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Implementation of Smart Onion Counting and Environmental Sensing System with ESP32 MCU Suheta, Titiek; Suryowinoto, Andy; Uman, Novian Patria; Anam, Choirul
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 2 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i2.13020

Abstract

The rapid development of embedded system technology in recent decades has had a significant impact, this advancement has contributed to an increase in production capacity with real-time monitoring trough embedded system MCU ESP32. The process of manufacturing onion products, such as fried shallots and garlic. The objective of this research is to develop a low-cost automatic onion counting system that utilizes an embedded system MCU ESP32 with integration of infrared sensors, temperature and humidity sensors to monitor production quality conditions in real-time for small scale Industry. Using the engineering design method, where the TCRT5000 sensor is employed to detect objects based on infrared light interruption, and environmental conditions are measured with the DHT22 sensor to maintain production quality. The internet connection for wireless communication for transmitting data to a mobile device through google firebase. Analysis was performed to evaluate performance such as, data transmission response time, and environmental sensor precision. The results obtained demonstrate that the system attained counting accuracy rates of 98.2% for garlic and 98.55% for shallots. with average data transmission response times of 1.51 seconds and 1.89 seconds, respectively, achieving a success rate of 97.15%. The environmental monitoring sensors demonstrated a high degree of accuracy, with a margin of error of 0.18 °C for temperature and 0.3% for humidity. The results show that this system works effectively in automating onion counting and monitoring, with an accuracy rate of over 98% and a response time of less than 2 seconds, making it suitable for small-scale automated production.
Analisa Keandalan Sistem Jaringan Distribusi 20 KV Dan Rekonfigurasi Recloser Pada Penyulang Kamal Suheta, Titiek; Faisal A, Muhammad
Jurnal JEETech Vol. 3 No. 2 (2022): Nomor 2 November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (864.496 KB)

Abstract

The increasing population in the Kamal area has improved the demand for electrical energy needs. Consequently, disruptions to the electricity distribution network may happen, such as blackouts in certain areas. The value of the reliability index will increase and not be in accordance with the standards that have been set. For this reason, this study calculated the reliability values of SAIFI and SAIDI on the Kamal feeder using the RIA (Reliability Index Assessment) method and the recloser reconfiguration using the fuzzy logic method. The simulation results indicated that the SAIFI value gained 6.331 times/year, while SAIDI obtained 20.212 hours/year. Based on recloser reconfiguration, the SAIFI value was earned 4.926 times/year, whereas SAIDI got 15.962 hours/year. The best location was located on line nineteen in group three, producing an output value of 0.461.
Implementation of SLAM Gmapping and Extended Kalman Filter for Security Robot Navigation System Firmansyah, Riza Agung; Prabowo, Yuliyanto Agung; Suheta, Titiek; Utomo, Afri Nanda Dwi
Emitor: Jurnal Teknik Elektro Vol 24, No 2: July 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v24i2.3104

Abstract

Robot Security is a robot that is responsible for security as well as patrolling. When patrol automatically, the robot requires a navigation system. The robot also needs a mapping system that is used to make a map of the environment and as information on its location according to the map. The sensors used are wheel odometry and LiDAR. The wheel odometry system often slips which causes errors in reading the actual position of the robot. To fix this problem, a sensor fusion between the Inertial Measurement Unit (IMU) and wheel odometry is used. To combine these sensors, namely using the Extend Kalman Filter (EKF) which runs on the Robot Operating System (ROS) operating system. Mapping and navigation system testing, carried out using IMU sensors and without IMU, towards the 5 target points that have been made. In the test without IMU, the error of the robot reaching the target was (x = 45.86%, y = 54.595%, and = 56.63%). After adding the IMU sensor, the robot error has decreased to (x = 2.02%, y = 1.796%, and = 0.22%). In conclusion, the data combined from the IMU sensor and wheel odometry could minimize the existing slip errors.
Evaluasi Kualitas Gas SF6 Pada Peralatan Gas Insulated Switchgear (GIS) 150 kV Kedinding Ari Nugraha, Mochamad Bintang; Suheta, Titiek; Aditya Anggoro, Fitra
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Abstract

