1 10 7 https://repository.horizon.ac.id/files/original/dc41b9eb19dd2aaa0259b6a4d5025bde.png 0374c59a31eb525bda02b357ac0a0e28 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 16 NO. 1 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Still Image A static visual representation. Examples include paintings, drawings, graphic designs, plans and maps. Recommended best practice is to assign the type Text to images of textual materials. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Cover Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 https://repository.horizon.ac.id/files/original/380ef2403d215efcaa49c71610cdff49.pdf b8f468a2a45f947d187ac9d7a45ad017 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 16 NO. 1 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 A Classifier to Detect Profit and Non Profit Websites Upon Textual Metrics for Security Purposes Subject The topic of the resource classifier; cyber-attacks; defense system; network traffic; nonprofit; profit; security polices; textual metrics; website. Description An account of the resource Abstract. Currently, most organizations have a defense system to protect their digital communication network against cyberattacks. However, these defense systems deal with all network traffic regardless if it is from profit or non-profit websites. This leads to enforcing more security policies, which negatively affects network speed. Since most dangerous cyberattacks are aimed at commercial websites, because they contain more critical data such as credit card numbers, it is better to set up the defense system priorities towards actual attacks that come from profit websites. This study evaluated the effect of textual website metrics in determining the type of website as profit or nonprofit for security purposes. Classifiers were built to predict the type of website as profit or non-profit by applying machine learning techniques on a dataset. The corpus used for this research included profit and non-profit websites. Both traditional and deep machine learning techniques were applied. The results showed that J48 performed best in terms of accuracy according to its outcomes in all cases. The newly built models can be a significant tool for defense systems of organizations, as they will help them to implement the necessary security policies associated with attacks that come from both profit and non-profit websites. This will have a positive impact on the security and efficiency of the network. Creator An entity primarily responsible for making the resource Yahya Tashtoush, Dirar Darweesh, Omar Darwish,Belal Alsinglawi & Rasha Obeidat Source A related resource from which the described resource is derived DOI: 10.5614/itbj.ict.res.appl.2022.16.1.6 Publisher An entity responsible for making the resource available IRCS-ITB Date A point or period of time associated with an event in the lifecycle of the resource 01 Desember 2021 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 2337-5787 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 classifier cyber-attacks defense system Jurnal Nasional Informatika network traffic nonprofit profit security polices textual metrics website https://repository.horizon.ac.id/files/original/4067dc686ca8ab562894617f3e4eec77.pdf 4f40971b5b6515d9f676e8f97e056086 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 16 NO. 1 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 A CNN-ELM Classification Model for Automated Tomato Maturity Grading Subject The topic of the resource automated tomato maturity grading; CNN-ELM; convolutional neural networks; extreme learning machines; hybrid classification model; tomato classification. Description An account of the resource Abstract. Tomatoes are popular around the world due to their high nutritional value. Tomatoes are also one of the world’s most widely cultivated and profitable crops. The distribution and marketing of tomatoes depend highly on their quality. Estimating tomato ripeness is an essential step in determining shelf life and quality. With the abundant supply of tomatoes on the market, it is exceedingly difficult to estimate tomato ripeness using human graders. To address this issue and improve tomato quality inspection and sorting, automated tomato maturity classification models based on different features have been developed. However, current methods heavily rely on human-engineered or handcrafted features. Convolutional neural networks have emerged as the preferred technique for general object recognition problems because they can automatically detect and extract valuable features by directly working on input images. This paper proposes a CNN-ELM classification model for automated tomato maturity grading that combines CNNs’ automated feature learning capabilities with the efficiency of extreme learning machines to perform fast and accurate classification even with limited training data. The results showed that the proposed CNN-ELM model had a classification accuracy of 96.67% and an F1-score of 96.67% in identifying six maturity stages from the test data. Creator An entity primarily responsible for making the resource John Paul Tan Yusiong Source A related resource from which the described resource is derived DOI: 10.5614/itbj.ict.res.appl.2022.16.1.2 Publisher An entity responsible for making the resource available IRCS-ITB Date A point or period of time associated with an event in the lifecycle of the resource 01 Desember 2021 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 2337-5787 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 automated tomato maturity grading CNN-ELM convolutional neural networks extreme learning machines hybrid classification model Jurnal Nasional Informatika tomato classification