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RANCANG BANGUN SPREAD SPECTRUM DENGAN METODE SINKRONISASI SERIAL CORRELATOR BERBASIS FPGA Noer Soedjarwanto; Anang Budikarso; Kukuh Setyadjit
Jurnal Teknik Ilmu dan Aplikasi Vol. 3 No. 2 (2022): Jurnal Teknik Ilmu dan Aplikasi
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Makalah ini menitik-beratkan pada pembuatan sistem sinkronisasi pada teknik pentransmisian spread spectrum asinkron. Dalam merealisasikan modul digunakan Field Programmable Gate Array ( FPGA ) Spartan II XC2S100-5 tq 144 yang terintegrasi pada Board XSA 100, implementasinya digunakan board XSA 100 dan software Xilinx ISE 6.1i. Modul terhubung secara wireline dan dirancang seperti terhubung secara wireless dimana pengaruh delay transmisi sangat besar pada proses tersebut. Dalam perancangan dan implementasi modul ini digunakan sistem Direct Sequence Spread Spectrum dan kode acak semu (pseudorandom code) maxlength dengan taping [5,2]. Pada proses transmisi antara pemancar dan penerima ditambahkan delay sebesar 1 periode chip atau sekitar 0.2 microsecond, sehingga menjadi sistem yang asinkron. Proses sinkronisasi pada penerima digunakan Serial Korelator yang terintegrasi dengan Digital Control Oscillator ( DCO ). Rangkaian ini bekerja pada proses akuisisi untuk mendapatkan timing sinyal yang benar pada proses despreading. Hasil pengujian dilakukan dan divisualisasi dengan Logic Analyser.

Pendeteksian Harmonisa Arus Berbasis Feed Forward Neural Network Secara Real Time Endro Wahjono; Dimas Okky Anggriawan; Achmad Luki Satriawan; Aji Akbar Firdaus; Eka Prasetyono; Indhana Sudiharto; Anang Tjahjono; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 16, No 1 (2020)
Publisher : Universitas Syiah Kuala

The development of power electronics converters has been widespread in the industrial, commercial, and home applications. The device is considered to produce harmonics in non-linear loads. Harmonics cause a decrease in power quality in the electric power system. To prevent a decrease in power quality caused by harmonics in the power system, the detection of harmonics has an important role. Therefore, this paper proposed feed forward neural network (FFNN) for harmonic detection. The design of harmonic detection device is designed with a feed forward neural network method that it has two stages of information processing, namely the training stage and the testing stage. FFNN has input harmonics and THDi as output. To detect harmonics, frst training is conducted to recognize waveform patterns and calculate the fast fourier transform (FFT) process ofﬂine. Prototype using the AMC1100DUB current sensor, microcontroller and display. To validate the proposed algorithm, compared by standard measurement tool and FFT. The results show the proposed algorithm has good performance with the average percentage error compared by standard measurement tool and FFT of 5.33 %.

Identification of Power Quality Disturbances Based on Fast Fourier Transform and Artificial Neural Network Dimas Okky Anggriawan; Endro Wahjono; Indhana Sudiharto; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 19, No 1 (2023)
Publisher : Universitas Syiah Kuala

This paper presents the proposed algorithms for the identification of Short Duration RMS Variations and Long Duration RMS Variations combined with harmonic. The proposed algorithms are Fast Fourier Transform (FFT) and Artificial Neural Network (ANN). The Algorithms identify nine types of Power Quality (PQ) disturbances such as normal signal, voltage sag, voltage swell, under voltage, over voltage, voltage sag combined harmonic, voltage swell combined harmonic, undervoltage combined harmonic, and over voltage combined harmonic. FFT is used to obtain the frequency spectrum of each PQ disturbance with frequency sampling of 1000 Hz, data length of 200. Output FFT is used to input data for ANN. Output ANN is a type of nine PQ disturbances. The result shows that proposed algorithms (FFT combined ANN) are effective for identification, which ANN with 20 neurons in the hidden layer has an accuracy of approximately 99.95 %

Identification of Power Quality Disturbances Based on Fast Fourier Transform and Artificial Neural Network Dimas Okky Anggriawan; Endro Wahjono; Indhana Sudiharto; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 19, No 1 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i1.27120

