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All Journal Teknika Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Pembelajaran dan Biologi Nukleus INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Jurnal Teknik Elektro (JTE) KREATIF: Jurnal Pengabdian Masyarakat Nusantara
Lusia Rakhmawati
Universitas Negeri Surabaya
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice

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Sistem Peringatan Dini Kecepatan Angin Menggunakan Metode Kalman Filter Berbasis SMS Estia Tri Puji Pertiwi; Lusia Rakhmawati
KREATIF: Jurnal Pengabdian Masyarakat Nusantara Vol. 5 No. 2 (2025): Jurnal Pengabdian Masyarakat Nusantara
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/kreatif.v5i2.7310

Abstract

This study presents the design and implementation of an early warning system for wind speed using the Kalman Filter method and Short Message Service (SMS) for real-time data transmission. The system is developed as a solution to the limited access to internet-based warning systems in coastal and remote areas. Wind speed is measured using a cup-type anemometer, while the DHT11 sensor monitors temperature. Data readings are processed by an Arduino Uno microcontroller and transmitted via the SIM800L GSM module in SMS format, enabling use on standard mobile devices with 2G networks. The Kalman Filter algorithm is applied to reduce noise caused by unstable wind, vegetation movement, or small animal interference. The system classifies wind speed into three levels: Safe (≤3.3 m/s), Alert (>3.3–8.1 m/s), and Danger (>8.1 m/s), with notifications via SMS and colored LED displays. Testing covered sensor accuracy, Kalman Filter performance, SMS delay, and overall system reliability. Results show measurement errors below 1% and SMS delays rated “excellent” by TIPHON standards. This system offers a reliable, low-cost solution for disaster risk reduction in internet-limited regions and can be further developed for broader early warning applications.
Prediksi Jangka Sangat Pendek Daya Keluaran PLTS Menggunakan LSTM Berbasis Sky Clearness Index Muhammad Miftahul Rizqi; Unit Three Kartini; Lusia Rakhmawati; Joko
JURNAL TEKNIK ELEKTRO Vol. 15 No. 1 (2026): JANUARI 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jte.v15n1.p38-45

Abstract

Pembangkit Listrik Tenaga Surya (PLTS) merupakan salah satu sumber energi terbarukan yang potensial di Indonesia, namun daya keluarannya sangat dipengaruhi oleh kondisi atmosfer yang bersifat fluktuatif. Penelitian ini bertujuan mengembangkan model prediksi jangka sangat pendek daya keluaran PLTS menggunakan metode Long Short-Term Memory (LSTM) berbasis Sky Clearness Index (SCI). Data penelitian berupa tegangan, arus, dan SCI dikumpulkan dari sistem PLTS Universitas Negeri Surabaya dengan interval 5 menit selama periode Mei–Juni 2025. Model LSTM dirancang dengan dua lapisan tersembunyi, Adam Optimizer, dan fungsi loss Mean Squared Error (MSE). Dataset dibagi menjadi 80% data latih dan 20% data uji. Evaluasi kinerja model dilakukan menggunakan Root Mean Square Error (RMSE), Mean Absolute Error (MAE), dan Mean Absolute Percentage Error (MAPE). Hasil penelitian menunjukkan bahwa model LSTM berbasis SCI mampu memprediksi daya keluaran PLTS dengan akurasi tinggi, dengan nilai RMSE sebesar 0,644, MAE sebesar 0,536, dan MAPE sebesar 3,66%. Nilai MAPE di bawah 10% menunjukkan performa prediksi yang sangat baik untuk peramalan jangka sangat pendek. Dengan demikian, integrasi SCI sebagai variabel input terbukti efektif dalam meningkatkan keandalan prediksi daya keluaran PLTS secara real-time.
Rancang Bangun Walking Stick sebagai Alat Bantu Penyandang Tunanetra Berbasis Internet of Things Rosi Fadila Mey Sabiliana; Lusia Rakhmawati; Bambang Suprianto; Miftahur Rohman
JURNAL TEKNIK ELEKTRO Vol. 15 No. 1 (2026): JANUARI 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jte.v15n1.p1-6

