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All Journal ELKHA : Jurnal Teknik Elektro REKAYASA e-Jurnal Arus Elektro Indonesia CYCLOTRON Jurnal Sistem Cerdas Jurnal Pengabdian Masyarakat Fakultas Teknik: Jurnal Abditek
Hasanur Mohammad Firdausi
Department Of Electrical Engineering, Jember University, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Physics

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Penerapan Jaringan Syaraf Tiruan Backpropagation untuk Smart Control Early Warning System (EWS) Gamma Aditya Rahardi
CYCLOTRON Vol 6 No 1 (2023): CYCLOTRON
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/cl.v6i1.16741

Abstract

Frekuensi angin puting beliung yang terjadi di beberapa wilayah di Kabupaten Jember menunjukkan bahwa Kabupaten Jember merupakan daerah yang rawan dengan bahaya angin puting beliung. Oleh karena itu, diperlukan sistem peringatan dini untuk menanggulangi bencana sehingga antisipasi warga dalam menghadapi bencana akan meningkat. Pada penelitian ini ditujukan untuk menghasilkan sensor DHT22 dan sensor anemometer dengan metode Jaringan Syaraf Tiruan Backpropagation yang dapat memberikan peringatan angin puting beliung sejak dini kepada masyarakat. Penerapan Jaringan Syaraf Tiruan Backpropagation digunakan untuk peramalan angin puting beliung dengan algoritma Levenberg-Marquardt. Hasil dari pembelajaran dengan menggunakan algoritma Levenberg-Marquardt didapatkan hasil terbaik Mean Squence Error (MSE) sebesar 3,6588 × 10-7 dengan rata-rata error dari setiap data pembelajaran sebesar ±2,61%.
Smart Camera for Volcano Eruption Early Warning System Based on Faster R-CNN and YOLO Firdausi, Hasanur Mohammad; Utomo, Satryo Budi; Widjonarko, Widjonarko
Rekayasa Vol 18, No 1: April 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i1.27372

Abstract

This research uses two object detection algorithms, Faster R-CNN with ResNet50 backbone and YOLOv5, to develop an intelligent camera system for monitoring volcanic activities. The models were trained and evaluated using CCTV footage from Mount Semeru, a region prone to volcanic eruptions. Key performance metrics such as Precision, Recall, and mean Average Precision (mAP) were used to evaluate the performance of both models. The high precision numbers for YOLOv5 and Faster R-CNN show they are good at avoiding false positives, which is essential for volcanic monitoring. YOLOv5 has a precision of 83.2%, while Faster R-CNN is 84%. However, recall shows a more significant difference between the two models. Faster R-CNN has a recall of 82%, meaning it is better at detecting all relevant volcanic activities, even if that means catching a few false positives. The variations in performance can be attributed to their respective designs. YOLOv5 is designed to achieve rapid, real-time detection by simultaneously predicting bounding boxes and class probabilities. This approach enhances speed but may slightly reduce recall.  Faster R-CNN uses a two-stage process, tending to be more accurate but can be slower and less flexible across different IoU thresholds. Its higher recall means it catches more objects, contributing to its lower mAP@50-95 since it could struggle with overlapping or varying-sized objects.
Optimization of Milk Pasteurization Process Using PID Control System Firdausi, Hasanur Mohammad; Cahyono, Yusuf Fani Dwi; Rahardi, Gamma Aditya; Ghozali, Moch; Muldayani, Wahyu; Herdiyanto, Dedy Wahyu
Jurnal Arus Elektro Indonesia Vol. 11 No. 2 (2025)
Publisher : Fakultas Teknik, Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jaei.v11i2.53734

Abstract

Livestock products that experience an increase in production every year are dairy products. Based on research data on national milk production in 2020, the amount of dairy products produced increased to 947,685.36 tons. Animal protein needed by the body to grow and develop and to maintain health is the source of milk. The dairy processing industry relies on fresh cow's milk. Milk needs to be further processed to extend its shelf life because milk is easily spoiled or damaged and has a relatively short shelf life as a food of animal origin. Pasteurization is a process that can be done. One effort to extend the shelf life of milk is by pasteurizing milk. The pasteurization process is carried out by heating milk at a temperature of LTLT 62°C-66°C for 30 minutes or HTST temperature of 72°C -75°C for 15 seconds. This study uses the LTLT method with a temperature of 63°C to maintain the temperature using the 2nd 2nd-orderer Nichols PID control. To apply the system, several components are used, namely, Arduino nano as a microcontroller, DS18B20 sensor as a milk temperature reader, as well as a feedback system from PID control, servo to regulate the valve used to regulate the intensity of the stove flame, and the servo, rotates according to the PID value received, MQ-02 sensor to maintain safety against LPG gas leaks. There is a 12C LCD to provide visual information on the temperature and ADC values from the MQ-02 sensor, and there is a buzzer as an indicator of the system. The buzzer will be ON when the pasteurization process time is complete and when a gas leak occurs. Then, there is a TCS3200 sensor that compares the colour of the milk.
Design and Construction of a 3-Phase Axial Type BLDC Generator for Wind Power Generator Hadi, Widyono; Rahardi, Gamma Aditya; Fathoni, Ahmad Nur; Pratama, Muhammad Rizal; Firdausi, Hasanur Mohammad
ELKHA : Jurnal Teknik Elektro Vol. 16 No.1 April 2024
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v16i1.75626