This paper presents the proposed algorithms for the identification of Short Duration RMS Variations and Long Duration RMS Variations combined with harmonic. The proposed algorithms are Fast Fourier Transform (FFT) and Artificial Neural Network (ANN). The Algorithms identify nine types of Power Quality (PQ) disturbances such as normal signal, voltage sag, voltage swell, under voltage, over voltage, voltage sag combined harmonic, voltage swell combined harmonic, undervoltage combined harmonic, and over voltage combined harmonic. FFT is used to obtain the frequency spectrum of each PQ disturbance with frequency sampling of 1000 Hz, data length of 200. Output FFT is used to input data for ANN. Output ANN is a type of nine PQ disturbances. The result shows that proposed algorithms (FFT combined ANN) are effective for identification, which ANN with 20 neurons in the hidden layer has an accuracy of approximately 99.95 %

Pendeteksian Harmonisa Arus Berbasis Feed Forward Neural Network Secara Real Time Endro Wahjono; Dimas Okky Anggriawan; Achmad Luki Satriawan; Aji Akbar Firdaus; Eka Prasetyono; Indhana Sudiharto; Anang Tjahjono; Anang Budikarso
Jurnal Rekayasa Elektrika Vol 16, No 1 (2020)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v16i1.15093

The development of power electronics converters has been widespread in the industrial, commercial, and home applications. The device is considered to produce harmonics in non-linear loads. Harmonics cause a decrease in power quality in the electric power system. To prevent a decrease in power quality caused by harmonics in the power system, the detection of harmonics has an important role. Therefore, this paper proposed feed forward neural network (FFNN) for harmonic detection. The design of harmonic detection device is designed with a feed forward neural network method that it has two stages of information processing, namely the training stage and the testing stage. FFNN has input harmonics and THDi as output. To detect harmonics, frst training is conducted to recognize waveform patterns and calculate the fast fourier transform (FFT) process ofﬂine. Prototype using the AMC1100DUB current sensor, microcontroller and display. To validate the proposed algorithm, compared by standard measurement tool and FFT. The results show the proposed algorithm has good performance with the average percentage error compared by standard measurement tool and FFT of 5.33 %.

IMPLEMENTASI SISTEM MONITORING PENAMPUNG AIR BERBASIS TELEGRAM DAN NODEMCU DI SEKTOR INDUSTRI UMKM Mohamad Ridwan; Ari Wijayanti; Djoko Santoso; Rahardhita Widyatra Sudibyo; Arifin Arifin; Hari Wahjuningrat Suparno; Nur Adi Siswandari; Anang Budikarso; Okkie Puspitorini; Yoedy Moegiharto; Rini Satiti; Moga Kurniajaya; Karimatun Nisa; Paramita Eka Wahyu Lestari; Via Alviana; Achmad Hildan Syahputra; Rahmadani Najwa Alfriza; Muhammad Luqmanul Chakim
BUDIMAS : JURNAL PENGABDIAN MASYARAKAT Vol 5, No 1 (2023): BUDIMAS : VOL. 5, NO.1, 2023
Publisher : LPPM ITB AAS Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/budimas.v5i1.6583

Pada zaman serba digital seperti saat ini, manusia mulai mengembangkan berbagai teknologi untuk memudahkan pekerjaan di segala bidang. Salah satu bidang yang membutuhkan inovasi akan perkembangan teknologi adalah bidang industri. Sektor industri yang masih belum menerapkan kemajuan teknologi terdapat pada industri UMKM (Usaha Mikro, Kecil, dan Menengah). Penerapan teknologi pada UMKM dapat digunakan untuk melakukan monitoring proses produksi agar dapat berjalan dengan baik. Pada pengabdian masyarakat ini akan dibuat alat untuk Implementasi Sistem Kontrol Penampung Air Berbasis Telegram dan NodeMCU. Alat tersebut menggunakan mikrokontroler NodeMCU ESP8266 yang di program menggunakan Bahasa C pada Arduino IDE dengan monitoring melalui Platform Thinger.io dan aplikasi Telegram. Sensor suhu, sensor ultrasonic, dan sensor turbidity akan mendeteksi air yang berasal dari sumber air secara real time dan akan mengirimkan data ke Thinger.io Cloud, lalu data akan dikirimkan ke Telegram. Terdapat 3 buah parameter yang akan dimonitoring yakni level air, suhu dan kekeruhan. Output dari alat tersebut juga akan ditampilkan pada LCD (Liquid Crystal Display) yang terpasang pada bak penampungan air.

