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Contact Name
Rahmat Hidayat
Contact Email
mr.rahmat@gmail.com
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Journal Mail Official
rahmat@pnp.ac.id
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Kota padang,
Sumatera barat
INDONESIA
JOIV : International Journal on Informatics Visualization
ISSN : 25499610     EISSN : 25499904     DOI : -
Core Subject : Science,
JOIV : International Journal on Informatics Visualization is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of Computer Science, Computer Engineering, Information Technology and Visualization. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the JOIV follows the open access policy that allows the published articles freely available online without any subscription.
Arjuna Subject : -
Articles 20 Documents
Search results for , issue "Vol 5, No 4 (2021)" : 20 Documents clear
An Improved Flower Pollination Algorithm for Global and Local Optimization M. Iqbal Kamboh; Nazri Bin Mohd Nawi; Azizul Azhar Ramli; Fanni Sukma
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.738

Abstract

Meta-heuristic algorithms have emerged as a powerful optimization tool for handling non-smooth complex optimization problems and also to address engineering and medical issues. However, the traditional methods face difficulty in tackling the multimodal non-linear optimization problems within the vast search space. In this paper, the Flower Pollination Algorithm has been improved using Dynamic switch probability to enhance the balance between exploitation and exploration for increasing its search ability, and the swap operator is used to diversify the population, which will increase the exploitation in getting the optimum solution. The performance of the improved algorithm has investigated on benchmark mathematical functions, and the results have been compared with the Standard Flower pollination Algorithm (SFPA), Genetic Algorithm, Bat Algorithm, Simulated annealing, Firefly Algorithm and Modified flower pollination algorithm. The ranking of the algorithms proves that our proposed algorithm IFPDSO has outperformed the above-discussed nature-inspired heuristic algorithms.
Feature Selection Approach to Detect DDoS Attack Using Machine Learning Algorithms Muhammad Aqil Haqeemi Azmi; Cik Feresa Mohd Foozy; Khairul Amin Mohamad Sukri; Nurul Azma Abdullah; Isredza Rahmi A. Hamid; Hidra Amnur
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.734

Abstract

Distributed Denial of Service (DDoS) attacks are dangerous attacks that can cause disruption to server, system or application layer. It will flood the target server with the amount of Internet traffic that the server could not afford at one time. Therefore, it is possible that the server will not work if it is affected by this DDoS attack. Due to this attack, the network security environment becomes insecure with the possibility of this attack. In recent years, the cases related to DDoS attacks have increased. Although previously there has been a lot of research on DDoS attacks, cases of DDoS attacks still exist. Therefore, the research on feature selection approach has been done in effort to detect the DDoS attacks by using machine learning techniques. In this paper, to detect DDoS attacks, features have been selected from the UNSW-NB 15 dataset by using Information Gain and Data Reduction method. To classify the selected features, ANN, Naïve Bayes, and Decision Table algorithms were used to test the dataset. To evaluate the result of the experiment, the parameters of Accuracy, Precision, True Positive and False Positive evaluated the results and classed the data into attacks and normal class. Hence, the good features have been obtained based on the experiments. To ensure the selected features are good or not, the results of classification have been compared with the past research that used the same UNSW-NB 15 dataset. To conclude, the accuracy of ANN, Naïve Bayes and Decision Table classifiers has been increased by using this feature selection approach compared to the past research.
Relationship between Korean Informatics Curriculum and Textbook Learning Element Considering Compound Word Jaehong Kim; Hosung Woo; Jamee Kim; WonGyu Lee
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.731

Abstract

With the development of information and communication technology, countries around the world have strengthened their computer science curriculums. Korea also revised the informatics curriculum(The name of a subject related to computer science in Korea is informatics.) in 2015 with a focus on computer science. The purpose of this study was to automatically extract and analyze whether textbooks reflected the learning elements of the informatics curriculum in South Korea. Considering the forms of terms of the learning elements mainly comprised of compound words and the characteristics of Korean language, which makes natural language processing difficult due to various transformations, this study pre-processed textbook texts and the learning elements and derived their reflection status and frequencies. The terms used in the textbooks were automatically extracted by using the indexes in the textbooks and the part-of-speech compositions of the indexes. Moreover, this study analyzed the relevance between the terms by deriving confidence of other terms for each learning element used in the textbooks. As a result of the analysis, this study revealed that the textbooks did not reflect some learning elements in the forms presented in the curriculum, suggesting that the textbooks need to explain the concepts of the learning elements by using the forms presented in the curriculum at least once. This study is meaningful in that terms were automatically extracted and analyzed in Korean textbooks based on the words suggested by the curriculum. Also, the method can be applied equally to textbooks of other subjects.
Bridging Usability and Accessibility of User Authentication using Usable Accessed (UAce) for Online Payment Applications Juliana Mohamed; Mohd Farhan Md Fudzee; Sofia Najwa Ramli; Mohd Norasri Ismail; - Defni
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.740

