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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 16 Documents
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Search results for , issue "Vol 7, No 3: Published September 2019" : 16 Documents clear
Indeks Subjeks dan Indeks Pengarang -, - INDEKS
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 3: Published September 2019
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i3.%p

Abstract

Indeks Subjeks dan Indeks Pengarang
Pengamanan Pesan pada Steganografi Citra dengan Teknik Penyisipan Spread Spectrum SAIDAH, SOFIA; IBRAHIM, NUR; WIDIANTO, MOCHAMMAD HALDI
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 3: Published September 2019
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i3.544

Abstract

ABSTRAKPada studi ini, dilakukan penggabungan metode - metode untuk memperkuat dan meningkatkan sisi keamanan proses pertukaran informasi atau pesan digital. Metode yang digunakan diantaranya adalah metode kriptografi dan metode steganografi. Implementasi pada sistem yang dibangun dilakukan dengan menyandikan pesan pada penerapan metode steganografi citra dalam menyembunyikan pesan tersandi yang dihasilkan ke dalam sebuah citra warna (RGB) dalam domain Discrete Cosine Transform dengan teknik penyisipan Spread Spectrum. Hasil penelitian menunjukan bahwa kualitas dari stego image sangat mirip dengan cover citra yang digunakan, berdasarkan perolehan nilai performansi objektif PSNR diatas 30 db dan subjektif MOS di atas nilai 4.Kata kunci: Steganografi, Discrete Cosine Transform, Spread Spectrum, PSNR, SNR ABSTRACTIn this study, a combination of methods was used to strengthen and enhance the security side of the process of exchanging information or digital messages. The methods used include cryptographic methods and steganography methods. The implementation of the system built is done by encoding the message on the application of the image steganography method in hiding the encrypted message generated into a color image (RGB) in the Discrete Cosine Transform domain with the Spread Spectrum insertion technique. The results of the study show that the quality of the stego image is very similar to the cover image used, based on the acquisition of an objective performance value of PSNR above 30 db and subjective MOS above a value of 4.Keywords: Steganografi, Discrete Cosine Transform, Spread Spectrum, PSNR, SNR
Dynamic Spatial Diversity Combiner pada Kanal Fading ARYANTA, DWI; LONDONG ALLO, RIENZY PRATAMA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 3: Published September 2019
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i3.466

Abstract

ABSTRAKKanal transmisi radio berkontribusi pada terjadinya efek fading yang dapat berpengaruh pada terjadinya penurunan kualitas sinyal pada penerima. Salah satu solusi yang digunakan untuk menekan efek fading adalah penggunaan Spatial Diversity di sisi penerima. Pada penelitian ini digunakan suatu teknik Dynamic Spatial Diversity Combining yang memadukan Selection Combining, Equal Gain Combining, dan Maximal Ratio Combining untuk mendapatkan kinerja combiner yang lebih efektif dan efisien. Simulasi dilakukan dengan menggunakan modulasi BPSK pada beberapa jenis kanal yaitu Rayleigh, Rician, Nakagami-m, Weibull, dan Suzuki. Hasil simulasi MATLAB menunjukkan bahwa secara umum kanal yang mendapatkan perbaikan kinerja penerimaan, dimana nilai terendah sebesar 2 dB terjadi pada kanal Suzuki dan tertinggi sebesar 4 dB pada kanal Weibull.Kata kunci: fading, spatial diversity, rayleigh, rician, weibull, nakagami, suzuki. ABSTRACTRadio transmission channels contribute to the occurrence of fading effects that can affect the decrease in signal quality at the receiver. One solution that is used to suppress fading effects is the use of Spatial Diversity on the receiving side. In this research, a Dynamic Spatial Diversity Combining technique is used which combines Selection Combining, Equal Gain Combining, and Maximal Ratio Combining to get a more effective and efficient combiner performance. Simulation is done using BPSK modulation on several types of canals, namely Rayleigh, Rician, Nakagamim, Weibull, and Suzuki. The MATLAB simulation results show that in general canals that get improved performance, where the lowest value of 2 dB occurs on the Suzuki channel and the highest is 4 dB on the Weibull canal.Keywords: fading, spatial diversity, rayleigh, rician, weibull, nakagami, suzuki.
Proyeksi EXIT Chart untuk Memprioritaskan Data Komunikasi Manusia pada Jaringan Super Padat NI’AMAH, KHOIRUN; LARASATI, SOLICHAH
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 3: Published September 2019
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i3.508

