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Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)
Published by Universitas Ahmad Dahlan
ISSN : 23383070     EISSN : 23383062     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
JITEKI (Jurnal Ilmiah Teknik Elektro Komputer dan Informatika) is a peer-reviewed, scientific journal published by Universitas Ahmad Dahlan (UAD) in collaboration with Institute of Advanced Engineering and Science (IAES). The aim of this journal scope is 1) Control and Automation, 2) Electrical (power), 3) Signal Processing, 4) Computing and Informatics, generally or on specific issues, etc.
Arjuna Subject : -
Articles 505 Documents
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Descriptive Analysis and ANOVA Test with File Sending on Computer Networks Attacked with Rogue's Dynamic Host Configuration Protocol (DHCP) Hero Wintolo; Yuliani Indrianingsih; Wahyu Hamdani; Syafrudin Abdie
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26167

Abstract

The requirement for a computer that is physically connected to a computer network to be able to access existing resources on a computer network in the form of an IP address obtained statically or dynamically. On a static IP address, there are not many problems that arise because it is loaded directly into the computer, while for a dynamic IP address, security problems arise in the form of a dynamic IP address sharing server in the form of DHCP Rogue. The configuration that is added to the first router when the network is hit by a DHCP rogue attack is to configure the main router, in this case, the first router, and the switch used as a connecting device between computers. configuration on both switches is done by snooping trust which is useful for securing IP addresses to avoid IP attackers. This research was conducted to find out if a computer network with a dynamic IP address was attacked by sending files between computers. Files with the longest sending time indicate an attack on the computer network. The method used in this study is the ANOVA test with descriptive-based analysis. Based on the results of the analysis, it is known that the average file transfer time on networks affected by DHCP Rogue is higher than the average file transfer time on normal and mitigated networks, and the significant value of the ANOVA test results has a value of 0.004. In general, it can be concluded that there are differences in data transfer when the network is normal, the network is subject to DHCP Rogue, and the network has been mitigated with DHCP Rogue.
On IPv6 Slow Adoption; Why We Might Approach it Wrongly? Mukhammad Andri Setiawan
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26058

Abstract

The slow adoption of IPv6, despite its numerous advantages over IPv4, is a pressing issue in many regions, including Indonesia. This challenge is particularly significant given the increasing demand for Internet of Things (IoT) devices and the need for a sustainable, scalable, and flexible network infrastructure. In response to this issue, our research introduces the Design Thinking-Inspired Technology Adoption (DTITA) model. This innovative approach leverages design thinking principles to facilitate the adoption of new and challenging technologies. DTITA incorporates the five stages of design thinking alongside traditional technology adoption factors, such as perceived usefulness, ease of use, and social influence. The DTITA model aims to create user-centric solutions that address new technologies' unique challenges and barriers. By placing the user at the center of the design process, we were able to develop solutions that are not only technologically advanced but also highly accessible and relevant to users. Through a survey involving individuals from the education industry, Internet Service Providers (ISPs), content providers, government institutions, and the Information and Communication Technology (ICT) industry, we identified key barriers impeding the widespread implementation of IPv6. This study provides valuable insights into the application of design thinking in the context of technology adoption, particularly in the case of IPv6. It contributes to the broader discourse on technology adoption and offers practical recommendations for stakeholders and decision-makers in Indonesia.
Application of SMOTE to Handle Imbalance Class in Deposit Classification Using the Extreme Gradient Boosting Algorithm Dina Arifah; Triando Hamonangan Saragih; Dwi Kartini; Muliadi Muliadi; Muhammad Itqan Mazdadi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26155

