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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro Teknika Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System Jurnal Pembelajaran dan Biologi Nukleus JE-Unisla INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Jurnal Teknik Elektro (JTE) Tarbiyah Wa Ta'lim: Jurnal Penelitian Pendidikan dan Pembelajaran Jurnal Pendidikan Teknik Elektro Journal of Innovative and Creativity 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 Mathematics Social Sciences Other

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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
Remaining Useful Life Estimation of Fouled HVAC Condensers via a Physics-Constrained Temporal Convolutional Network with SHAP Interpretation Dandy Risfanto Huri; Lusia Rakhmawati; Rifqi Firmansyah
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol. 9 No. 1 (2026): Februari
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajeee.v9n1.p36-40

Abstract

The condenser is one of the most fouling-prone parts of an HVAC system, and as deposits build up the compressor draws more power while efficiency falls. Predictive maintenance tries to catch this decline early, but it needs a dependable estimate of how much useful life the component has left. As a preliminary, simulation-based feasibility study, this work examines whether an explainable and physically consistent model can supply that estimate for an air-cooled condenser. Using the asymptotic Kern-Seaton model, a degradation dataset covering one complete fouling cycle (180 days sampled every minute) was generated, and from it six thermal and electrical features were derived and checked against the underlying physics. A Temporal Convolutional Network (TCN) was then trained with a physics-informed penalty that prevents the predicted life from rising over time, and SHapley Additive exPlanations (SHAP) were used to expose the reasoning behind each prediction. On a quartile-stratified test set the unconstrained TCN obtained a mean absolute error of 2.63 days and an R2 of 0.994, against 3.43 days for an LSTM baseline. Adding the physics penalty raised the error only slightly, to 2.88 days, while cutting non-monotonic predictions, a deliberate trade-off of a small amount of pointwise accuracy for physically consistent RUL trajectories. SHAP ranked the approach temperature as the most influential feature, which matches the way fouling degrades heat transfer. The predicted RUL and a derived Health Index were finally translated into a four-level maintenance decision scheme. The results indicate that the framework is promising; validation on real sensor data is the necessary next step.
Perancangan Chatbot Open-Domain Berbasis Retrieval Augmented Generation dan Large Language Model untuk Generasi Digital Afif Putra Romadhoni; Lusia Rakhmawati; I Gusti Putu Asto Buditjahjanto; Nurhayati Nurhayati
Journal of Innovative and Creativity (Joecy) Vol. 6 No. 2 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v6i2.13022

Abstract

The rapid advancement of artificial intelligence, particularly Large Language Models (LLMs), has driven the development of chatbots capable of generating more natural and interactive conversations. However, general-purpose chatbots still have limitations in providing personalized interactions that meet users' specific needs. This study aims to design and implement an open-domain chatbot based on a Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) with mood personalization and response tone features. The system was developed as a web-based application using an LLM as the response generator and a keyword-based RAG mechanism to provide additional context from a knowledge base. The novelty of this research lies in the integration of the RAG mechanism, mood personalization, response tone selection, and a safety layer within a single chatbot system designed to deliver a more personalized and secure conversational experience. System evaluation was conducted through response time testing and user acceptance testing using the Technology Acceptance Model (TAM). The results indicate that all designed features were successfully implemented and that the system was capable of generating responses across various conversational scenarios. Furthermore, the evaluation demonstrated a high level of user acceptance in terms of perceived usefulness, perceived ease of use, attitude toward using, and behavioral intention to use. Therefore, the developed chatbot was successfully implemented and can serve as a digital interaction medium that leverages LLM and RAG technologies to provide a more personalized conversational experience for users.
SMART TRAINING KIT BERBASIS INTERNET OF THINGS SEBAGAI ALAT MONITORING KEBUGARAN FISIK ATLET BOLA VOLI Renno Bagas Syahputra; Muhamad Syariffuddien Zuhrie; Lusia Rakhmawati; Agus Wiyono
Jurnal Media Elektro Vol 14 No 2 (2025): Oktober 2025
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jme.v0i0.24225