Abstract

The need for electrical energy in remote areas to improve community welfare must be a concern for universities. The government's ability to build new electricity sources is very minimal because it requires large infrastructure and costs, but the government continues to strive to develop new power plants. Therefore, it is necessary to strive for innovation to build power plants from renewable energy sources. There is a need to use renewable energy as an alternative to replace electrical energy which is increasingly in crisis. One alternative energy that is easy to make is energy that uses magnetic force as a model for generating electricity. Brushless Direct Current (BLDC) motors are an alternative to current DC motors. This three-phase permanent magnet axial flux generator is specially designed for vertical-type wind turbines. This generator consists of two stators and one rotor. where each stator consists of 9 coils and the magnet used is a neodymium permanent magnet. Based on test results, this generator can produce a voltage of 12.57 VDC with a wind speed of 6.84 m/s. So, it can turn on DC lights and charge DC batteries. This three-phase axial BLDC generator was tested in 3 stages, namely without load, using battery load, and DC-light load with wind conditions depending on natural conditions.
Penerapan Sistem Deteksi Angin Puting Beliung Berbasis Fuzzy logic dan SMS Gateway untuk Peningkatan Kesiapsiagaan Masyarakat Firdausi, Hasanur Mohammad; Mubarok, Imam Anas; Faqih, Achmad; Taufik, Moh; Rahardi, Gamma Aditya
Jurnal Pengabdian Masyarakat Fakultas Teknik : Jurnal Abditek Vol. 5 No. 02 (2025): Jurnal Pengabdian Masyarakat Fakultas Teknik : Jurnal Abditek
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/Abditek.052.05

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk menerapkan sistem deteksi dini angin puting beliung berbasis fuzzy logic dengan sensor DHT22 dan anemometer yang dilengkapi SMS Gateway sebagai media peringatan dini. Sistem ini sebelumnya dikembangkan dalam penelitian dengan hasil akurasi yang baik, kemudian diimplementasikan pada masyarakat sebagai bagian dari peningkatan kesiapsiagaan bencana. Metode kegiatan meliputi sosialisasi, instalasi perangkat, pelatihan masyarakat, serta evaluasi respon warga terhadap pesan peringatan dini yang diterima melalui SMS dengan kategori “Waspada”, dan “Siaga”. Hasil kegiatan menunjukkan bahwa masyarakat mampu memahami pesan peringatan dan mengambil langkah mitigasi sederhana sesuai tingkat bahaya. Implementasi teknologi ini berhasil meningkatkan kesadaran masyarakat akan pentingnya kesiapsiagaan menghadapi bencana puting beliung.
A Multivariate LSTM Approach for Monthly Rice Production Forecasting in East Java Firdausi, Hasanur Mohammad; Utomo, Satryo Budi; Rahardi, Gamma Aditya; Prasetiyo, Dani Hari Tunggal
Jurnal Sistem Cerdas Vol. 8 No. 3 (2025): In progress (December)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i3.595

Abstract

Accurate forecasting of rice output is essential for improving regional food security planning, particularly in East Java Province, which serves as a major national rice granary. This study develops a Long Short-Term Memory (LSTM) model to predict rice production using monthly data on production and harvested area from 2018 to 2024. The methodology includes data preprocessing, normalization, sequence construction with a sliding window, training of a multivariate LSTM model, and performance evaluation using mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE). Results show that the LSTM model achieves superior predictive accuracy, with an MAE of 95,030.16, RMSE of 120,229.01, and MAPE of 16.64%, significantly outperforming baseline Moving Average and Linear Regression models. While the model effectively captures seasonal production trends, some inaccuracies remain during periods of anomalous production values. These findings suggest that the LSTM model is effective for projecting rice production and may provide a foundation for early warning systems and regional food distribution strategies. Further improvements could be realized by integrating climate variables or adopting a hybrid model architecture to enhance predictive precision.
Co-Authors Achmad Faqih Cahyono, Yusuf Fani Dwi Dani Hari Tunggal Prasetiyo Dedy Wahyu Herdiyanto Dodi Setiabudi Fathoni, Ahmad Nur GAMMA ADITYA RAHARDI Ghozali, Moch Immawan Wicaksono Mubarok, Imam Anas Pratama, Muhammad Rizal Satryo Budi Utomo Taufik, Moh Wahyu Muldayani Widjonarko . Widyono Hadi