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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 9,174 Documents
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Instrumentation system for data acquisition and monitoring of hydroponic farming using ESP32 via Google Firebase Prisma Megantoro; Rizki Putra Prastio; Hafidz Faqih Aldi Kusuma; Abdul Abror; Pandi Vigneshwaran; Dimas Febriyan Priambodo; Diaz Samsun Alif
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp52-61

Abstract

This article discusses the design of a hydroponic planting process monitoring system based on the internet of things. This device uses an ESP32 microcontroller board as the main controller. The parameters that were monitored and acquired were the conditions of the hydroponic growing media. Those parameters are; water pH, water temperature, water turbidity level, and ambient air temperature and humidity. The five parameters are measured by analog sensors integrated with the ESP32. These parameters affect the growth process and the quality of crop yields. This article also describes the calibration method for each sensor used for parameter measurement. Then the monitoring of these parameters is carried out by utilizing a real-time database, namely Google Firebase. This platform is very suitable for all IoT-based monitoring and control applications. Measurement result data is uploaded and saved to the real-time database. Then paired by Android-based applications. This application was created to be used by hydroponic farmers who use this device. Thus the results of monitoring can be used to optimize the process of growing hydroponic plants.
Hybrid model for software development: an integral comparison of DevOps automation tools Poonam Narang; Pooja Mittal
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp456-465

Abstract

DevOps is a fine fusion of development and operations teams together to deliver more efficient, reliable and quality software. DevOps make use of alternative set of automation tools for different development stages of software. The research presented in th is paper analyses selective automation tools to provide comprehensive and comparative tabular analysis followed by graphical comparison according to latest Google Trends. Best performer tools out of these alternative tool sets are grouped together into int egrated tool chain (ITC) in order to escalate DevOps performance in future. A hybrid automated model for software development using these selective automation tools from the ITC is also proposed. This analytic comparison will prove to be a big utility for young researchers, students and software developers to be cognizant with DevOps automation cul ture. Study of other tools or enhancement of the proposed hybrid model could also be considered as a part of future research.
A new direction search of hybrid quasi-Newton Evar Lutfalla Sadraddin; Ivan Subhi Latif
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp538-545

Abstract

A new hybrid quasi-Newton search direction ( HQNEI ) is proposed. It uses the update formula of Broyden–Fletcher–Goldfarb–Shanno (BFGS) with a certain conjugate gradient (CG) parameter by a nested direction. The global convergence analysis and superlinear rate, addtionaly with sufficient descent are proved using exact line search. Finally, the computation comparisons are made with original hybrid parents; BFGS and CG, through the efficiency in terms of iteration numbers and CPU-running time showing the superior of HQNEI. Therefore, the results marked preference of HQNEI from other two producer algorithms.
Application of advanced encryption standard in the computer or handheld online year-round registration system Jomar L. Calpito; Paul L. Olanday; Alain C. Gallarde
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp922-935

Abstract

With various severe security threats for web applications, ensuring security on the database layer itself is imperative. Hence, this study aims to protect data saved on the computer or handheld online year-round (CHOY) registration system using the advanced encryption standard (AES) to strengthen data security within the app so that even potential attackers gain access to the app's database; they cannot obtain valuable information because it is scrambled and unreadable. The proponents based the study's conceptual framework on the symmetric and asymmetric key algorithms and procedures manual on enrollment of Southern Isabela College of arts and trades (SICAT) and ISO 25010. The study consists of three elements: developing the CHOY web app imbued with AES, testing it in terms of online registration and spam prevention, and evaluating it using the ISO 25010 in terms of compatibility, reliability, and security. The evaluation results show that implementing the AES in the CHOY web app meets the ISO 25010 criteria mentioned above.
A novel energy efficient routing scheme for wireless sensor networks Veeresh Hiremath; Gopal Bidkar
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp271-280

Abstract

In the current rapid developing and smart world, the wireless sensor networks domain is among the most emergent fields with plenty of applications such as healthcare, wildlife, environmental monitoring, defense, and landslide detection. Distribution of cluster heads along with the selection of cluster heads is essentially vital for optimizing various network performance parameters. In this paper, a novel energy efficient routing scheme based on probabilistic sector wise clustering has been proposed, which results in energy saving in conjunction with superior network lifetime for wireless sensor networks. In the proposed routing technique, the sensing field is divided into multiple sectors and clusters in five different types. Nodes in the sector can communicate directly with the base station in one-hop or through the gateway node in two-hops. Nodes in the cluster communicate to the base station through the cluster head in three-hops. The simulation results of all five types are compared in terms of their life span. Life span of the network is analyzed by considering the round number in which the first node dies, the round number till which 80% of the nodes are alive, 50% of nodes are alive and 20% of the nodes are alive.
Utilizing a strait-range green phosphor γ-AlON:Mn,Mg for the task of achieving a super-broad hue gamut display My Hanh Nguyen Thi; Phan Xuan Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp748-753