Abstract

Penelitian ini bertujuan untuk merancang dan membangun Walking Stick berbasis Internet of Things (IoT) sebagai alat bantu bagi penyandang tunanetra untuk meningkatkan keselamatan dan kemandirian dalam beraktivitas. Sistem ini menggunakan mikrokontroler ESP8266 sebagai pengendali utama, sensor ultrasonik HC-SR04 untuk mendeteksi rintangan, modul GPS Neo 6M untuk menentukan lokasi pengguna, serta modul SIM800L sebagai media komunikasi data berbasis SMS untuk mengirimkan notifikasi kondisi pengguna kepada keluarga. Pengujian dilakukan untuk mengukur kinerja deteksi rintangan, efisiensi daya, serta keandalan komunikasi data. Hasil pengujian menunjukkan tingkat keberhasilan deteksi rintangan rata-rata sebesar 92,2%, dengan waktu respon 2,12 detik dan latensi buzzer 134,1 ms. Nilai error sistem rata-rata sebesar 6,1%, menunjukkan akurasi sensor mencapai 93,9%. Efisiensi daya sistem mencapai 96,6%, dengan durasi operasi hingga 103 jam menggunakan power bank berkapasitas 20.000 mAh. Pada aspek komunikasi data, nilai rata-rata delay sebesar 2,1 detik, jitter sebesar 200 ms, dan throughput sebesar 0,6 kbps, dengan tingkat keandalan pengiriman data mencapai 97,3%. Hasil ini menunjukkan bahwa sistem bekerja dengan stabil dan efisien, serta layak digunakan sebagai alat bantu berbasis IoT bagi penyandang tunanetra.   Kata Kunci: Walking Stick, IoT, ESP8266, SIM800L, Ultrasonik, GPS, Tunanetra.
Detection of Soil Organic Matter Using IoT-Based Soil Color Sensors with Random Forest Method Muhammad Afifi Andriansyah; Lusia Rakhmawati; I Gusti Putu Asto Buditjahjanto
JURNAL PEMBELAJARAN DAN BIOLOGI NUKLEUS Vol 12, No 1: Jurnal Pembelajaran Dan Biologi Nukleus March 2026
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jpbn.v12i1.9077

Abstract

Background: Soil organic matter (SOM) is an important indicator of soil fertility that plays a role in agricultural productivity and ecosystem sustainability. However, conventional laboratory-based methods still have limitations in terms of time, cost, and do not support real-time monitoring. Therefore, an approach based on sensors and machine learning is needed for quick and efficient estimation. This study proposes an Internet of Things (IoT)-based system that integrates an RGB soil color sensor (TCS3200) and a pH sensor to estimate soil organic matter content using a Random Forest algorithm. Methodology: Laboratory analysis was conducted using the Walkley–Black method. Soil samples were taken from seven locations (T1–T7). The Random Forest model was developed with parameters n_estimators = 100 and max_depth = 10, and validated using a train-test split method (80:20). Findings: The results showed that darker-colored soils have higher organic carbon content. The model's error values indicated an MAE of 0.031 and an RMSE of 0.032. The Random Forest model achieved a classification accuracy of 85.7% and a coefficient of determination R² ≈ 0.97. Contributions: This study contributes by developing an integrated IoT and machine learning system capable of quickly, accurately, and cost-effectively estimating soil organic matter to support precision agriculture
Co-Authors ., Joko Purwanto Abdurrohman Haidar Nashiruddin Nashiruddin Achilles Jaka Dewayana Adikara AFANDI, ANAS . Akbar Kurnia Saleh Arif Widodo Bambang Suprianto . Endroyono, E Estia Tri Puji Pertiwi Farid Baskoro Fiqih Yerdian Alamsyah Hapsari Peni Agustin Tjahyaningtijas Hidayatullah, Muhammad Syarif I Gusti Putu Asto Buditjahjanto James William Jokanan Lilik Anifah MACHMUD, MIFTACHUL . Miftahur Rohman Moch Andreyan Adi Prakoso Moh. Hanafi Muhammad Afifi Andriansyah Muhammad Miftahul Rizqi Nur Kholis Nurhayati Nurhayati Putra, Widya Permana Ramadhani Arie Sadewa Setiyanto Rosi Fadila Mey Sabiliana Suwadi Suwadi Titiek Suryani Tjahyaningtijas, Hapsari PA Unit Three Kartini WAHYULIANY, SHANDRA . Wirawan Wirawan Wirawan, Wirawan