Real-Time Fire Risk Assessment in Server Rooms Using Hybrid Threshold and Fuzzy Logic on Raspberry Pi Renel Cikita Robbyn; Anang Budikarso
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68129/jcsns.v1i1.37

The server room is a critical area for the storage and operation of server-related machines. In this environment, it is essential to protect data and systems from unwanted events. Significant increases in temperature or humidity can cause severe damage to equipment, system failures, and even fire risks due to sparks from transmission cables. Temperature and humidity readings with average values of 29.83°C and 45.5%, respectively, and low standard deviations, indicating reliable measurements. with an average delay of approximately 2.5 milliseconds. The system continuously monitors temperature, humidity, and flame presence to assess risk levels accurately. Threshold methods provide immediate alerts when sensor readings exceed predefined limits, while fuzzy logic enables nuanced risk classification based on combined sensor inputs. Experimental results demonstrate the system's effectiveness in early detection of hazardous conditions via visual and auditory alarms, thereby enhancing the protection of critical server infrastructure.

Performance Analysis of Full-Duplex DF Relay-Based D2D Communication with Energy Harvesting Afina Nabila Dirganingsih; Anang Budikarso; Yoedy Moegiharto; Mohammad Ridwan; Faridatun Nadziroh; Budi Aswoyo
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68129/jcsns.v1i1.41

Device-to-device (D2D) communication is a promising technology that leverages spectral efficiency and relieves network congestion in next-generation wireless systems. However, it suffers from significant performance degradation under Interference and limited transmission power and energy limitations, especially in the suburban areas with non-line-of-sight (NLOS) propagation conditions. To tackle these challenges, this paper studies a full-duplex D2D communication system with an energy-harvesting decode-and-forward (DF) relay based on the power-splitting relaying (PSR) protocol. The system model enables simultaneous information and energy transfer using radio-frequency (RF) signals as the energy source. We examine two scenarios: a relay-assisted self-interference model and a multi-node interference model. We evaluate system performance in terms of signal-to-noise ratio (SNR), throughput, and outage probability for different energy-harvesting efficiencies, power-splitting factors, and time-allocation parameters. Simulations show that system performance rises with energy-harvesting efficiency. We also identify optimal power-splitting and time-allocation values for maximum throughput. In the full-duplex DF relay system, self-interference is present at the relays, yet spectral efficiency improves. However, multiple nodes cancel each other out, causing a drop. These results help design effective, energy-efficient D2D communication systems with near-optimal performance for future wireless networks.

IoT-Based Monitoring and Control of Smoke Concentration in Fish Smoking Warehouses Using Fuzzy Logic and ESP32 Urifah Nur Rohmah; Faridatun Nadziroh; Budi Aswoyo; Anang Budikarso; Ida Anisah
Journal of Communication Systems, Networks, and Security Vol. 1 No. 1 (2026): April
Publisher : Politeknik Elektronika Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68129/jcsns.v1i1.51

Fish smoking is a common practice for preserving and flavoring fish; unfortunately, traditional methods of smoking can produce dangerous air pollutants, including carbon monoxide (CO) and nitrogen oxides (NO₂), which have severe implications for workers' health and environmental performance. In this context, we propose an Internet of Things (IoT)- based intelligent system for real-time monitoring and control of smoke levels in fish smoking warehouses. The MICS-6814 gas sensor, combined with the ESP32 microcontroller, measures CO and NO₂ levels, while a fuzzy-logic algorithm classifies air quality using the CO₂-N₂ Air Pollution Standard Index (ISPU) from the reference. The proposed approach automatically controls ventilation via a fan actuator, which is triggered when pollutant levels exceed specific thresholds. The results of the experiment show that at a distance of 40 cm, as soon as it falls, this system is determined to be an unhealthy air condition if it starts automatic ventilation. Still, at a distance of 1 m, air quality remains moderate and therefore requires no action. The system enabled real-time monitoring, classification, and control, while data visualization was handled via a web-based interface and an LCD. Power, investigations repeatedly reported that indoor air quality management in fish smoking places demonstrated its practicality in reducing health risks from smoke exposure

Solar Cell Energy Utilization Using SEPIC Converter with Fuzzy Logic Control for Electric Stove Indhana Sudiharto; Suryono Suryono; Ahmad Firyal Adila; Anang Budikarso
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.v7i2.12703

In this modern era, most household appliances require electrical energy as an energy source. The use of energy in large and sustainable amounts will cause an energy crisis. Where fossil fuels will run out and cannot be renewed. Therefore, renewable alternative energy is needed that can be used as an energy substitute for one of the solutions. One of the alternative energies is solar cell energy that to supply the energy needs of electric stoves. This study discusses photovoltaic system that use 10 solar cells each with a power of 100 WP and 90 VDC. The electrical energy generated from the solar cell is 1000 WP. From the solar cell, the voltage is increased using a Single-Ended Primary-Inductor Converter (SEPIC) converter and controlled using Fuzzy Logic Control (FLC). The output voltage is used to meet the power needs of an electric stove with a maximum power of 650 W which has an average efficiency of 93%.

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