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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Elektronika dan Telekomunikasi FIRM: Journal of Management Studies eProceedings of Engineering
Nasrullah Armi
Telkom University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences

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Impact of carrier frequency offset and in-phase and quadrature imbalance on the performance of wireless precoded orthogonal frequency division multiplexing Suyoto Suyoto; Agus Subekti; Arief Suryadi Satyawan; Nasrullah Armi; Chaeriah Bin Ali Wael; Galih Nugraha Nurkahfi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5153-5163

Abstract

Precoding in orthogonal frequency division multiplexing (OFDM) system proved to reduce the peak-to-average power ratio (PAPR), so that it improves BER. However, from the existing literature, the effect of carrier frequency offset (CFO), in-phase and quadrature (IQ) imbalance on precoded wireless OFDM systems has not been carried out. Therefore, this study evaluated the precoded OFDM (P-OFDM) system performance by considering the impact of CFO and IQ imbalance. P-OFDM performance evaluation is expressed in signal-to-interference noise ratio (SINR) and bit error rates (BER). The communication channels used are the additive white Gaussian noise (AWGN) channel and the frequency-selective Rayleigh fading (FSRF) channel, while the channel equalization process is considered perfect. The results of the analysis and simulation show that P-OFDM is greater affected by the presence of CFO and IQ imbalance than conventional OFDM system. In AWGN channel, P-OFDM experiences different SINR for each subcarrier. This is different from conventional OFDM system, where all SINRs are the same for all subcarriers. In the FSRF channel, both the POFDM system and the OFDM system experience different SINR for each subcarrier, where the SINRs fluctuation in the P-OFDM system is much larger than in the OFDM system.
Pengaruh Waktu Sensing Terhadap Kinerja Throughput Dalam Cognitive Radio Network Angga Wijaya; Fiky Yosef Suratman; Nasrullah Armi
eProceedings of Engineering Vol 3, No 1 (2016): April, 2016
Publisher : eProceedings of Engineering

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Abstract

Cognitive Radio adalah teknologi baru yang memungkinkan secondary user (unlisence) untuk menggunakan spektrum primer (license) setiap kali tersedia. Spectrum sensing dipengaruhi oleh waktu pendeteksian spektrum frekuensi primer, untuk menghindari adanya kesalahan deteksi. Pada penelitian ini dilakukan analisis kinerja deteksi pada sistem cognitive radio dengan teknologi Orthogonal Frequency Division Multiplexing (OFDM). Yang berupa, analisis Receiver Operating Characteristic (ROC), sensing time dan throughput. Deteksi dilakukan dengan teknik energy detector. Semakin besar nilai sensing time, maka semakin besar geseran pada distribusi E. Karena geseran distribusi E tersebut dapat mempermudah kerja energy detector untuk medeteksi lebih akurat. Hal ini menyebabkan probability of detection semakin besar. Penggunaan energy detector pada prakteknya kurang baik karena adanya noise power yang tidak menentu atau uncertain noise. Pada saat sensing time berdurasi 24ms, didapatkan received throughput untuk kondisi (iii) sebesar 0.4387 bits/ms, (ii) sebesar 0.2503 bits/ms dan (i) sebesar 0.1040 bits/ms. Maka, sensing time tersebut tepat digunakan untuk sistem cognitive radio dengan teknologi OFDM. Karena pada teknologi OFDM, diperlukan probability of detection (Pd) yang besar untuk meminimalisir adanya gangguan atau interferensi dari secondary user kepada primary user. Kata kunci : Cognitive Radio, OFDM, Energy Detector, Sensing time, Throughput
Simulasi Dan Analisis Jaringan Ethernet Passive Optical Network (Epon) Untuk Telkom Cipondoh Tangerang Muhammad Irfan Alghiffari; Achmad Ali Muayyadi; Nasrullah Armi
eProceedings of Engineering Vol 10, No 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstract

Robust automotive radar interference mitigation using multiplicative-adaptive filtering and Hilbert transform Asmaur Rohman, Budiman Putra; Suryadi Satyawan, Arief; Kurniawan, Dayat; Indrawijaya, Ratna; Bin Ali Wael, Chaeriah; Armi, Nasrullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp326-336

Abstract

Radar is one of the sensors that have significant attention to be implemented in an autonomous vehicle since its robustness under many possible environmental conditions such as fog, rain, and poor light. However, the implementation risks interference because of transmitting and/or receiving radar signals from/to other vehicles. This interference will increase the floor noise that can mask the target signal. This paper proposes multiplicative-adaptive filtering and Hilbert transform to mitigate the interference effect and maintain the target signal detectability. The method exploited the trade-off between the step-size and sidelobe effect on the least mean square-based adaptive filtering to improve the target detection accuracy, especially in the long-range case. The numerical analysis on the millimeter-wave frequency modulated continuous wave radar with multiple interferers concluded that the proposed method could maintain and enhance the target signal even if the target range is relatively far from the victim radar.
Random sample consensus-based room mapping using light detection and ranging Latukolan, Merlyn Inova Christie; Pramudita, Aloysius Adya; Armi, Nasrullah; Hamdani, Nizar Alam; Susilawati, Helfy; Satyawan, Arief Suryadi
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.6932