Abstract

Usability and accessibility are significant authentication aspects for online applications. Despite the fact that there are ongoing efforts to improve the interface design, some existing research only focuses on a single aspect of it. Thus, it is vital to investigate how to merge these two features into a practical and workable solution. This study presents a preliminary process for designing accessible and usable applications for online banking payment using Usable Accessed (UAce by adopting Design Science Research (DSR) as its methodology. The UAce standard considers attributes and characteristics from the user authentication. The standard establishes a development method and tool for assessing subjectively and quantitatively usable, as well as the user authentication while taking into account specific elements, qualities, and features. The DSR technique for developing highly usable and accessible interactive apps was utilized in designing this approach.
Monitoring Rice Crop and Paddy Field Condition Using UAV RGB Imagery Mohd Yazid Abu Sari; Yana Mazwin Mohmad Hassim; Rahmat Hidayat; Asmala Ahmad
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.742

Abstract

An effective crop management practice is very important to the sustenance of crop production. With the emergence of Industrial Revolution 4.0 (IR 4.0), precision farming has become the key element in modern agriculture to help farmers in maintaining the sustainability of crop production. Unmanned aerial vehicle (UAV) also known as drone was widely used in agriculture as one of the potential technologies to collect the data and monitor the crop condition. Managing and monitoring the paddy field especially at the bigger scale is one of the biggest challenges for farmers. Traditionally, the paddy field and crop condition are only monitored and observed manually by the farmers which may sometimes lead to inaccurate observation of the plot due the large area. Therefore, this study proposes the application of unmanned aerial vehicles and RGB imagery for monitoring rice crop development and paddy field condition. The integration of UAV with RGB digital camera were used to collect the data in the paddy field. Result shows that the early monitoring of rice crops is important to identify the crop condition. Therefore, with the use of aerial imagery analysis from UAV, it can help to improve rice crop management and eventually is expected to increase rice crop production.
A Packet Delay Assessment Model in the Data Link Layer of the LTE Ulugbek Amirsaidov; Azamat Qodirov
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.601

Abstract

The issues of modeling and evaluating the characteristics of the LTE data link layer functioning are considered. Transmitting packets in the data link layer are represented by a probabilistic-temporal graph consisting of two subgraphs. The first subgraph describes the operation of the HARQ protocol, and the second subgraph describes the operation of the ARQ protocol. The first subgraph is nested within the second subgraph. The probabilities of correct reception, non-error detection, and retransmission of packets in the MAC and RLC layers and generating functions of the packet service time based on the HARQ and ARQ protocols are determined. With the help of generating functions, the average value, variance, and coefficient of variation of the packet service time are determined. To calculate the average packet delay time in the LTE data link layer, the type of queuing system is selected, taking into account the coefficient of variation of the packet service time. The analysis of packets' delay time in the network's data link layer is carried out for different values of the intensity of packet arrival and the probabilities of a bit error in the physical layer of the network. For the sustainable functioning of the data link layer of the network, the limit values of the intensity of the arrival of packets are determined for a given probability of a bit error in the physical layer of the network.
An Efficient Approach for Uncertain Event Detection in RFID Complex Event Processing Siti Salwani Binti Yaacob; Hairulnizam Bin Mahdin; Mohammed Saeed Jawad; Nayef Abdulwahab Mohammed Alduais; Akhilesh Kumar Sharma; Aldo Erianda
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.736

