioning module, SW-420 vibration detection sensor, and an electronically controlled solenoid lock. The implemented mechanism is monitored and controlled via the Telegram application, allowing the owner to receive real-time updates about the motorcycle’s status through a Telegram Bot. The development process involves hardware integration, ESP8266 programming, and functional testing. The SW-420 sensor detects vibrations as indicators of possible theft, triggering a buzzer alarm and sending instant notifications through Telegram. The GPS Neo-7M module provides location data in real time, automatically or upon user request, through a Google Maps link. Users can also lock or unlock the motorcycle remotely by sending the lock or /unlock commands via Telegram. Test results show that the system responds to vibrations in less than one second, delivers Telegram notifications within 3–5 seconds, and determines location with an accuracy of 3–10 meters. Overall, the proposed system offers an effective, practical, and low-cost solution to enhance motorcycle security.
Sistem Irigasi Sawah Berbasis Internet Of Things Memanfaatkan Energi Panas Matahari Dengan Panel Surya Alfiyan, Muhammad; Budi Laksono, Arief; Aisyatul Faroh, Rifky
Jurnal FORTECH Vol. 6 No. 2 (2025): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v6i2.6104

Abstract

The rice field irrigation system based on the Internet of Things (IoT), utilizing solar energy through photovoltaic panels, is designed to improve agricultural efficiency, particularly in automating water distribution. This system consists of a soil moisture sensor, water level sensor, 12V DC water pump, servo motor for opening the irrigation gate, and an ESP32 microcontroller connected to the Blynk application to monitor and control irrigation in real-time via smartphone. Electrical energy is supplied by solar panels and stored in batteries through a solar charge controller (SCC), allowing the system to operate independently of the main power grid. Test results show that the system can accurately read soil moisture and water level, activate the pump, and open the irrigation gate according to user commands via the Blynk app. The use of renewable energy and remote control makes this system an innovative solution to support sustainable agriculture and address water scarcity in rice fields, especially during the dry season.
Sistem Irigasi Sawah Berbasis Internet Of Things Memanfaatkan Energi Panas Matahari Dengan Panel Surya Alfiyan, Muhammad; Budi Laksono, Arief; Aisyatul Faroh, Rifky
Jurnal FORTECH Vol. 6 No. 2 (2025): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v6i2.6104

Abstract

The rice field irrigation system based on the Internet of Things (IoT), utilizing solar energy through photovoltaic panels, is designed to improve agricultural efficiency, particularly in automating water distribution. This system consists of a soil moisture sensor, water level sensor, 12V DC water pump, servo motor for opening the irrigation gate, and an ESP32 microcontroller connected to the Blynk application to monitor and control irrigation in real-time via smartphone. Electrical energy is supplied by solar panels and stored in batteries through a solar charge controller (SCC), allowing the system to operate independently of the main power grid. Test results show that the system can accurately read soil moisture and water level, activate the pump, and open the irrigation gate according to user commands via the Blynk app. The use of renewable energy and remote control makes this system an innovative solution to support sustainable agriculture and address water scarcity in rice fields, especially during the dry season.
Sea Land Segmentation of East Java’s North Coast Using Landsat 9 and ResNet50 Nafiiyah, Nur; Ilyas; Rifky Aisyatul Faroh; Salwa Nabilah; Nur Azizah Affandy
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 2 (2026): April 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i2.7435

Abstract

Coastal regions are among the most vulnerable ecosystems due to the combined impacts of natural processes and human activities. Climate change, population growth, and coastal development accelerate shoreline dynamics, increasing the need for accurate and efficient coastal monitoring. Satellite-based remote sensing, combined with deep learning techniques, provides a promising solution for large-scale and continuous shoreline analysis. This study proposes a deep learning–based approach for coastal land–sea segmentation using the ResNet50 architecture applied to Landsat 9 OLI imagery of the North Coast of East Java, Indonesia. The dataset consists of multispectral images processed into 224×224 pixel tiles, accompanied by manually generated ground truth segmentation maps. Two optimization strategies, Adam and Stochastic Gradient Descent (SGD), are evaluated to determine the most effective optimizer for improving segmentation performance. Experimental results demonstrate that the Adam optimizer outperforms SGD across multiple training epochs, achieving the highest segmentation accuracy with mean Intersection over Union (IoU) and Dice coefficient values of 0.888 and 0.934, respectively. These findings indicate that optimizer selection significantly influences the performance of ResNet50-based coastal segmentation. The proposed approach shows strong potential for supporting automated and large-scale coastal monitoring applications using medium-resolution satellite imagery.
Rancang Bangun Alat Pemantau Blind Spot Pada Kendaraan Besar Berbasis Internet Of Things (IoT) Waliudddin, Aubait; Abidin , Zainal; Aisyatul Faroh, Rifky
Jurnal FORTECH Vol. 7 No. 1 (2026): In Progress
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v7i1.7104