Abstract

Deposits became one of the main products and funding sources for banks and increasing deposit marketing is very important. However, telemarketing as a form of deposit marketing is less effective and efficient as it requires calling every customer for deposit offers. Therefore, the identification of potential deposit customers was necessary so that telemarketing became more effective and efficient by targeting the right customers, thus improving bank marketing performance with the ultimate goal of increasing sources of funding for banks. To identify customers, data mining is used with the UCI Bank Marketing Dataset from a Portuguese banking institution. This dataset consists of 45,211 records with 17 attributes. The classification algorithm used is Extreme Gradient Boosting (XGBoost) which is suitable for large data. The data used has a high-class imbalance, with "yes" and "no" percentages of 11.7% and 88.3%, respectively. Therefore, the proposed solution in the research, which focused on addressing the Imbalance Class in the Bank marketing dataset, was to use Synthetic Minority Over-sampling (SMOTE) and the XGBoost method. The result of the XGBoost study was an accuracy of 0.91016, precision of 0.79476, recall of 0.72928, F1-Score of 0.56198, ROC Area of 0.93831, and AUCPR of 0.63886. After SMOTE was applied, the accuracy was 0.91072, the precision was 0.78883, the recall was 0.75588, F1-Score was 0.59153, ROC Area was 0.93723, and AUCPR was 0.63733. The results showed that XGBoost and SMOTE could outperform other algorithms such as K-Nearest Neighbor, Random Forest, Logistic Regression, Artificial Neural Network, Naïve Bayes, and Support Vector Machine in terms of accuracy. This study contributes to the development of effective machine learning models that can be used as a support system for information technology experts in the finance and banking industries to identify potential customers interested in subscribing to deposits and increasing bank funding sources.
Eidos System Prediction of Myopia in Children in Early Education Stages Abdullah M. Al-Ansi; Mudar Almadi; Parul Ichhpujani; Vladimir Ryabtsev
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26292

Abstract

This study used a database containing factors that, when processed using the Eidos intellectual system, detect myopia in children of primary school age. The database includes parameters that take into account the properties of the visual system, as well as factors that determine the duration of the performance of the main functions of the cognitive and entertaining nature of the students. The results obtained allow us to determine those factors that are more conducive to the appearance of myopia. The negative impact of some factors that cause myopia can be removed, such as, limiting the screen time spent, increasing outdoor activities/sports. A retrospective training sample can be used for automated processing using the Eidos intellectual system of the results obtained during the preventive examination of schoolchildren by an ophthalmologist. Early intervention towards myopia management in students, improves the chances of maintaining vision and slows myopia progression. The contribution of this research includes factors of a social nature that could be influenced at school in the process of education, increasing the attention towards childent, awareness of maintaining vision and slows down the progression of myopia.
Website Vulnerability Analysis of AB and XY Office in East Java Muchammad Zaidan; Febyola Noeraini; Zamah Sari; Denar Regata Akbi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26183

Abstract

Study this aim for analyze and identify vulnerability existing security on AB and XY Service Websites in East Java. Contribution study this is give more understanding deep about type vulnerability specific security and its impact to field website security. Method research used involve data scanning, analysis vulnerabilities, and Brute Force experiments. A total of 2 samples of AB and XY Service Websites were analyzed For identify existing vulnerabilities the data. However so, necessary noted that method study this own a number of limitations. First, size sample used possible limited to AB and XY Service Websites in East Java only, so generalization results study against other websites needs done with be careful. Second, analysis statistics used only covers analysis descriptive, so study this not yet investigate linkages between existing variables. Although thus, results study show exists necessary weaknesses and vulnerabilities corrected on AB and XY Service Websites. A number of findings covers problem website configuration and handling vulnerability that is not adequate. With highlight specific susceptibility, research this give more understanding deep about threat security faced by AB and XY Service Websites. In context field website security, research this own implication important. With understand existing vulnerabilities on AB and XY Service Websites, steps repair proper security can take for protect sensitive data and improve protection security in a manner whole. Kindly whole, research this identify and analyze vulnerability security on AB and XY Service Websites, as well give more understanding Specific about type existing vulnerabilities. Although there are limitations in method study this is the result still give valuable insight in field website security and can become base for repair more security effective and more data protection on both the AB and XY Service Websites.
Electrical Tomography Sensor Modelling for Detection of Fuel Proportion in Vessel Rian Fahrizal; Jaga Sobar Julianto; Alief Maulana; Rocky Alfanz; Ceri Ahendyarti; Rohmadi Rohmadi; Imamul Muttakin
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26304

