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All Journal Bulletin of Electrical Engineering and Informatics Journal of ICT Research and Applications JURNAL MEDIA INFORMATIKA BUDIDARMA Journal on Education Jurnal Bisnis dan Manajemen West Science Jurnal INFOTEL
Dadang Gunawan
Department Of Electrical Engineering Faculty Of Engineering, Universitas Indonesia, Depok 16424, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering

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Feasibility of LTE 700 MHz Digital Dividend for Broadband Development Acceleration in Rural Areas Denny Setiawan; Djamhari Sirat; Dadang Gunawan
Journal of ICT Research and Applications Vol. 6 No. 1 (2012)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.2012.6.1.2

Abstract

The need of broadband services to reduce digital divide in rural areas had increased in the recent years. The government of the Republic Indonesia shared similar intention and had set guidance of ICT development in its "economic master plan" and "medium term development plan". This paper addressed feasibility and suitability of its implementation in Indonesia, by conducting assessment of possible solutions. Using mixed method, the study was started with qualitative approach to identify possible options, conducted benchmarking and case study analysis to narrow down the options and finally conducted quantitative calculation for the two remaining options and measure performance of the solutions. The results of analysis concluded that early implementation of LTE in 700 MHz Digital Dividend would be feasible in certain geographical areas to fasten the broadband plan development in Indonesia.
Electrical Capacitance Volume Tomography Static Imaging by Non-Optimized Compressive Sensing Framework Nur Afny Catur Andryani; Dodi Sudiana; Dadang Gunawan
Journal of ICT Research and Applications Vol. 10 No. 3 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.3.4

Abstract

Electrical capacitance volume tomography is a volumetric tomography technique that utilizes capacitance and fringing to capture behavior or perturbation in the sensing domain. One of the crucial issues in developing ECVT technology is the reconstruction algorithm. In practice, ILBP is most used due to its simplicity. However, it still presents elongation errors for certain dielectric contrasts. The high undersampling measurement of the ECVT imaging system, which is mathematically defined as an undetermined linear system, is one of the most challenging issues. Compressive sensing (CS) is a framework that enables the recovery of a sparse signal or a signal that can be represented as sparse in a certain domain, by having a lower dimension of measurement data compared to the Shanon-Nyquist theorem. Thus, mathematically, this framework is promising for solving an undetermined linear system such as the ECVT imaging system. This paper discusses the possibility of developing an ECVT imaging technique for static objects based on a CS framework. Based on the simulation results, Non-optimized CS does not completely succeed in providing better ECVT imaging quality. However, it does provide more localized imaging compared to ILBP. In addition, by having fewer requirements for the measurement data dimension, the CS framework is promising for reducing the number of required electrodes.
Analisis Faktor Pendorong Loyalitas Pemain Game (Consumer Loyalty) Terhadap Mobile Games dengan Fokus Studi Mobile Legend Anita Rizkiyani; Prof. Dr. Ir. Dadang Gunawan, M.Eng.
Jurnal Bisnis dan Manajemen West Science Vol 2 No 1 (2023): Jurnal Bisnis dan Manajemen West Science
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (534.499 KB) | DOI: 10.58812/jbmws.v2i1.122

Abstract

Keberadaan internet menjadi hal yang penting untuk masa sekarang. Pemanfaatan internet juga semakin meluas, tak terbatas hanya memfasilitasi komunikasi dan berbagi informasi, akan tetapi internet juga banyak digunakan sebagai sarana hiburan, salah satunya untuk bermain game. Mobile Legend  menjadi salah satu   Mobile Game  berbasis kan internet dan juga memiliki pemain (pelanggan) dengan jumlah yang besar di Indonesia. Dengan jumlah pemain aktif yang tinggi, perlu untuk dianalisa mengenai loyalitas dari para pemain. Loyalitas (Customer Loyalty) ini dapat diteliti berdasarkan empat variabel utama yaitu Product Feature yang berfokus pada Gameplay dan User Interface. Lalu Price pada faktor Price on The Game dan Price of The Virtual Item. Game Designed dengan aspek Game Value, Interaction dan Community. Serta Operator Telekomunikasi dengan menganalisis faktor Infrastructure Provider, Ecosystem Development Partner dan juga Sales Partner. Analisis data untuk penelitian ini akan menggunakan SPSS edisi 25 dan AMOS. Operator Telekomunikasi hanya memberikan pengaruh akan tetapi tidak besar dan perlunya perencanaan lebih matang untuk pengembangan infrastruktur dan juga penjualan. Lain halnya dengan Product Feature, hanya sebesar 1% pengaruh yang diberikan terhadap loyalitas pemain. Serta Product Features tidak signifikan dikarenakan adanya saturasi permainan. Selain itu Price termasuk signifikan dikarenakan karena ada banyaknya interaksi yang bisa dilakukan selama bermain serta dorongan yang berasal dari komunitas-komunitas yang ada, sehingga meningkatkan loyalitas dari pemain. Game Value memiliki pengaruh terbesar dalam menjaga loyalitas pemain. Tingginya nilai yang didapatkan karena ada banyaknya interaksi yang bisa dilakukan selama bermain serta dorongan yang berasal dari komunitas-komunitas yang ada, sehingga meningkatkan loyalitas dari pemain.
Perbandingan Metode Penyesuaian Kontras Citra Pada Pengenalan Ekspresi Wajah Menggunakan Fine-Tuning AlexNet Akhmad Sarif; Dadang Gunawan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6382

