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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 29, No 3: March 2023" : 64 Documents clear
Microstrip patch antennas for various applications: a review Md. Sohel Rana; Sifat Hossain; Shuvashis Biswas Rana; Md. Mostafizur Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1511-1519

Abstract

This paper aims to review microstrip antennas for various applications. The design of microstrip patch antennas is a new research field developed for use in 5th generation communication applications. An antenna is a collection of multiple devices connected together that function as a single antenna to send or receive radio waves. Antennas can be of different shapes and sizes. The microstrip patch is an antenna pattern that is light in weight, low profile, and focuses on producing results. In the future, microstrip patch antennas may be used for some 6G communication systems applications. In addition, 6G communication applications can be created on other devices, including biomedical, autonomous vehicles, vehicle-to-vehicle (V2V) communication, internet of things (IoT), machine learning, Artificial Neural Network Algorithms, radar, and wireless communication. In the past, the multiple input, multiple output (MIMO) pattern was a standard geometry used in 4G wireless applications. This paper discusses the geometric structures of antennas, various analysis methods for antenna characteristics, antenna dimensions, and many different types of antennas. Also, it will discuss the previous papers' substrate materials, loss tangent, thickness, return loss, bandwidth, voltage-standing-wave-ratio (VSWR), gain, and directivity.
Fuzzy logic system for drug storage based on the internet of things: a survey Shivan Mohammed Othman; Maiwan Bahjat Abdulrazzaq
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1382-1392

Abstract

The rapid development of internet of things (IoT) technology over the course of recent history has made it possible to connect a large number of smart things and sensors, as well as to establish an environment in which data can be seamlessly exchanged between them. This has led to an increase in the demand for data analysis and storage platforms such as cloud computing and fog computing. One of the application areas for the internet of things that has garnered a lot of interest from the business world, academic institutions, and the government is healthcare. The IoT and fuzzy logic are being used in the medical business to improve patient safety, the overall quality of care, and the overall efficiency of medical operations. The most important healthcare studies that are pertinent to pharmacies have been used as the basis for this research. The purpose of this research is to investigate recent advancements in medical modules, remotes, and detector patterns, as well as current innovations in IoT and fuzzy logic-based health care, and current policies from around the world, with the intention of determining how well they support the long-term growth of IoT and fuzzy logic in healthcare.
Design of novel high speed parallel prefix adder Deepak Kumar Athur; Bhuvanesh Narayanan; Amshuman Gopalakrishnan; Sasipriya Palanisamy; Anita Angeline Augustine
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1345-1354

Abstract

Adders are crucial logical building blocks found almost in all the modern electronic system designs. In the adder architecture design, the fundamental issue is the propagation latency in the carry chain. As the length of the input operands increases, the length of the carry chain along with it. Parallel prefix adders, which address the problem of carry propagation in adders, are the most efficient adder topologies for hardware implementation. However, delay reduction still could be achieved for very high speed applications. Hence, in this paper design of 16bit novel parallel prefix adder is proposed and compared against the existing parallel prefix adder architectures. The design and simulation are carried out using xilinx vivado for field- programmable gate array (FPGA) simulation and Cadence® for ASIC. The results of ASIC implementation demonstrate 17.8% delay reduction while compared to sparse kogge-stone adder.
Performance improvement of dye-sensitized solar cells by using natural chlorophyll and anthocyanin dyes Miladina Rizka Aziza; Eka Maulana; Panca Mudjirahardjo; Jumiadi Jumiadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1290-1299

Abstract

Natural dye-sensitized solar cells (DSSC) have gained so much attention in recent years due to its low-cost fabrication process, ease of fabrication, and environmentally friendly. In order to improve the DSSC performance, the absorbance spectral of dyes must reach the maximum visible spectrum values. The combination of two dyes with different absorbance spectra can be utilized to expand the absorbance spectral. Here, we demonstrated the combination of natural chlorophyll and anthocyanin dyes from cassava leaves and black sticky rice, respectively, to enhance the DSSC performance. Our findings provide insights for increasing the DSSC performance by varying the combination of natural dyes. The highest efficiency was obtained from Chlorophyll:Anthocyanin 3:1.
Utilizing the power controller, enhance the operation of a single-phase AC to DC converter Raghad Hameed Ahmed; Mohammed Taha Yunis; Basima Taresh Dawood
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1224-1232

Abstract

Smooth switching technology with a single-phase converter from AC to DC is existing in this work. A study of implementing a buck-batch converter was explored and the implementation details assessed. The system explaining the versatile balanced power control (VPBC) has advantages, the suggested boost buck processor is charged during the downtime; the voltage is relieved via the MOSFET switch. It has enhanced the power factor to 0.9715 at full load in further development. The advanced model of the AC to DC converter design will maintain stability and its reliability will depend on the average “charge” and “discharge” with the help of the VPBC-controlled current of the inductor, compensate automatically. Because of this process, a linear construction between line current and voltage is achieved by running normal work at regular intervals. As a result, they almost realized the PF at the input source. The output voltage of the planned for any load condition in the transformer model is always constant (0-1,000) watts. Suggested circuit has a great dynamic reaction.  Suggested PFC circuit is usable for a range of loads. From the simulation, the efficiency of the suggested transformer is 91.11% upper at the rated load. Designed by MATLAB.
Optimization artificial neural network classification analysis model diagnosis Gingivitis disease Vicky Ariandi; Musli Yanto; Annisak Izzaty Jamhur; Firdaus Firdaus; Riandana Afira
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1648-1656