Abstract

The performance of volleyball athletes is greatly influenced by the speed and accuracy of their footwork in reaching the ball, especially during footwork training. This study aims to design a physical fitness monitoring device based on the Internet of Things (IoT) called STARK (Smart Training Kit) using the Neo M9N GNSS sensor and ESP32 microcontroller. Position coordinates, time, and speed data are collected in real-time at a sampling rate of up to 25 Hz, then stored on a MicroSD card in CSV format. The data is transmitted to the cloud via a gateway application for visualization through Google Sheets and Google Maps. Testing was conducted using a comparison method of speed and distance traveled, with the Haversine Formula as the benchmark. Test results show that higher sampling frequencies yield more detailed recorded data. The device demonstrates sufficiently stable accuracy during constant movement, though small errors increase as object speed increases. Thus, this tool can serve as an alternative for monitoring sports training and support a sports science approach through measurable and structured data.
Rancang Bangun Sistem Kontrol Suhu dan Kelembapan Berbasis IOT dengan Fuzzy Logic untuk Optimasi Proses Fermentasi pada Pengolahan Tempe Shabrina Putri Maghfira; Bambang Suprianto; Lusia Rakhmawati; Rifqi Firmansyah
JURNAL TEKNIK ELEKTRO Vol. 14 No. 3 (2025): SEPTEMBER 2025
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jte.v14n3.p257-263

Abstract

Tempe adalah makanan tradisional Indonesia bergizi tinggi yang diproduksi melalui fermentasi kedelai menggunakan jamur Rhizopus. Proses fermentasi konvensional masih bergantung pada suhu dan kelembapan lingkungan yang tidak stabil, sehingga memengaruhi kualitas dan konsistensi produksi. Untuk mengatasi hal tersebut, dikembangkan sistem inkubator cerdas berbasis Internet of Things (IoT) yang mengontrol suhu dan kelembapan secara otomatis menggunakan sensor DHT22, mikrokontroler ESP32, logika fuzzy, dan aplikasi Blynk untuk pemantauan real-time. Sistem ini dirancang menjaga suhu 30°C–35°C dan kelembapan 60%–80%, sesuai kondisi optimal fermentasi. Penelitian ini menggunakan metode rancang bangun dengan melakukan perancangan dan pengujian langsung dalam kondisi terkontrol untuk mengamati pengaruh suhu dan kelembapan terhadap kualitas tempe. Hasil pengujian menunjukkan sistem mampu menjaga kestabilan lingkungan dan menghasilkan tempe dengan tekstur dan kepadatan yang baik, sehingga mendukung efisiensi serta konsistensi produksi bagi produsen tempe skala kecil hingga menengah. Inovasi ini diharapkan dapat menjadi solusi praktis dan terjangkau untuk meningkatkan kualitas industri tempe lokal.
Optimalisasi Set Point RPM Fan ID pada Industri Semen Menggunakan Algoritma XGBoost Regressor Berbasis Parameter Operasional dan Komposisi Kimia James Tulende; Lusia rakhmawati; Bambang Suprianto
JURNAL TEKNIK ELEKTRO Vol. 15 No. 3 (2026): Vol 15 No 3 (2026): SEPTEMBER 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jte.v15n3.p185-194

Abstract

Industri semen merupakan salah satu sektor industri berenergi tinggi yang membutuhkan pengelolaan operasi efisien untuk menjaga efisiensi energi dan stabilitas proses pembakaran pada kiln. Salah satu peralatan vital dalam sistem kiln adalah Induced Draft (ID) Fan yang berfungsi mengatur tekanan negatif dan aliran gas buang selama proses pembakaran. Penentuan setpoint kecepatan putar (RPM) ID Fan yang masih dilakukan secara manual berdasarkan pengalaman operator sering kali sulit menyesuaikan fluktuasi kondisi operasional dan karakteristik bahan baku. Penelitian ini bertujuan untuk mengoptimalkan penentuan setpoint RPM ID Fan menggunakan algoritma XGBoost Regressor berbasis 20 parameter operasional kiln. Dataset historis sebanyak 2.143 observasi diproses melalui alur prapemrosesan data, seleksi variabel, serta pembagian data training dan testing dengan rasio 80:20. Kinerja model dievaluasi menggunakan Mean Absolute Error (MAE), Root Mean Square Error (RMSE), dan Koefisien Determinasi (). Hasil penelitian menunjukkan bahwa model XGBoost Regressor dengan konfigurasi estimators 100 dan learning rate 0,1 menghasilkan performa terbaik dengan nilai sebesar 96,86%, MAE sebesar 0,7068 RPM, dan RMSE sebesar 0,9546 RPM, mengungguli Regresi Linear Dasar ( = 96,34%) serta menawarkan stabilitas regularisasi yang lebih baik dibanding Random Forest Regressor ( = 97,39%). Hasil prediksi diintegrasikan ke dalam dashboard interaktif Google Looker Studio untuk memberikan visualisasi real-time yang mendukung pengambilan keputusan berbasis data (data-driven decision-making) bagi Control Room Operator (CRO) guna meningkatkan efisiensi energi listrik dan stabilitas operasi kiln. Kata kunci: industri semen, Induced Draft Fan, RPM, XGBoost Regressor, machine learning, Google Looker Studio.
Pengembangan Sistem Pompa Sump Otomatis Berbasis IoT untuk Saluran Cable Duct James Tulende; Lukman Hakim Febriansyah; Dwi Bagus Aminudin; Lusia Rakhmawati
JURNAL TEKNIK ELEKTRO Vol. 15 No. 3 (2026): Vol 15 No 3 (2026): SEPTEMBER 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jte.v15n3.p219-227