Abstract

Light detection and ranging (LiDAR) is a high-accuracy data source for geospatial providers that is displayed in two dimensions (2D) or three dimensions (3D). It is used to measure the distances or 2D or 3D maps of the environment. This study examines a random sample consensus (RANSAC)-based room mapping approach utilizing LiDAR. The RANSAC is used to achieve line fitting as a solution to acquire missing or incomplete point cloud data during the process of room scanning. The maximum x-y distance is proposed to achieve a proper model to fix the missing line during the LiDAR scanning process. Data retrieval uses ground-based LiDAR located in the middle of a certain room with the dimension of 5.76×4.95 m2. To explore a room mapping, a 2D LiDAR YDLIDAR G4 with an operating frequency of 7 Hz is used. The derived raw data is then visualized with MATLAB. The results show that the RANSAC can perform line-fitting for missing or illegible LiDAR point cloud data during the scanning process due to reflection or obstacles. The increase in the amount of data used is then directly proportional to the probability of the number of correct models.
A new approach to joint resource management in MEC-IoT based federated meta-learning Samafou, Faustin; Amine Adoum, Bakhit; Abba Ari, Ado Adamou; Marius Fidel, Faitchou; Moungache, Amir; Armi, Nasrullah; Mourad Gueroui, Abdelhakh
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7993

Abstract

MEC and IoT are rapidly expanding technologies that offer numerous opportunities to enhance efficiency and application performance. However, the huge volume of data generated by IoT devices, coupled with computational and latency constraints, poses data processing challenges. To address this within the MEC architecture, deploying computing servers at the network edge near IoT devices is a promising approach. This reduces latency and traffic load on the core network while improving the user experience. However, offloading computations task from IoT devices to MEC servers and efficiently allocating computing resources is a complex problem. IoT tasks may have specific requirements in terms of latency, bandwidth and energy efficiency, while computing resources and capacities maybe limited or shared between several users. We propose an approach called FedMeta2Ag, which we evaluate using the MNIST database. With 20 epochs, the training accuracy reached 91.5%, while the test accuracy achieved 92.0%. Performance consistently improved during the initial 20 iterations and gradually stabilized thereafter. Additionally, we compared the performance of our proposed model with existing methods, finding that our approach outperforms existing models in predicting performance more accurately. Thus, this approach effectively meets the demanding performance requirements of wireless communication systems.
Kinerja Spectrum Sensing dengan Metode Matched Filter Detector pada Radio Kognitif ANGGA, BAYU; ARYANTA, DWI; ARMI, NASRULLAH
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 1, No 1: Published January - June 2013
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v1i1.60

Abstract

ABSTRAKEvolusi sistem nirkabel dan teknologi saat ini telah membuat dampak besar pada masyarakat. Namun, disaat yang sama pengelolaan dan pemanfaatan kelangkaan spektrum tidak efisien. Radio kognitif adalah paradigma baru dalam merancang sistem komunikasi nirkabel yang bertujuan untuk meningkatkan pemanfaatan spektrum frekuensi radio (RF) dan mengurangi seminimal mungkin kelangkaan spektrum. Spectrum sensing adalah langkah utama yang akan memungkinkan jaringan radio kognitif, yaitu untuk menentukan status spektrum dan aktivitas pengguna utama secara berkala, dengan menggunakan metode matched filter detector dan energy detector sebagai pembandingnya. Hasil dari kinerja spectrum sensing berdasarkan simulasi, menunjukan kinerja matched filter detector membutuhkan SNR = 15 dB untuk mencapai probability detection (Pd) sebesar 100%, dengan probability false alarm sebesar 0,01, sedangkan energy detector hanya membutuhkan SNR = 14,2 dB. Secara keseluruhan untuk deteksi sinyal yang optimal kinerja matched filter detector tidak lebih baik dibanding kinerja energy detector.Kata kunci: spectrum sensing, radio kognitif, probability detection, matched filter detector, energy detector.ABSTRACTThe evolution of wireless systems and current technology has made a huge impact on society. However, at the same time the management and utilization of spectrum scarcity is not efficient. Cognitive Radio is a new paradigm in designing wireless communication system that aims to improve the utilization of the radio frequency spectrum (RF) and reduce to a minimum the scarcity of spectrum. Spectrum sensing is a major step that will allow the cognitive radio networks, namely to determine the status of the spectrum and activity of the primary user at regular intervals, using the method of matched filter detector and energy detector as a comparison. The results of the performance spectrum sensing based on simulations, indicates the performance matched filter detector requires SNR = 15 dB to achieve detection probability (Pd) of 100%, with a probability of false alarm of 0.01, whereas energy detector only requires SNR = 14.2 dB. As a whole for optimum signal detection performance of matched filter detector is not better than the performance of energy detector.Keywords: spectrum sensing, cognitive radio, probability detection, matched filter detector, energy detector.
Kinerja Spectrum Sensing Dengan Metode Cyclostationary Feature Detector Pada Radio Kognitif CAHYO, HENDRY; ARYANTA, DWI; ARMI, NASRULLAH
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 1, No 1: Published January - June 2013
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v1i1.26