Abstract

Electrical capacitance volume tomography (ECVT) is a method for determining the volumetric distribution of dielectric permittivity using the capacitance measurement principle. The determination of volumetric distribution of dielectric permittivity is important to regulate a process in which quantity of materials is a decisive parameter such as in industrial setting or vehicle sub-system. ECVT is a relatively fast and non-radiating method to observe spatio-temporal phenomena inside a process, making it a valuable technique. Sensor modelling and image reconstruction study are essentials in designing a suitable imaging system based on measurements from plurality of electrodes providing higher degree of information being observed. This research conducts sensor modelling with varying fuel objects in the interior of a cylindrical vessel. The capacitance value was simulated between a combination of eight electrodes mounted encapsulating the tube. Each measured electrode was given an excitation voltage as a source of an electrostatic field, which interacts with the object’s presence. The objects in this study are benzene, kerosene, and diesel fuel, along with reference dielectric values of water and air. Image reconstruction used the linear back projection (LBP) method. Matrix operations between sensor’s pre-defined sensitivity and capacitance values produce data that can be plotted into an image estimating the true distribution of objects. Capacitance values from modelling are proportional to the actual object’s permittivity. The reconstruction provides qualitative information on the proportion of fuel in the vessel based on the capacitance value. Images have distinct values according to the presence of different objects under investigation. The research contribution is a proof of concept in using capacitance tomography to detect different fuels inside an enclosed tank at modelling stage. In addition, this study serves as a guideline for implementing a non-invasive and non-intrusive system for determining proportions of materials of interests inside a certain setup.
Sentiment Analysis of Customers’ Review on Delivery Service Provider on Twitter Using Naive Bayes Classification Ari Basuki
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26327

Abstract

Customer evaluations on social media may help us remain competitive and comprehend our business's target market. By analysing consumer evaluations, a business owner can identify common themes, pain points, and desired features or enhancements.  By analysing customer feedback across multiple channels, such as social media, online reviews, and customer service interactions, businesses can rapidly identify any negative sentiment or potential brand damage. The contribution of our study is to evaluate the performance of the Naive Bayes method for classifying customer feedback on courier delivery services obtained via Twitter. The Naive Bayes algorithm is selected due to its simplicity, which facilitates efficient computation, suitability for large datasets, outstanding performance on text classification, and ability to manage high-dimensional data. In this investigation, the Naive Bayes classifier accuracy is 0.506, which is considered to be low.  According to our findings, the irrelevant feature classification resulting in an error throughout the categorization process. A large number of data appearance characteristics that do not correspond to the testing data category have been identified as a result of this occurrence.
Design and Implementation of Embedded Biometric-Based Access Control System with Electronic Lock using Raspberry Pi Youssef Elmir; Abdeldjalil Abdelaziz; Mohammed Haidas
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26162