Abstract

Gingivitis is a disease that can be caused by the buildup of bacteria and plaque caused by leftover food. This disease can attack anyone, especially children who are not aware of maintaining dental and oral health. This study aims to build and optimize the classification analysis model for the diagnosis of Gingivitis. The classification analysis model was built using the artificial neural network (ANN) method which was optimized using fuzzy logic and the multiple linear regression (MRL) method. Optimization with fuzzy aims to develop a pattern of rules in the detection. The MRL method is also used as a process of measuring analysis patterns to ensure the analytical model presents maximum results. The results study indicate that the optimization of fuzzy and MRL methods provides excellent output. These results are based on the fuzzy output which can provide a pattern of 40 rules. The MRL method is can present the level of correlation of each analysis variable with a significant output having an average value of 94.2%. Based on the results of this study, the analysis model that is optimized with the fuzzy logic method and MRL contributes to maximizing the process of diagnosing Gingivitis.
PI controller for photovoltaic-fed novel multilevel inverter topologies Dhandapani Karthikeyan; Simran Rajiv Khiani; Albert Alice Hepzibah; Uthayakumar Jothilingam; Ravindran Ramkumar; Arumbu Venkadasamy Prathaban; Krishnasamy Vijayakumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1268-1280

Abstract

This research describes the analysis and design of a unique 7-level and 9-level multi-level inverter topology with fewer DC power supplies and power switches, and a comparison using pulse width modulation (PWM). Comparisons of 7-level and 9-level multi-level inverters that analyze characteristics using optimal nearest level modulation (ONLM) technology are made using various PWM approaches such as nearest level modulation (NLM) technique, phase disposition (PD), phase opposition disposition (POD), and alternate phase opposition disposition (APOD). The output is evaluated based on a high Vrms, low total harmonic distortion (THD) harmonic profile. The controller is based on artificial intelligence (AI) and machine learning (ML) techniques. ONLM techniques are used to measure the voltage harmonics of the full load, several DC offset values are used. The control technology provided is validated using MATLAB/Simulink simulation tools and laboratory-based experimental testing.
Machine learning prediction of video-based learning with technology acceptance model Rahayu Abdul Rahman; Suraya Masrom; Nor Hafiza Abd Samad; Rulfah M. Daud; Evi Meutia
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1560-1566

Abstract

COVID-19 outbreak has significant impacts on education system as almost all countries shift to new way of teaching and learning; online learning. In this new environment, various innovative teaching methods have been created to deliver educational material in ensuring the learning outcomes such as video content. Thus, this research aims to implement machine learning prediction models for video-based learning in higher education institutions. Using survey data from 103 final year accounting students at Malaysian public university, this paper presents the fundamental frameworks of evaluating three machine learning models namely generalized linear model, random forest and decision tree. Besides demography attributes, the performance of each machine learning algorithm on the video-based learning usage has been observed based on the attributes of technology acceptance model namely perceived ease of use, perceived usefulness and attitude. The findings revealed that the perceived ease of use has given the highest weight of contributions to the generalized linear model and random forest while the major effects in decision tree has been given by the attitude variable. However, generalized linear model outperformed the two algorithms in term of the prediction accuracy.
Text prediction recurrent neural networks using long short-term memory-dropout Orlando Iparraguirre-Villanueva; Victor Guevara-Ponce; Daniel Ruiz-Alvarado; Saul Beltozar-Clemente; Fernando Sierra-Liñan; Joselyn Zapata-Paulini; Michael Cabanillas-Carbonell
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1758-1768

Abstract

Unit short-term memory (LSTM) is a type of recurrent neural network (RNN) whose sequence-based models are being used in text generation and/or prediction tasks, question answering, and classification systems due to their ability to learn long-term dependencies. The present research integrates the LSTM network and dropout technique to generate a text from a corpus as input, a model is developed to find the best way to extract the words from the context. For training the model, the poem "La Ciudad y los perros" which is composed of 128,600 words is used as input data. The poem was divided into two data sets, 38.88% for training and the remaining 61.12% for testing the model. The proposed model was tested in two variants: word importance and context. The results were evaluated in terms of the semantic proximity of the generated text to the given context.
Improved services traceability and management of a food value chain using block-chain network: a case of Nigeria Maureen Ifeanyi Akazue; Rume Elizabeth Yoro; Bridget Ogheneovo Malasowe; Obinna Nwankwo; Arnold Arnold Ojugo
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1623-1633

Abstract

Competitive asset markets and increased globalization have continued to ripple the food value chain with complex dynamics, which has led to a range of challenges such as food safety and quality, traceability, and overall supply chain inefficiency. These have further continued to endanger the general well-being of society. With rice as a staple food in Nigeria, the rice food supply value chain consists of a series of tasks, processes, and activities that are linked together from freshly harvested products to consumer demand and supply. Study advances the SmartRice, a sensor-based block-chain framework that decentralizes as well as provides a decision-support for the food supply value chain process by first ensuring that accurate data of harvested goods are reported, and passed on to a chain. The study advances a decentralized framework to eliminate various forms of fraud rippled across the existing centralized system, minimize corruption through its sensor-based layered model as well as minimize the error in reported data along the value chain.

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