Abstract

Blind spot atau titik buta adalah area di sekitar kendaraan yang tidak dapat terlihat langsung oleh pengemudi, baik melalui pandangan mata maupun kaca spion. Kondisi ini terutama sering terjadi pada kendaraan berukuran besar seperti truk dan bus, dan menjadi salah satu faktor utama penyebab kecelakaan lalu lintas. Berdasarkan hal tersebut, penelitian ini dilakukan untuk merancang dan membangun alat pemantau blind spot berbasis Internet of Things (IoT) dengan tujuan meningkatkan keselamatan berkendara serta mengurangi risiko kecelakaan. Sistem ini dirancang menggunakan mikrokontroler ESP32, sensor ultrasonik HC-SR04, sensor inframerah Sharp GP2Y0A21YK0F, dan modul GPS Ublox Neo-6M untuk mendeteksi objek sekaligus melacak posisi kendaraan secara real-time. Output dari sistem ditampilkan melalui LED, buzzer, LCD, serta notifikasi aplikasi Telegram Bot. Uji coba menunjukkan bahwa sistem mampu mendeteksi objek di area blind spot dengan tingkat akurasi yang baik dan memberikan peringatan secara real-time kepada pengemudi. Dengan demikian, implementasi sistem ini diharapkan dapat membantu pengemudi kendaraan besar dalam mengantisipasi potensi bahaya akibat blind spot.
Perancangan Sistem PLTS Off-Grid Dengan Sistem ATS Berbasis Internet of Things (IoT) Abdillah, M Mursyid; Budi Laksono, Arief; Aisyatul Faroh, Rifky
Jurnal FORTECH Vol. 7 No. 1 (2026): In Progress
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v7i1.7105

Abstract

Sistem pembangkit listrik tenaga surya (PLTS) off-grid menawarkan solusi berkelanjutan untuk memenuhi kebutuhan energi rumah tangga, terutama di daerah terpencil. Penelitian ini merancang sistem PLTS off-grid dengan fitur Automatic Transfer Switch (ATS) yang memungkinkan pergantian otomatis antara sumber daya surya dan cadangan jaringan listrik konvensional. Sistem ini terintegrasi dengan teknologi Internet of Things (IoT) untuk pemantauan dan pengendalian jarak jauh melalui perangkat pintar. Perancangan melibatkan simulasi kapasitas energi surya, kebutuhan rumah tangga, serta algoritma pergantian sumber daya yang optimal. Hasil menunjukkan bahwa integrasi ATS dengan IoT meningkatkan efisiensi sistem, memastikan pasokan energi yang stabil, serta memungkinkan pengguna untuk mengoptimalkan konsumsi energi dan mengurangi biaya operasional. Desain ini mendukung transisi menuju penggunaan energi terbarukan, memberikan solusi inovatif untuk pengelolaan sumber daya energi rumah tangga secara cerdas dan berkelanjutan
Rancang Bangun Alat Pemantau Blind Spot Pada Kendaraan Besar Berbasis Internet Of Things (IoT) Waliudddin, Aubait; Abidin , Zainal; Aisyatul Faroh, Rifky
Jurnal FORTECH Vol. 7 No. 1 (2026): In Progress
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v7i1.7104

Abstract

Blind spot atau titik buta adalah area di sekitar kendaraan yang tidak dapat terlihat langsung oleh pengemudi, baik melalui pandangan mata maupun kaca spion. Kondisi ini terutama sering terjadi pada kendaraan berukuran besar seperti truk dan bus, dan menjadi salah satu faktor utama penyebab kecelakaan lalu lintas. Berdasarkan hal tersebut, penelitian ini dilakukan untuk merancang dan membangun alat pemantau blind spot berbasis Internet of Things (IoT) dengan tujuan meningkatkan keselamatan berkendara serta mengurangi risiko kecelakaan. Sistem ini dirancang menggunakan mikrokontroler ESP32, sensor ultrasonik HC-SR04, sensor inframerah Sharp GP2Y0A21YK0F, dan modul GPS Ublox Neo-6M untuk mendeteksi objek sekaligus melacak posisi kendaraan secara real-time. Output dari sistem ditampilkan melalui LED, buzzer, LCD, serta notifikasi aplikasi Telegram Bot. Uji coba menunjukkan bahwa sistem mampu mendeteksi objek di area blind spot dengan tingkat akurasi yang baik dan memberikan peringatan secara real-time kepada pengemudi. Dengan demikian, implementasi sistem ini diharapkan dapat membantu pengemudi kendaraan besar dalam mengantisipasi potensi bahaya akibat blind spot.
Perancangan Sistem PLTS Off-Grid Dengan Sistem ATS Berbasis Internet of Things (IoT) Abdillah, M Mursyid; Budi Laksono, Arief; Aisyatul Faroh, Rifky
Jurnal FORTECH Vol. 7 No. 1 (2026): In Progress
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v7i1.7105