Abstract

This paper presents the design and implementation of an improved access control system based on biometric recognition, utilising Raspberry Pi technology. The proposed system aims to enhance the security of the existing electronic lock-based system at the SGRE-Lab of University Tahri Mohammed of Bechar in Algeria. The proposed system employs multimodal biometrics, integrating facial recognition and speaker verification for personal identification. Following initial verification by the electronic lock, the system captures the user's face through a camera to perform facial recognition. In cases where the user's identity is uncertain, a voice recognition module prompts the user to say a secret word, confirming their identity through the microphone. The combination of these two biometric techniques ensures access is granted, and an access log is recorded, with an accompanying notification sent to the administrator via SMS. As technical contribution, this paper presents the design and implementation of an embedded biometric-based access control system using Raspberry Pi, which includes the integration with an electronic lock and digicode, in the other hand, a second innovation contribution by combining biometric-based authentication with Raspberry Pi technology, this paper introduces an innovative approach to access control systems that provides a more secure and reliable means of access control than traditional methods based on keys or passwords. An overview of the proposed system's architecture is provided, its operation modes, and necessary hardware and software requirements. The promising obtained results of demonstrations show a notable improvement in security levels, characterized by reduction of false acceptances, however, the paper acknowledges that users unfamiliar with the biometric system may face challenges, potentially leading to false rejections. Future work should focus on mitigating these challenges and addressing user familiarity issues.
Aspect-Based Sentiment Analysis from User-Generated Content in Shopee Marketplace Platform Andharini Dwi Cahyani
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26367

Abstract

A number of businesses, such as TripAdvisor, Open Table, and Yelp, have successfully utilized aspect-based sentiment analysis in order to gain insights from reviews provided by customers and enhance the quality of their goods or services.  Businesses are able to swiftly discover any unfavorable sentiment or possible harm to their brand when they analyze client input across numerous aspects from social media, online reviews, and conversations with customer care representatives. This study aims to explain how aspect-based semantic analysis of market-collected user-generated data through performance comparisons of Doc2vec and TF-IDF vectorization. Both Doc2Vec and TF-IDF have their own distinctive qualities, which might vary according on the nature of the job, the dataset, and the volume of the available training data. For the objectives of this research, the data was obtained from several of fashion merchants that run their companies by means of the Shopee platform, which is a well-known online marketplace platform in Indonesia.  In this research, the accuracy and F1 Score achieved by Doc2Vec vectorization was superior to those achieved by TF-IDF vectorization. Our findings shows that Doc2Vec vectorization is better for classifying customer ratings because it can pull out the semantic meaning of words in a document. The findings also shows that the score of c and gamma parameter have significant impact to the score of Accuracy and F1 Score of the classifier.By precisely categorizing client sentiment, this study enables businesses to improve their services, respond to customers' problems, and increase their customer satisfaction.
Strawberry Plant Diseases Classification Using CNN Based on MobileNetV3-Large and EfficientNet-B0 Architecture Dyah Ajeng Pramudhita; Fatima Azzahra; Ikrar Khaera Arfat; Rita Magdalena; Sofia Saidah
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 3 (2023): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i3.26341

Abstract

Strawberry is a plant that has many benefits and a high risk of being attacked by pests and diseases. Diseases in strawberry plants can cause a decrease in the quality of fruit production and can even cause crop failure. Therefore, a method is needed to assist farmers in identifying the types of diseases in strawberry plants. Currently, there are many methods to assist farmers in identifying types of disease in plants, including strawberry plants. In this study, a system is proposed to be able to detect strawberry plant diseases by classifying the disease based on healthy and diseased strawberry leaf images. The proposed system is the Convolutional Neural Network (CNN) algorithm using MobileNetV3-Large and EfficientNet-B0 models to train pre-processed datasets. The results of this study obtained the best accuracy reaching 92.14% using the MobileNetV3-Large architecture with the hyperparameter optimizer RMSProp, epochs 70, and learning rate 0.0001. The percentage of the evaluation model using MobileNetV3-Large for precision, recall, and F1-Score achieved 92.81%, 92.14%, and 92.25%.  Whereas in the EfficientNet-B0 architecture, the best accuracy results only reach 90.71% with the hyperparameter optimizer Adam, 70 epochs, and a learning rate of 0.003. Then, the precision, recall, and F1-scores for EfficientNet-B0 reached 92.65%, 90.00%, and 90.37%. Overall, it presents fairly good results in classifying strawberry leaf plant disease. Furthermore, in future work, it needs to obtain higher accuracy by generating more datasets, trying other augmentation techniques, and proposing a better model.

Page 27 of 51 | Total Record : 505

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