Abstract

Sump pumps play a critical role in preventing water accumulation in cable ducts at industrial facilities by automatically removing water entering the cable duct. Conventional sump pump systems generally rely on manual monitoring and have limited protection features, which may reduce operational reliability and increase the risk of pump failure. This study proposes an ESP32-based automatic sump pump monitoring and control system integrated with the Arduino IoT Cloud for real-time monitoring and remote operation. The developed system employs a float switch to detect the water level, a flow switch to verify water flow, and a Thermal Overload Relay (TOR) to protect the pump motor from overload conditions. The implemented control algorithm includes automatic pump operation, Flow Fail detection with a timeout of 10 s, Over Time protection limiting continuous operation to 300 s (5 min), automatic fault reset after 8 h for non-overload faults, and a 5 s recovery delay following overload clearance. Experimental results demonstrate that the proposed system successfully performs automatic pump control, detects abnormal operating conditions, and provides reliable fault protection. Furthermore, the integration with the Arduino IoT Cloud enables real-time monitoring of pump status, water level, flow condition, and fault information, as well as remote manual control through a wireless network. The proposed system offers a practical, low-cost, and reliable solution for improving safety, monitoring capabilities, and operational efficiency of sump pump systems for water management in industrial cable ducts.
Co-Authors ., Joko Purwanto Abdurrohman Haidar Nashiruddin Nashiruddin Achilles Jaka Dewayana Adikara AFANDI, ANAS . Afif Putra Romadhoni Agus Budi Santosa Agus Wiyono Agustin T, Rr Hapsari Peni Akbar Kurnia Saleh Alveda, Albin Ananda, Radika Pratama Bagas Arif Widodo Bambang Suprianto . Dandy Risfanto Huri Dluha, Moch. Fajrud Dwi Bagus Aminudin Endroyono, E Estia Tri Puji Pertiwi Farid Baskoro Fiqih Yerdian Alamsyah Hapsari Peni Agustin Tjahyaningtijas Hidayatullah, Muhammad Syarif I Gusti Putu Asto Buditjahjanto James Tulende James William Jokanan Kurniasyah, Ikmal Kusuma Lilik Anifah Lukman Hakim Febriansyah MACHMUD, MIFTACHUL . Meilinda Mutiara Susilo Miftahur Rohman Moch Andreyan Adi Prakoso Moh. Hanafi MUHAMAD SYARIFFUDDIEN ZUHRIE Muhammad Afifi Andriansyah Muhammad Miftahul Rizqi Mukti, Bahrul Anugrah Ningrum, L. Endah Cahya Nugroho, Yuli Sutoto Nur Kholis Nurhayati Nurhayati Nurhayati Nurhayati Praditya, Wisnu Aji Prakoso, Moch Andreyan Adi Prasetyo, Ilham Andhy Pratama, Dimas Surya Putra, Widya Permana Raden Mohamad Herdian Bhakti Rahmadianti, Ade Putri Ramadhani Arie Sadewa Setiyanto Renno Bagas Syahputra Rifqi Firmansyah Rina Harimurti Rohana, Aliffia Siski Rosi Fadila Mey Sabiliana Shabrina Putri Maghfira Subuh Isnur Haryudo SULISTIYO, EDY Suwadi Suwadi Titiek Suryani Tjahyanigtijas, Raden Roro Hapsari Peni Agustin Tjahyaningtijas, Hapsari PA Tjahyaningtijas, Raden Roro Hapsari Peni Agustin Tri Rijanto Tulende, James Unit Three Kartini WAHYULIANY, SHANDRA . WARNIATI, Ika Sudy Utami Windiasmoro, Rizki Dwi Wirawan Wirawan Wirawan, Wirawan Yudha, Irvan Yulianto, Rizki Dwi