Pemutus Tenaga (PMT) berfungsi untuk menghubungkan dan memutuskan rangkaian listrik pada gardu induk, baik dalam kondisi berbeban maupun saat terjadi gangguan arus, sehingga diperlukan analisis umur untuk menjamin keandalannya. Penelitian ini bertujuan mengevaluasi kualitas gas SF6 dan memprediksi sisa umur PMT pada Bay Ujung dan Kenjeran dengan memanfaatkan data parameter gas serta jumlah trip periode 2020–2024. Gas SF6 memiliki peran penting sebagai media isolasi dan pemadam busur api, sehingga kualitasnya berpengaruh langsung terhadap kemampuan isolasi dan keandalan operasi. Analisis dilakukan menggunakan metode matematis dan regresi polinomial dengan acuan spesifikasi CB Merlin Gerin Tipe FG 3 yang memiliki batas operasi 2000 kali trip. Hasil pengujian gas SF6 periode 2021–2023 menunjukkan kondisi masih aman dengan purity 99,9% (>97%), moisture content maksimum 105 ppmv, dew point -41,7 °C hingga -45,4 °C, serta SO2 0 ppmv (<12 ppmv). Prediksi menunjukkan batas 2000 trip tercapai pada Bay Ujung tahun 2052 dan Bay Kenjeran tahun 2053. Kebaruan penelitian ini terletak pada evaluasi kualitas gas SF6 pada GIS 150 kV Kedinding berdasarkan data lapangan aktual yang dibandingkan dengan standar IEC dan CIGRE. Hasilnya memberikan pemetaan kondisi gas serta rekomendasi teknis pemeliharaan preventif untuk memperpanjang umur peralatan dan menjaga keandalan sistem tenaga listrik.
Analisis Dampak Operasi Pada Beban Puncak Terhadap Efisiensi Dan Penurunan Umur Transformator 60 MVA 150/20 kV Agustiawan, Saiful; Suheta, Titiek
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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Abstract

Transformator distribusi berperan penting dalam menjaga keandalan sistem tenaga listrik sehingga analisis efisiensi dan prediksi sisa umur menjadi krusial. Hasil pengukuran menunjukkan efisiensi keempat transformator berada pada kisaran 99–100%, dengan Trafo 1, 2, dan 3 relatif stabil, sedangkan Trafo 4 lebih rendah pada beberapa jam tertentu. Prediksi sisa umur menggunakan Backpropagation Neural Network (BPNN) menghasilkan akurasi 97–100% dengan MSE < 0,5. Estimasi menunjukkan Trafo 1 sekitar 15,2 tahun, Trafo 3 15,5 tahun, Trafo 4 11,2 tahun, dan Trafo 2 telah melewati umur operasi. Kebaruan penelitian ini terletak pada integrasi analisis efisiensi dan BPNN sebagai sistem monitoring prediktif yang mendukung strategi predictive maintenance untuk meningkatkan keandalan transformator.
Analisa Kondisi Dan Prediksi Umur Transformator Daya Menggunakan Metode Health Index Berbasis Artificial Neural Network (ANN) Pambudi, Wahyu Setyo; Setyawan, Wahyu; Munir, Misbahul; Suheta, Titiek; Prabowo, Yuliyanto Agung
Jurnal Teknologi Elektro Vol 17, No 1 (2026)
Publisher : Electrical Engineering, Universitas Mercu Buana

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Abstract

Transformator daya merupakan salah satu komponen utama yang mempunyai peran penting pada sistem transmisi dan distribusi listrik. Untuk beroperasi secara optimal dibutuhkan pemantauan kondisi transformator secara berkala untuk mencegah terjadinya kerusakan dan memperpanjang umur transformator daya. Salah satu metode yang digunakan untuk menilai kondisi transformator daya adalah health index, yaitu metode yang mengintegrasikan berbagai hasil pengujian, seperti dissolved gas analysis (DGA), analisis minyak transformator, dan pengujian furan, guna memberikan gambaran menyeluruh mengenai kondisi kesehatan transformator. Penelitian ini bertujuan untuk menganalisis kesehatan transformator daya berdasarkan hasil uji laboratorium ketiga parameter utama tersebut. Dengan memanfaatkan metode artificial neural network (ANN), penelitian ini juga mengevaluasi kemampuan ANN dalam memprediksi kondisi kesehatan serta umur transformator. Hasil penelitian menunjukkan bahwa metode health index berbasis ANN efektif dalam mengidentifikasi kondisi dan memprediksi umur transformator daya secara komprehensif.