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ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika
Published by Institut Teknologi Nasional Bandung
ISSN : 23388323     EISSN : 24599638     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering Engineering
Jurnal ELKOMIKA diterbitkan 3 (tiga) kali dalam satu tahun pada bulan Januari, Mei dan September. Jurnal ini berisi tulisan yang diangkat dari hasil penelitian dan kajian analisis di bidang ilmu pengetahuan dan teknologi, khususnya pada Teknik Energi Elektrik, Teknik Telekomunikasi, dan Teknik Elektronika.
Arjuna Subject : -
Articles 826 Documents
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Kendali Aliran dan Tekanan Adaptif dengan Metode Artificial Neural Network pada Alat Terapi Oksigen SALAM, ABYANUDDIN; NUGRAHA, NUR WISMA; ALFARIDHANI, WILDAN
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 1: Published January 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i1.133

Abstract

ABSTRAKPenelitian ini bertujuan untuk merancang prototype pengendalian aliran dan tekanan adaptif pada alat terapi oksigen. Sensor yang digunakan yaitu sensor MAX30100 untuk membaca saturasi oksigen dan sensor MLX90614 sebagi sensor yang dapat menghitung Respiration Rate atau laju napas. Metode yang digunakan yaitu Artificial Neural Network yang diimplentasikan pada Raspberry Pi. Sistem akan bekerja dengan memprediksi nilai laju aliran dan tekanan oksigen yang diperlukan pasien berdasarkan nilai Respiration Rate (RR). Artificial Neural Network (ANN) dapat diimplmentasikan pada rancangan alat terapi oksigen, dengan persentase akurasi Output ANN terhadap perhitungan yaitu 99,39%, sedangkan persentase akurasi ANN terhadap pembacaan aliran oksigen yang terbaca pada sensor flow sebesar yaitu 94,73% dan persentase akurasi ANN terhadap pembacaan tekanan oksigen pada sensor pressure sebesar 89,03%.Kata kunci: Terapi Oksigen, Respiration Rate, Artificial Neural Network ABSTRACTThis research aims to design a prototype of flow and pressure control in an adaptive oxygen therapy device. The sensors used are MAX30100 sensors to read oxygen saturation and MLX90614 sensors as sensors that can calculate Respiration Rate or breath rate. The method used is Artificial Neural Network which is implemented on Raspberry Pi. The system will work by predicting the value of the flow rate and oxygen pressure required by the patient based on the Respiration Rate (RR) value. Artificial Neural Network (ANN) can be implemented in the design of oxygen therapy devices, with the percentage of ANN Output accuracy to the calculation of 99.39%, while the percentage of ANN accuracy on oxygen flow readings on the flow sensor is 94.73% and the percentage of ANN accuracy on oxygen pressure readings on the pressure sensor is 89.03%.Keywords: Oxygen Therapy, Respiration Rate, Artificial Neural Network
Estimasi SOC Saat Discharging pada Baterai VRLA Berbasis Elman Backpropagation YANARATRI, DIAH SEPTI; SUTEDJO, SUTEDJO; FIRMANSYAH, ACHMAD DICKY; IRIANTO, IRIANTO; RAKHMAWATI, RENNY; ADILA, AHMAD FIRYAL
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 4: Published October 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i4.862