Abstract

Research related to facial expression recognition (FER) has become a significant topic of interest in the field of computer vision due to its broad applications. Artificial intelligence technologies, such as deep learning, have been applied in FER research. The use of deep learning models in FER requires a dataset for training, which plays a crucial role in determining the performance of deep learning. However, the available FER datasets often require preprocessing before being processed using deep learning. In this study, a comparison of contrast adjustment preprocessing methods was conducted using Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). Subsequently, the dataset images were used with a fine-tuned deep learning model, specifically AlexNet, to classify them according to the categories of human facial expressions. The objective of this research is to determine the superior contrast adjustment method for FER dataset images in improving the performance of the deep learning model employed. The CK+ dataset (The Extended Cohn-Kanade) and KDEF dataset (The Karolinska Directed Emotional Faces) were used in this study. The results indicate that the CLAHE method outperforms HE in both the CK+ and KDEF datasets. In the CK+ dataset, the CLAHE method achieved an average accuracy of 93.21%, while the average accuracy of the HE method was 91.50%. For the KDEF dataset, the average accuracy of the CLAHE method was 88.35%, compared to 84.70% for the HE method.
Real-time stress detection and monitoring system using IoT-based physiological signals Atika Hendryani; Dadang Gunawan; Mia Rizkinia; Rinda Nur Hidayati; Frisa Yugi Hermawan
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5132

Abstract

Currently, medical experts use psychophysiological questionnaires to evaluate human stress levels during counseling or interviews. Typically, biochemical samples use urine, saliva, and blood samples to identify the effects of stress on the human body. This research explains that stress detection can be done by analyzing psychological signals and the importance of monitoring stress levels. The authors develop research on stress detection based on psychological signals. The system then processes the recorded data; the android application displays the calculation results. The database can also be accessed as a spreadsheet via a web application. The design of real-time stress detection and monitoring using internet of things (IoT) can work well.
Penyempurnaan Sistem Inkubator Bayi Berbasis FLC Menggunakan Algoritma Genetika Setiyo Budiyanto; Lukman Medriavin Silalahi; Dadang Gunawan; Erry Yulian Triblas Adesta
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.991

Abstract

This research problem focuses on treating premature babies due to hypothermia so that the baby must be put in an incubator for several days. Conventional intensive care method in premature babies, namely skin-to-skin care method between mother and child. Meanwhile, the latest technological developments, the method is already based on electrical-Internet of Things (IoT) engineering. This research proposes the design of an IoT-based prototype known as a smart incubator. This prototype has been equipped with a real-time monitoring system and system settings using the mamdani fuzzy inference system control method and combined using the Genetic Algorithm (GA) method. The results showed that the ideal temperature range in the smart incubator was 33° C with an accuracy of 99.97% and was in accordance with the fuzzy membership degree in the range of 29° C ≤x≤ 37° C. Furthermore, the ideal relative humidity range in the smart incubator was 60% with an accuracy of 98.60% and was in accordance with the fuzzy membership degree in the range of 59 ≤x≤ 65. Then, the noise range in the smart incubator is 37.9dB to 56.8dB with an accuracy of 96.44% and has been appropriate at the fuzzy membership degree. At a maximum distance of 50cm, it takes 8 seconds for the prototype to detect movement as a safety measure.
Pemanfaatan Teknologi Penginderaan dalam Penentuan Pola Sebaran Biota Laut untuk Pencegahan Ilegal Fishing pada Laut Natuna Utara Guna Mendukung Sistem Pertahanan Negara Debiyanti Debiyanti; Dadang Gunawan; Setyo Budiyanto
Journal on Education Vol 6 No 2 (2024): Journal on Education: Volume 6 Nomor 2 Tahun 2024
Publisher : Departement of Mathematics Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joe.v6i2.5257

Abstract

Indonesia is a maritime country that has a variety of marine biota, especially the North Natuna Sea. This research focuses on the utilization of sensing technology to identify marine biota distribution patterns and prevent Illegal Fishing in the North Natuna Sea. In this context, maritime security becomes a critical aspect, involving not only protection from direct threats such as piracy or smuggling, but also issues such as Illegal Fishing and marine environmental pollution. The research uses the literature study method, collecting and analyzing data from various sources. The results show the importance of integrating advanced technologies such as satellites, radars and unmanned aircraft (UAVs) in maritime surveillance systems. International collaboration, especially with platforms such as the Indo-Pacific Regional Information Sharing (IORIS) and programs such as those run by the United States Coast Guard (USCG), has also proven important in strengthening Indonesia's maritime security capacity. This research emphasizes the importance of combining military and non-military defenses with remote sensing technologies to address threats and disruptions in Indonesia's maritime region.
Co-Authors Akhmad Sarif Anita Rizkiyani Atika Hendryani Debiyanti Debiyanti Denny Setiawan Djamhari Sirat Dodi Sudiana Erry Yulian Triblas Adesta Frisa Yugi Hermawan Lukman Medriavin Silalahi Mia Rizkinia Nur Afny Catur Andryani Rinda Nur Hidayati Setiyo Budiyanto Setyo Budiyanto