Abstract

ABSTRAKPenelitian ini dilakukan untuk menguji jaringan masa depan dengan melibatkan ribuan mesin. Teknik Coded Random Access (CRA) akan dijadikan bagian penting pada teknologi komunikasi seluler generasi ke-5 (5G) tahun 2020 yang diprediksi data komunikasi manusia bercampur dengan mesin. CRA pada penelitian ini dipandang sebagai skema multiple access terbaru yang memanfaatkan coding (repetition dan MDS codes), penelitian ini berdasarkan repetition codes untuk mendesain sub-optimal degree distribution pada grup manusia dan mesin. Kinerja sistem dievaluasi menggunakan parameter proyeksi Extrinstric Information Transfer (EXIT) chart, throughput, dan packet-loss rate (PLR). Sub-optimal degree distribusi untuk grup manusia ((3,1),0.3, (8,1),0.7), grup mesin ((2,1),0.6, (4,1),0.4). Throughput grup manusia tanpa fading 0,775 paket/slot dengan fading 0,736 paket/slot dan grup mesin tanpa fading 0,669 paket/slot dengan fading 0,646 paket/slot. Kontribusi penelitian ini sangat signifikan karena data pada komunikasi manusia dapat diprioritaskan yang dilihat dari kinerja deteksi paket yang diterima tanpa error (throughput) pada grup manusia lebih tinggi dibanding mesin.Kata kunci: Repetition codes , EXIT Chart, Degree Distribusi, Manusia, Mesin. ABSTRACTThis research considers future super-dense networks. Coded Random Access (CRA) technique is ecxpected to be important in fifth generation (5G) celullar communication in 2020 predicted that human data communication are mixed with machines. CRA as a new multiple accesss sheme which exploiting coding (repetition and MDS codes), this research is based on repetition codes for design sub-optimal degree distribution for human and machines groups. The performance of prioritized are evaluated based on parameters, e.g., projection Extrinsic Information (EXIT) chart, throughput, and packet-loss rate (PLR). Sub optimal degree distribution human ((3,1),0.3, (8,1),0.7), machines ((2,1),0.6, (4,1),0.4). Throughput human without fading 0,775 packet/slot with fading 0,736 packet/slot and machine without fading 0,669 packet/slot with fading 0,646 packet/slot. The contribution of this research is significant because the data on human communication can be prioritized as seen from the performance of correctly received packets (throughput) in the human group is higger than machines.Keywords: Repetition Codes, EXIT Chart, Degree Distribution, Human, Machines.
Perancangan Oxygen Analyzer Dilengkapi Penyimpanan Data Eksternal Berbasis Arduino Uno FAJRIN, HANIFAH RAHMI; ROSYADIY, TUHFA’TUN NU’MAN; SUKWONO, DJOKO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 3: Published September 2019
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i3.559

Abstract

ABSTRAKOxygen analyzer sebelumnya hanya dilengkapi dengan penyimpanan data internal dengan maksimal penyimpanan 10 data. Berdasarkan permasalahan tersebut, dibuatlah oxygen analyzer untuk mengukur kadar oksigen pada output gas medis dengan parameter kadar oksigen (%) dilengkapi dengan penyimpanan data eksternal yang bisa menyimpan banyak data untuk keperluan kalibrasi peralatan dan pengecekan kevalidan dari kadar oksigen yang diberikan ke pasien sehingga data perlu disimpan dengan baik tanpa dicatat satu persatu tapi otomatis tersimpan pada memori eksternal yang bisa dipindah ke komputer. Untuk mengukur kadar oksigen pada output gas medis digunakan sensor oksigen tipe KE-50, dan mikrokontroler Arduino Uno. Setelah pengujian data, nilai error yang didapatkan berada di bawah 1% dan penyimpanan data eksternal berfungsi dengan baik.Kata kunci: Oksigen, Sensor Oksigen, Gas Medis, penyimpanan data, arduino ABSTRACTThe previous study designed an oxygen analyzer that was only equipped with internal data storage with a maximum of 10 data storage. Therefore a tool was made to measure oxygen levels at the output of medical gas with oxygen level parameters (%) equipped with external data storage that can store a lot of data for the purposes of equipment calibration and checking the validity of the oxygen level given to the patient so that the data needs to be stored neatly without needing to be recorded one by one but automatically stored in external memory that can be moved to the computer. To measure oxygen levels at the output of medical gas used the KE-50 type of oxygen sensor, and the Arduino Uno microcontroller. After testing the data, the error values obtained are below 1% and external data storage works properly.Keywords: Oxygen, Oxygen sensor, Medical gas, data storage, arduino
Smoke and Fire Detection Base on Convolutional Neural Network WAHYUNI, ELVIRA SUKMA; HENDRI, MUHAMMAD
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 3: Published September 2019
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i3.455

Abstract

ABSTRAKDeteksi api dan asap adalah langkah pertama sebagai deteksi dini kebakaran. Deteksi dini kebakaran berdasarkan pemrosesan gambar dianggap mampu memberikan hasil yang efektif. Pilihan metode deteksi adalah kunci penting. Metode ekstraksi fitur berdasarkan analisis statistik dan analisis dinamis kadang-kadang memberikan akurasi kurang akurat dalam mendeteksi asap dan api, terutama pada deteksi asap, hal ini disebabkan oleh karakteristik objek asap yang transparan dan bergerak. Dalam penelitian ini, metode Convolutional Neural Network (CNN) diterapkan untuk deteksi asap dan api. Dari penelitian ini, diketahui bahwa CNN memberikan kinerja yang baik dalam deteksi kebakaran dan asap. Akurasi deteksi tertinggi diperoleh dengan menggunakan 144 data pelatihan, 20.000 iterasi dengan dropout.Kata kunci: Deteksi asap, deteksi kebakaran, Jaringan Syaraf Konvolusional ABSTRACTFire and smoke detection is the first step as early detection of fires. Early detection of fire based on image processing is considered capable of providing effective results. The choice of detection method is an important key. Feature extraction methods based on statistical analysis and dynamic analysis sometimes provide less accurate accuracy in detecting smoke and fire, especially on smoke detection, this is due to the characteristics of transparent and moving smoke objects. In this study, the Convolutional Neural Network (CNN) method was applied for smoke and fire detection. From this study, it is known that CNN provides good performance in fire and smoke detection. The highest detection accuracy is obtained by using 144 training data, 20,000 iterations and dropout is true.Keywords: Smoke detection, Fire detection, Convolutional Neural Network

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