Abstract

ABSTRAKPenurunan performa baterai terjadi akibat siklus pengisian dan pengosongan berulang yang melebihi batas, mempercepat degradasi. Penelitian ini bertujuan untuk meningkatkan akurasi estimasi State of Charge (SOC) baterai menggunakan Artificial Neural Network (ANN) dengan algoritma Elman Backpropagation. Metode digunakan karena menambahkan lapisan context neuron yang mampu menangkap pola dinamis pada data baterai. Pengujian dilakukan dengan membandingkan hasil estimasi SOC dari metode ini dengan metode Coulomb Counting. SOC baterai diestimasi dari 100% hingga 60%, dan hasil menunjukkan bahwa meskipun Coulomb Counting awalnya memberikan SOC lebih tinggi, estimasi dari kedua metode menjadi lebih mirip seiring waktu. Error estimasi berkisar antara 0,1% hingga 14,7%. Algoritma Elman Backpropagation terbukti mampu memberikan estimasi SOC yang lebih akurat, namun masih memerlukan kalibrasi lebih lanjut untuk meningkatkan presisi.Kata kunci: Artificial Neural Network, Baterai, Coulumb Counting, Elman Backpropagation, State of Charge. ABSTRACTThe decline in battery performance occurs due to repeated charge and discharge cycles that exceed limits, accelerating degradation. This study aimed to improve the accuracy of State of Charge (SOC) estimation using an Artificial Neural Network (ANN) with the Elman Backpropagation algorithm. The method used was unique in adding a context neuron layer capable of capturing dynamic patterns in battery data. Testing was conducted by comparing SOC estimates from this method with the Coulomb Counting method. The battery's SOC was estimated from 100% to 60%, and the results showed that although Coulomb Counting initially provided higher SOC estimates, the estimates from both methods became more similar over time. Estimation errors ranged from 0.1% to 14.7%. The Elman Backpropagation algorithm proved to provide more accurate SOC estimates, although further calibration is needed to improve precision.Keywords: Artificial Neural Network, Battery, Coulumb Counting, Elman Backpropagation, State of Charge.
Kelayakan Finansial Pembangunan Pembangkit Listrik Tenaga Hybrid Di Sanggar Kota Batu, Jawa Timur MULJANTO, WIDODO PUDJI; WIYOGA, BELDA ROSALIE PUTRI; WARTANA, I MADE; SULISTIAWATI, IRRINE BUDI
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 4: Published October 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i4.1063

Abstract

ABSTRAKIndonesia masih bergantung pada energi fosil untuk sumber pembangkit listrik. Mengingat, bahan bakar fosil terbatas, upaya melakukan peralihan ke energi terbarukan dan ramah lingkungan semakin digiatkan. Studi kasus penelitian dilakukan di Sanggar Latar di Batu dengan melakukan analisa kelayakan pembangunan Pembangkit Listrik Tenaga Phikohidro dan Pembangkit Lisrik Tenaga Surya. Analisa yang digunakan untuk melihat layak dan tidaknya proyek dengan menghitung selisih kas masuk dan keluar (NPV), tingkat pengembalian yang diharapkan dari proyek (IRR), serta total manfaat yang diperoleh beserta pengeluaran biaya yang dilakukan. Menggunakan asumsi investasi selama 25 tahun dan suku bunga 6 %, diperoleh besar selisih kas sebesar Rp 86.158.036,-, Tingkat pengembalian (IRR) 47%, dengan total manfaat sebesar (BCR) 4,10. Waktu yang dibutuhkan untuk pengembalian investasi selama 2,33 tahun artinya pembangunan pembangkit listrik tenaga hybrid dapat direalisasikan.Kata kunci: analisis investasi, kelayakan proyek, pembangkit listrik tenaga hibrid ABSTRACTIndonesia still relies on fossil energy as a power plant. Knowing that fossil fuels are limited, the efforts of new and environmentally friendly energy resources are being intensified. A case study conducted at Sanggar Latar in Batu, using the analysis of the feasability of establishing both a biomass power plant (PLTPh) and a solar power plant (PLST). The analysis that is used to the project on worthy or not with calculating differences of cash in and out (NPV), the level of returning that is hoped from the project (IRR), and the total of benefits received with the expenses that is done. Using investment assumption for 25 years and interest rate 6%, a large differences was obtained with Rp 86.158.036,-, cash, level of return (IRR) 47%, and the benefit total (BCR) 4,10. Time needed for the investment return is 2,33 years that is the development of hybrid power plant can be realized.Keywords: investment analysis, project feasibility, hybrid power plant
Komunikasi Cahaya Tampak untuk Model Sistem Pintu Otomatis Berbasis Internet of Things NATALI, YUS; R. F, NURWAN; NURHAYATI, ADE; RIZKY, M.; A, M. NABIL; M, MOSES; ROIHAN, M.; S, ALVA NURVINA; DORAND, PIETRA; SUYATNO, SUYATNO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 4: Published October 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i4.938