Abstract

ABSTRAKPerkembangan dalam dunia telekomunikasi nirkabel terutama spektrum frekuensi adalah hal yang perlu mendapatkan perhatian penting. Spektrum frekuensi merupakan sumber daya yang terbatas, penggunaannya harus dilakukan secara efisien dan se-maksimal mungkin. Penelitian ini membahas teknik spectrum sensing pada radio kognitif untuk menghadapi masalah keterbatasan penggunaan spektrum frekuensi. Radio kognitif merupakan sistem radio cerdas yang bisa mengatur parameternya seperti frekuensi kerja, daya pancar, dan skema modulasi secara optimal dalam melakukan proses komunikasi. Spectrum sensing merupakan teknik untuk memaksimalkan penggunaan spektrum frekuensi. Penelitian ini membandingkan kinerja metode cyclostationary feature detection dan metode energy detection pada teknik spectrum sensing menggunakan software matlab sehingga dapat diketahui bahwa kinerja cyclostationary feature detection untuk nilai Pd = 0,85 lebih handal sebesar 0,2 untuk fungsi probability of false dan lebih handal sebesar 2 dB untuk fungsi signal to noise ratio daripada energy detection.Kata kunci: radio kognitif, spectrum sensing, cyclostationary feature detection, energy detection, probability of false alarm. ABSTRACTDevelopments in the world of wireless telecommunications specially frequency spectrum is an important thing to get attention. Frequency spectrum is afinite resource, its use must be efficiently and as maximum as possible. This study discuss the technique of spectrum sensing in cognitive radio to faces the problem using restrictiveness of frequency spectrum. Cognitive radio is a smart radio system that can adjust its parameters like work frequency, emission power, and modulation scheme are optimal in the communication process. Spectrum sensing is a technique to maximize the use of the frequency spectrum. This study compared performance of cyclostationary feature detection methodh with energy detection methodh in spectrum sensing technique using matlab software so ascertainable that cyclostationary feature detection performance for Pd value 0,85 better about 0,2 for probability of false alarm function and better about 2 dB for signal to noise ratio function than energy detection.Keywords:  cognitif radio, spectrum sensing, cyclostationary feature detection, energy detection, probability of false alarm.
Telemedicine and AI in Occupational Skin Disease Management: A Contemporary Review Purwoko, Reza Yuridian; Muliadi, Jemie; Roestam, Rusdianto; Wan Sen, Tjong Wan Sen; Pamungkas, Lukas Sangka; Nugroho, Anto Satriyo; Armi, Nasrullah; Supriyadi, Muhamad Rodhi; Melati, Rima; Alfaqih, Muhammad Subhan; Montolalu, Ivan Adrian; Ruhdiat, Rudi; Ferianasari, Inneke Winda; Aryanti, Evy Aryanti; Saputra, Silvan; Asmail, Asmail; Rahayaan, Manuela; Hi Rauf, Siti Nuraini
FIRM Journal of Management Studies Vol 8, No 2 (2023): FIRM JOURNAL OF MANAGEMENT STUDIES
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/firm.v8i2.5802

Abstract

Occupational skin diseases present significant challenges to workplace health, impacting both productivity and quality of life. The integration of telemedicine and artificial intelligence (AI) has transformed dermatological care by facilitating remote consultations, enabling early diagnosis, and supporting continuous monitoring. The COVID-19 pandemic has accelerated the adoption of digital health solutions, underscoring their potential to enhance accessibility and efficiency in occupational dermatology.AI-driven innovations, including machine learning algorithms and wearable technologies, have further improved diagnostic accuracy and patient management. However, challenges such as healthcare disparities, technological limitations, and workplace-specific factors continue to hinder widespread implementation. This review explores the evolving role of telemedicine and AI in managing occupational skin diseases, highlighting key challenges, emerging opportunities, and policy considerations for enhancing workplace health outcomes.
Sistem Pertanian Terpadu Skala Mikro Berbasis Iot Pada Ayam Petelur Alsha, Nando Irawan; Muayyadi, Achmad Ali; Armi, Nasrullah
eProceedings of Engineering Vol. 11 No. 4 (2024): Agustus 2024
Publisher : eProceedings of Engineering