Abstract

The globalization of manufacturing has increased the risk of counterfeiting as the demand grows, the production flow increases, and the availability expands. The intensifying counterfeit issues causing a worriment to companies and putting lives at risk. Companies have ploughed a large amount of money into defensive measures, but their efforts have not slowed counterfeiters. In such complex manufacturing processes, decision-making and real-time reactions to uncertain situations throughout the production process are one way to exploit the challenges. Detecting uncertain conditions such as counterfeit and missing items in the manufacturing environment requires a specialized set of technologies to deal with a flow of continuously created data. In this paper, we propose an uncertain detection algorithm (UDA), an approach to detect uncertain events such as counterfeit and missing items in the RFID distributed system for a manufacturing environment. The proposed method is based on the hashing and thread pool technique to solve high memory consumption, long processing time and low event throughput in the current detection approaches. The experimental results show that the execution time of the proposed method is averagely reduced 22% in different tests, and our proposed method has better performance in processing time based on RFID event streams.
Group Decision Support System Using AHP, Topsis and Borda Methods for Loan Determination in Cooperatives Yance Sonatha; Meri Azmi; Indri Rahmayuni
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.640

Abstract

Cooperatives are one of the business units which purpose is to help the economy of small and medium-sized communities. One of the cooperatives in the city of Padang, West Sumatra, Indonesia is KPN Kapur Warna. The routine business unit managed by KPN Kapur Warna is for savings and loans. So far, the savings and loan process is still done manually, including determining the eligibility of members to receive loans. Determination of the eligibility of members is carried out less objectively, by only looking at the profile of participants in general and the decision-making process is only carried out by one person, namely the chairman of the cooperative. The process that has been carried out so far has often resulted in wrong targets, namely providing loans to members who are not appropriate, resulting in bad credit or delays in paying monthly installments of participants. Therefore, we need a group decision support system that can help solve the above problems. In this study, a group decision support system was made using the AHP, TOPSIS and BORDA methods using five main criteria. The AHP method is used to determine the priority value for each criterion and the TOPSIS method is used to rank each alternative. Each decision maker performs the same process with the two methods, and then voting is carried out using the BORDA method of combining assessments for different decision makers. This study succeeded in providing a reference in determining the eligibility of which members are entitled to receive loans from cooperatives, with results that are more subjective and can help cooperatives in their work efficiently.
Proposition for LMS Integration for Share, Exchange, and Spread of Online Lectures under Covid-19 Environment Won Ho; Nguyen-Khang Pham; Dae-Hyun Lee; Yong Kim
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.744

Abstract

There has been a movement to share and spread online lectures through OCW and MOOC systems. This movement would have been spread widely and adopted widely if those courses could be easily exchangeable with other platforms or services. If this function is available, learning activities, resources, learning outcomes can be accessed between different platforms and services. With this function, the credit exchange between different platforms or services will be easier. It also facilitates course sharing and circulation. Because the LMS is the basic platform for online classes, providing sharable and reusable learning activities, resources, and learning outcomes across the different LMSs is very demanding for online education. Analyzing LMS use in Korean universities, Moodle, Canvas, and domestic LMSs are founded to be the significant three kinds that are widely used in Korea. In this paper, a method of integrating Moodle, Canvas, and domestic LMS services is proposed. A central Moodle server is installed as the main LMS server, and the method to connect or complement with a central Moodle server is proposed for each different kind of LMS. LMS users can easily access a different kind of LMS as a form of imported course, tightly connected service, or log in as SSO. This proposition can be applied to various service fields such as KMOOC, KOCW, credit exchange, lecture exchange between universities, regional unification of online educational centers as a practical problem-solver.
Intelligence Eye for Blinds and Visually Impaired by Using Region-Based Convolutional Neural Network (R-CNN) Lee Ruo Yee; Hazalila Kamaludin; Noor Zuraidin Mohd Safar; Norfaradilla Wahid; Noryusliza Abdullah; Dwiny Meidelfi
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.735

Abstract

Intelligence Eye is an Android based mobile application developed to help blind and visually impaired users to detect light and objects. Intelligence Eye used Region-based Convolutional Neural Networks (R-CNN) to recognize objects in the object recognition module and a vibration feedback is provided according to the light value in the light detection module. A voice guidance is provided in the application to guide the users and announce the result of the object recognition. TensorFlow Lite is used to train the neural network model for object recognition in conjunction with extensible markup language (XML) and Java in Android Studio for the programming language. For future works, improvements can be made to enhance the functionality of the Intelligence Eye application by increasing the object detection capacity in the object recognition module, add menu settings for vibration intensity in light detection module and support multiple languages for the voice guidance.

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