Abstract

ABSTRAKKomunikasi cahaya tampak (Visible Light Communication) merupakan solusi untuk komunikasi berkecepatan tinggi pada sistem berbasis Internet of Things. Model pintu otomatis berbasis IoT menggunakan komunikasi cahaya tampak berhasil dibuat untuk keamanan rumah. Komunikasi tersebut dengan panjang gelombang 650 nm berwarna merah diujicobakan untuk jarak 20 cm. Penerima fotodioda mengaktifkan motor servo untuk membuka pintu dengan maksimal sudut rotasi 120 derajat. Ada enam macam kondisi pintu terbuka yang ditampilkan di LCD dan dikirimkan melalui internet ke website. Secara keseluruhan sistem berjalan dengan baik. Komunikasi cahaya tampak juga diujicobakan sebagai sinyal pembawa dengan mendeteksi tegangan yang dikirimkan oleh laser di fotodioda. Berdasarkan ujicoba didapatkan data yang dikirimkan dapat diterima dengan baik, walaupun perubahan tegangan turun sampai dengan 1.5% di fotodioda.Kata kunci: komunikasi cahaya tampak (Visible Light Communication), Internet of Things, pintu otomatis, keamanan, sinyal pembawa ABSTRACTVisible Light Communication (VLC) is a solution for high-speed communication that can be utilized for Internet of Things (IoT) systems. An automatic door model based on IoT using VLC has been successfully assembled for user security at home. This communication, with a wavelength of 650 nm in red light, was tested for 20 cm. The photodiode receiver activates the servo motor to open the door with a maximum rotation angle of 120 degrees. The open door process consists of 6 different conditions displayed on the LCD and transmitted via the internet to the website. In a comprehensive evaluation, the system operates optimally. In addition, VLC was also tested as a carrier signal to examine the voltage sent by the laser. Based on the experiment, the data sent can still be received well, even though there is a voltage change up to 1.5% at the photodiode receiver.Keywords: Visible Light Communications (VLC), Internet of Things, automatic door, security, carrier signal
Studi Pengaruh Biomassa Bahan Bakar Jumputan Padat (BBJP) pada Proses Co-firing di PLTU ADE ARTA, MOCHAMAD ZAINUDIN; WIDAYAT, WIDAYAT; MUCHAMMAD, MUCHAMMAD
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 4: Published October 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i4.995

Abstract

ABSTRAKUntuk mereduksi emisi Gas Rumah Kaca (GRK), Pemerintah Indonesia mengajukan kebijakan untuk mengaplikasikan teknologi berbasis Energi Terbarukan (EBT) di PT PLN (Persero) dengan menerapkan co-firing di PLTU batubara. Untuk mengevaluasi karakteristik co-firing biomassa BBJP dilakukan pengujian dengan metode direct co-firing dan uji laboratorium untuk mendapatkan komposisi biomassa BBJP melalui Analisis Proksimat dan Analisis Ultimate. Hasil pengujian menunjukkan bahwa Gross Caloric Value (as received) dan Hardgrove Grindability Index (as received) biomassa BBJP 2646 Kcal/kg dan 20. Hasil uji arus pulverizer, pulverizer outlet temperature, AFR pulverizer mengalami peningkatan seiring kenaikan persentase biomassa BBJP dan sebaliknya untuk coal flow mengalami penurunan. Hasil uji Specific Fuel Consumption (SFC) co-firing biomassa BBJP 5% sebesar 0,58 dan NPHR 2.687 kcal/kWh.Kata kunci: co-firing, SFC, biomassa, pulverizer, Hardgrove Grindability Index ABSTRACTTo reduce greenhouse gas (GHG) emissions, the Government of Indonesia has proposed a policy to apply Renewable Energy-based technology (EBT) at PT PLN (Persero) by implementing co-firing in coal-fired power plants. To evaluate the co-firing characteristics of BBJP biomass, tests were conducted using the direct co-firing method and laboratory tests to obtain the composition of BBJP biomass through Proximate Analysis and Ultimate Analysis. The test results showed that the Gross Caloric Value (as received) and Hardgrove Grindability Index (as received) of BBJP biomass were 2,646 Kcal/kg and 20. The test results of pulverizer flow, pulverizer outlet temperature, AFR pulverizer increased as the percentage of BBJP biomass increased and vice versa for coal flow decreased. Specific Fuel Consumption (SFC) test results of co-firing 5% BBJP biomass amounted to 0.58 and NPHR of 2,687 kcal/kWh.Keywords: co-firing, SFC, biomass, pulverizer, Hardgrove Grindability Index
Optimasi Teknologi WAV2Vec 2.0 menggunakan Spectral Masking untuk meningkatkan Kualitas Transkripsi Teks Video bagi Tuna Rungu NOERCHOLIS, ACHMAD; DWIANDINI, TITANIA; MUKTI, FRANSISKA SISILIA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 4: Published October 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i4.877