Abstract

The screen backlighting produced by green β-sialon:Eu, as well as red K2SiF6:Mn phosphors, have an extremely expansive hue gamut that encompasses the majority of the national television system committee (NTSC) triangle. For our research, a substitute phosphor in green would be probed in terms of improving the screen hue range even further. The phosphor γ-AlON:Mn,Mg appears to be green in color with a smaller radiation band of colors than sharp β-silaon:Eu. By replacing γ-AlON:Mn,Mg with β-sialon:Eu, the screen hue range in the blue-green area is significantly expanded. In both the CIE 1931 and CIE 1976 hue spaces, the hue range of screens with γ-AlON:Mn,Mg, and K2SiF6:Mn entirely surpasses the NTSC benchmark. Furthermore, the stability of LEDs emit white light using γ-AlON:Mn,Mg appears to be similar to LEDs that utilize β-sialon:Eu.
Image anomalies detection using transfer learning of ResNet-50 convolutional neural network Zaid Taher Omer; Amel Hussein Abbas
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp198-205

Abstract

With the quick advancement of keen fabricating, information-based blame determination has pulled in expanding attention. As one of the foremost prevalent strategies of diagnosing errors, deep learning has accomplished exceptional comes about. Be that as it may, due to the truth that the estimate of the seeded tests is little in diagnosing mistakes, the profundities of the deep learning (DL) models for fault conclusion are shallow compared to the convolutional neural network in other regions (including ImageNet), which limits the accuracy of the final prediction. In this paper, ResNet-50 with a 25 convolutional layer depth has been proposed to diagnose anomalous images. Trained ResNet-50 applies ImageNet as a feature extractor to diagnose errors. It was proposed on three sets of data which are the bottle, the spoon, and the carton, and the proposed method was achieved. The prediction accuracy of the data set was 99%, 95% and 90%, respectively.
Cluster-based fuzzy regression trees for software cost prediction Assia Najm; Abdelali Zakrani; Abdelaziz Marzak
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp1138-1150

Abstract

The current paper proposes a novel type of decision tree, which is never used for software development cost prediction (SDCP) purposes, the cluster-based fuzzy regression tree (CFRT). This model uses the fuzzy k-means (FKM), which deals with data uncertainty and imprecision. The tree expansion is based on the variability measure by choosing the node with the highest value of granulation diversity. This paper outlined an experimental study comparing CFRT with four SDCP methods, notably linear regression, multi-layer perceptron, K-nearest-neighbors, and classification and regression trees (CART), employing eight datasets and the leave-one-out cross-validation (LOOCV). The results show that CFRT is among the best, ranked first in 3 datasets according to four accuracy measures. Also, according to the Pred(25%) values, the proposed CFRT model outperformed all the twelve compared techniques in four datasets: Albrecht, constructive cost model (COCOMO), Desharnais, and The International Software Benchmarking Standards Group (ISBSG) using LOOCV and 30-fold cross-validation technique.
Performance analysis of the application of convolutional neural networks architectures in the agricultural diagnosis Sara Belattar; Otman Abdoun; El khatir Haimoudi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp156-162

Abstract

Agriculture is an important sector for developing countries and farmers. Recently, numerous techniques for increasing agricultural productivity have been utilized. However, different issues are still encountered by farmers including various plant diseases. Plant diseases diagnoses are challenging research, and they should be analyzed and treated by detecting the diseased plant leaves. For that reason, in this paper, we develop our proposed architecture using convolutional neural networks (OP-CNN) as a computer-aided to detect and diagnose plant diseases. The proposed architecture can assist farmers in increasing both the quantity and quality of their agricultural productivity. Besides this, the OP-CNN helps to reduce disease prevalence through early detection. The performance of our proposed model is compared with other convolutional neural networks (CNN) architectures in order to validate its capability. The strawberry dataset was employed to train and test the models since the strawberry is one of the main crops in the Larache Province (Morocco). The experimental tests demonstrate that our proposed OP-CNN reaches the highest values versus DenseNet121, VGG19, and ResNet50 with 100%, 99%, 97%, and 63% respectively for classification accuracy, 100%, 100%, 98% and, 79% respectively for precision, 100%, 99%, 97%, and 63% respectively for recall, and 100%, 99%, 97%, and 58% respectively for "F" _1Score.
Secure and efficient routing protocol for low-power and lossy networks for IoT networks Soukayna Riffi Boualam; Mariya Ouaissa; Mariyam Ouaissa; Abdellatif Ezzouhairi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp478-487

Abstract

R outing p rotocol for l ow p ower and l ossy (RPL) is destined to support the specific requirements of l ow p ower and l ossy n etworks (LLN). This type of network suffers from the problem of determining and securing a routing protocol to best suit an environment. This article aims to present a new version of the efficient and secure RPL protocol. The proposed scheme consists of two parts : i) Proposing a new o bjective f unction (OF) based RPL which combines three nodes and links metrics are: e xpected r etransmission n umber (ETX), h ope c ount (HC), and the residual energy in order to have a precise decision to c hoose the optimal way to the des tination. ii) To securing the new efficient RPL protocol by combining an improved Diffie - Hellman (DH) algorithm for a robust key exchange model with k eyed - h ash m essage a uthentication c ode (HMAC) to ensure the authentication and integrity of RPL data exchan ged. To verify the level of security, we apply a formal verification using AVISPA tool which indicate that the s ecure and e fficient RPL (SE-RPL) achieve all security requirements. Simulation results on the Contiki platform illustrate that our proposed is m ore efficient in terms of p acket d elivery r atio (PDR) and energy compared to others standard OF.

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