Abstract

Sistem pembangkit listrik tenaga surya (PLTS) off-grid menawarkan solusi berkelanjutan untuk memenuhi kebutuhan energi rumah tangga, terutama di daerah terpencil. Penelitian ini merancang sistem PLTS off-grid dengan fitur Automatic Transfer Switch (ATS) yang memungkinkan pergantian otomatis antara sumber daya surya dan cadangan jaringan listrik konvensional. Sistem ini terintegrasi dengan teknologi Internet of Things (IoT) untuk pemantauan dan pengendalian jarak jauh melalui perangkat pintar. Perancangan melibatkan simulasi kapasitas energi surya, kebutuhan rumah tangga, serta algoritma pergantian sumber daya yang optimal. Hasil menunjukkan bahwa integrasi ATS dengan IoT meningkatkan efisiensi sistem, memastikan pasokan energi yang stabil, serta memungkinkan pengguna untuk mengoptimalkan konsumsi energi dan mengurangi biaya operasional. Desain ini mendukung transisi menuju penggunaan energi terbarukan, memberikan solusi inovatif untuk pengelolaan sumber daya energi rumah tangga secara cerdas dan berkelanjutan
Coastline segmentation on Landsat 8 OLI images using majority voting with deep learning models Nur Nafiiyah; Salwa Nabilah; Nur Azizah Affandy; Rifky Aisyatul Faroh; Esa Prakasa
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i2.pp588-596

Abstract

Coastlines are highly dynamic due to both natural processes and anthropogenic factors, including global warming and sea level rise. Accurate coastline segmentation is essential for effective monitoring and management. Although previous studies have applied deep learning for coastline detection, many existing models still suffer from instability across scenes, blurred boundaries, and segmentation artifacts, indicating that model generalization remains a challenge. This study aims to develop a more robust coastline segmentation approach by introducing an automated majority voting strategy that integrates three deep learning models: ResNet50, ResNet18, and MobileNet-V2. Landsat 8 OLI imagery is used for training and testing. The Jaccard index results show that ResNet18, ResNet50, and MobileNet-V2 achieved scores of 0.96, 0.98, and 0.95 respectively, while the proposed majority voting method also achieved 0.98. Despite the producing a similar numerical score to the best individual model (ResNet50), the ensemble method improves segmentation consistency by reducing artifacts such as unwanted peripheral shapes and cracks within land areas. These findings demonstrate that combining multiple segmentation outputs yields more stable and reliable coastline detection than using single models. Future work will apply this approach to broader Indonesian coastal regions to further assess its generalizability across diverse shoreline conditions.
Co-Authors Abdillah, M Mursyid Abdur Rohman Wakhid Abidin , Zainal affan Bachri Affan Bachri Alfiyan, Muhammad Amri, Sholihul Ar Rizqi, Ahmad Bustanul Ali Ayu Ismi Hanifah Bachri, Affan Budi Laksono, Arief Cahyaningtias, Sari Eko Wahyu Santoso Esa Prakasa Gilbran Bintang Erlangga Hasan Wahyudi, Muhammad Hidayat, Faruq Dwi Fahrul Ilmi, Ulul Ilyas Karimatun Nisa Laksono, Arief Budi Luki Septya Mahendra Masruroh Muhammad Mahbub Junaidi Muhammad Rudi Irawan Mukhoyyaroh, Indah Mukhoyyaroh, Nur Indah Nabilah, Salwa Nafiiyah, Nur Nisa, Tika Ziadhatin Ni’am, Wafirun Prasetyo, M. Romadhoni Eko Purnawan, Heri Resmi, Fitroh Salwa Nabilah Santoso, Eko Wahyu Saputra, M. Bayu Irwan Ulul Ilmi Utomo, Heru Prasetio Wakhid, Abdur Rohman Waliudddin, Aubait Waliuddin, Aubait Wijaya, Bara Ramadani