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Abstract

Pertanian tradisional masih dilakukan dengan pengolahan dan pemantauan terhadap komoditas yang dibudidayakan secara manual sehingga menyebabkan kurangnya efektifitas dan efisiensi waktu dan sumber daya. Telur ayam merupakan salah satu komoditas pangan tertinggi yang banyak dikonsumsi oleh masyarakat di indonesia karena memiliki banyak manfaat bagi kesehatan dan menjadi sumber protein utama selain ikan dan daging. Dengan ini dapat dibuat sebuah sistem pertanian terpadu skala mikro berbasis IoT yang dapat meningkatkan efektifitas dan efisiensi penggunaan waktu dan sumber daya. Dalam pengelolaannya pada sektor peternakan akan dilakukan monitoring dan controlling terhadap nilai suhu pada kandang Ayam petelur. Berdasarkan hasil pengujian yang dilakukan sistem dapat menyalakan kipas pendingin secara otomatis pada saat kondisi suhu >25oC dan akan berhenti menyala pada kondisi suhu <25oC. Monitoring kondisi kadar Gas Amonia pada kandang untuk mengetahui kebersihan kondisi kandang, serta melakukan controlling pemberian pakan secara otomatis berdasarkan waktu. Melalui penggunaan IoT, sistem peternakan ini dapat memberikan informasi yang akurat secara realtime sehingga kontrol pada alat dapat bekerja sesuai dengan kondisi yang sedang terjadi. Dalam implementasinya, sistem pertanian terpadu skala mikro berbasis IoT ini juga mempertimbangkan aspek keberlanjutan. Sumber daya yang digunakan oleh salah satu sektor juga berasal dari sektor yang lain (sharing resources). Hal ini diharapkan mampu mengurangi penggunaan lahan sekaligus mengurangi penggunaan sumber daya agar efektif dan efisien. Kata kunci : Pertanian, Ayam Petelur, Telur, Suhu, Amonia, IoT.
Co-Authors Abba Ari, Ado Adamou Achmad Ali Muayyadi Adam Kusumah Firdaus Agus Subekti Agus Subekti Alfaqih, Muhammad Subhan Aloysius Adya Pramudita Alsha, Nando Irawan Amine Adoum, Bakhit Aminuddin Rizal Andri Fachrur Rozie Andria Arisal Angga Wijaya Anto Satriyo Nugroho, Anto Satriyo Arie Setiawan Arief Suryadi Satyawan Armanda, Ridho Arumjeni Mitayani Aryanti, Evy Aryanti Asih Setiarini Asmail, Asmail BAYU ANGGA, BAYU Bin Ali Wael, Chaeriah Budi Prawara Budiman Putra Asmaur Rohman Chaeriah Bin Ali Wael Chaeriah Bin Ali Wael Dayat Kurniawan Dayat Kurniawan Dayat Kurniawan Dharu Arseno DWI ARYANTA Estiningtyas, Aurellia Kartika Fajri Darwis Ferianasari, Inneke Winda Fiky Y. Suratman Galih Nugraha Nurkahfi Ghifary, Hilmi Rifa Hamdani, Nizar Alam Hana Arisesa Helfy Susilawati HENDRY CAHYO, HENDRY Hi Rauf, Siti Nuraini Indrawijaya, Ratna Isnanta, Rafif Tian Latukolan, Merlyn Inova Christie Lestari, Wina Ayu Marius Fidel, Faitchou Mochamad Mardi Martadinata Montolalu, Ivan Adrian Moungache, Amir Mourad Gueroui, Abdelhakh Muayyadi, Achmad Aly Muhamad Fauzan Muhammad Irfan Alghiffari Muliadi, Jemie Omar Saeed Al Mushayt Pamungkas, Lukas Sangka Prasetyo Putranto Purwoko, Reza Yuridian Rahayaan, Manuela Rendra Dwi Firmansyah Rico Dahlan Rima Melati Ros Sariningrum Ruhdiat, Rudi Rusdianto Roestam Salita Ulitia Prini Samafou, Faustin Saputra, Silvan Satyawan, Arief Suryadi Sopyan Setiana Sudirja Sudirja Sulaksono Priyo Sulistyaningsih Sulistyaningsih Supriyadi, Muhamad Rodhi Suryadi Satyawan, Arief Suyoto Suyoto Suyoto Suyoto Suyoto Suyoto Taufiqqurrachman Taufiqqurrachman Vita Awalia Mardiana Vita Awalia Mardiana Wajeb Gharibi Wan Sen, Tjong Wan Sen Wiko, Bimo Winy Desvasari Winy Desvasari Yulianto, Rivo Dwi