Abstract

ABSTRAKTeknologi Automatic Speech Recognition (ASR) telah berkembang pesat sebagai alat untuk meningkatkan aksesibilitas informasi bagi penyandang tuna rungu, terutama melalui video. WAV2Vec 2.0, salah satu teknologi ASR unggulan, efektif dalam transkripsi teks, namun kinerjanya menurun saat menghadapi noise. Penelitian ini bertujuan mengoptimalkan WAV2Vec 2.0 dengan menerapkan Spectral Masking untuk mengurangi noise tanpa mengorbankan kejelasan sinyal utama. Evaluasi dilakukan pada tiga jenis video: podcast, video dengan background noise, dan video dengan background music. Hasil menunjukkan penurunan Word Error Rate (WER) yang signifikan, sebesar 78.06% pada podcast dan 53.85% pada video dengan background noise. Hasil penelitian menunjukkan bahwa Spectral Masking efektif dalam meningkatkan akurasi transkripsi, menawarkan solusi inovatif untuk aksesibilitas tuna rungu dalam kondisi audio yang kompleks.Kata kunci: noise reduction, spectral masking, tuna rungu, WAV2Vec 2.0 ABSTRACTAutomatic Speech Recognition (ASR) technology has rapidly evolved as a tool to enhance information accessibility for the hearing impaired, particularly through video content. WAV2Vec 2.0, a leading ASR technology, is effective in text transcription, but its performance degrades in the presence of noise. This study aims to optimize WAV2Vec 2.0 by applying Spectral Masking to reduce noise without compromising the clarity of the main signal. The evaluation was conducted on three types of videos: podcasts, videos with background noise, and videos with background music. The results show a significant reduction in Word Error Rate (WER), with a 78.06% decrease in podcasts and a 53.85% decrease in videos with background noise. These findings demonstrate that Spectral Masking effectively enhances transcription accuracy, offering an innovative solution for improving accessibility for the hearing impaired in complex audio conditions.Keywords: noise reduction, spectral masking, tuna rungu, WAV2Vec 2.0
Indeks Subjeks dan Indeks Pengarang -, - INDEKS
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 4: Published October 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i4.%p

Abstract

Indeks Subjeks dan Indeks Pengarang
Threshold Potential Simulation on Grounding System using CYMGround Substation Program FITRIANI, AYU; PANJAITAN, JOEL; SYAHPUTRA, SOFYAN ANWAR; PAKPAHAN, ARNOLD; SIRAIT, REGINA; HUTAJULU, ELFRIDA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.1

Abstract

Excessive fault current on a poor grounding system can cause several symptoms such as the appearance of touch and step voltage and affect the grounding resistance value. This study aims to design a grounding system with variations in the number of conductors and embedded rods where that can have a good impact on the grounding system, which can help reduce the occurrence of excessive fault currents and reduce the value of touch voltage and step voltage that appears. The research method used in this study is the Wenner Method (four-point method) where which method is used in simulating a grounding system that affects the variation in the number of conductors and embedded rods using CYMGRD (CYMGround Substation Program) software. The test results show that the maximum touch voltage value is 729.01 Volts and the maximum step voltage value is 2423.88 Volts. The simulation results state that the condition of the grounding system with variations in the number of conductors and embedded rods is stated in a safe condition.
Indeks Subjeks dan Indeks Pengarang -, - INDEKS
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 3: Published July 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i3.%p

Abstract

Indeks Subjeks dan Indeks Pengarang
Non-Contact Measurement of Infant Respiratory Rate Based on Video using Pose Estimation and Optical Flow Analysis SABILA, NURUL KHAIRA; IKHSAN, MOHAMMAD
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.29

Abstract

Non-contact respiratory rate measurement in infants presents an innovative alternative to traditional contact-based methods, which often lead to discomfort. This study aims to develop an automated approach for measuring infant respiratory rate via a non-contact method using video recordings. The method automatically detects the Region of Interest (ROI) in the infant's torso and estimates the respiratory rate using optical flow. A pose estimation model is employed to detect the ROI automatically. The method was developed and tested on the AIR-125 video dataset, which includes various lighting conditions, infant poses, and frame rates. Results demonstrate that the proposed method effectively detects the torso and provides reliable respiratory rate estimations with a mean absolute error of 3.82 BPM and Root Mean Square Error 5,01 BPM. This system offers a flexible, non-contact solution for monitoring infant respiratory rate suitable for both home and clinical settings.

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