https://repository.horizon.ac.id/files/original/ed4ddc8b51fdc0e2f66c6090a1abb427.pdf b5c75cb769a63401212e83cb73513d12 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 16 NO. 1 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 Automatically Detect Software Security Vulnerabilities Based on Natural Language Processing Techniques and Machine Learning Algorithms Subject The topic of the resource machine learning algorithms; natural language processing techniques; software security vulnerability detection; software vulnerabilities; source code features. Description An account of the resource Abstract. Nowadays, software vulnerabilities pose a serious problem, because cyber-attackers often find ways to attack a system by exploiting software vulnerabilities. Detecting software vulnerabilities can be done using two main methods: i) signature-based detection, i.e. methods based on a list of known security vulnerabilities as a basis for contrasting and comparing; ii) behavior analysis-based detection using classification algorithms, i.e., methods based on analyzing the software code. In order to improve the ability to accurately detect software security vulnerabilities, this study proposes a new approach based on a technique of analyzing and standardizing software code and the random forest (RF) classification algorithm. The novelty and advantages of our proposed method are that to determine abnormal behavior of functions in the software, instead of trying to define behaviors of functions, this study uses the Word2vec natural language processing model to normalize and extract features of functions. Finally, to detect security vulnerabilities in the functions, this study proposes to use a popular and effective supervised machine learning algorithm. Creator An entity primarily responsible for making the resource Cho Do Xuan, Vu Ngoc Son & Duong Duc Source A related resource from which the described resource is derived DOI: 10.5614/itbj.ict.res.appl.2022.16.1.5 Publisher An entity responsible for making the resource available IRCS-ITB Date A point or period of time associated with an event in the lifecycle of the resource 01 Desember 2021 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 2337-5787 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 Jurnal Nasional Informatika machine learning algorithms natural language processing techniques software security vulnerability detection software vulnerabilities source code features https://repository.horizon.ac.id/files/original/02d76dad9804747b2109a958debcfbae.pdf aaace5da2934f8c2b7273ad582a733af Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 16 NO. 1 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 Mobile Robot Path Planning Optimization Based on Integration of Firefly Algorithm and Cubic Polynomial Equation Subject The topic of the resource cubic polynomial equation; firefly algorithm; mobile robot; optimal path planning. Description An account of the resource Abstract. Mobile Robot is an extremely essential technology in the industrial world. Optimal path planning is essential for the navigation of mobile robots. The firefly algorithm is a very promising tool of Swarm Intelligence, which is used in various optimization areas. This study used the firefly algorithm to solve the mobile robot path-planning problem and achieve optimal trajectory planning. The objective of the proposed method is to find the free-collision-free points in the mobile robot environment and then generate the optimal path based on the firefly algorithm. It uses the A∗ algorithm to find the shortest path. The essential function of use the firefly algorithm is applied to specify the optimal control points for the corresponding shortest smooth trajectory of the mobile robot. Cubic Polynomial equation is applied to generate a smooth path from the initial point to the goal point during a specified period. The results of computer simulation demonstrate the efficiency of the firefly algorithm in generating optimal trajectory of mobile robot in a variable degree of mobile robot environment complexity. Creator An entity primarily responsible for making the resource Sura Mazin Ali, Janan Farag Yonan, Omar Alniemi & Amjed Abbas Ahmed Source A related resource from which the described resource is derived DOI: 10.5614/itbj.ict.res.appl.2022.16.1.1 Publisher An entity responsible for making the resource available IRCS-ITB Date A point or period of time associated with an event in the lifecycle of the resource 01 Desember 2021 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 2337-5787 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 cubic polynomial equation firefly algorithm Jurnal Nasional Informatika mobile robot optimal path planning https://repository.horizon.ac.id/files/original/66a9b6b3c5e50d3c23a9a2bf54b7c456.pdf df90f49b1e0b6e5e6f6a2cfea3b4b864 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 16 NO. 1 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 Predicting the Extent of Sidoarjo Mud Flow Using Remote Sensing Subject The topic of the resource MNDWI; neural network; regression; remote sensing; Sidoarjo mudflow. Description An account of the resource Abstract. The Sidoarjo mud flow in East Java is the result of a natural phenomenon in which hot mudflow occurs due to volcanic activity. The Sidoarjo mud flow resulted in a considerable ecological disaster in the area. In this study, by using the Modification of Normalized Difference Water Index (MNDWI) technique we measured the extension of the mudflow area from 2013 to 2020 using Landsat 8 satellite data imagery. This study is meant to predict the extension of the mud flow area in the research site by comparing regression and neural network techniques in order to find the best approach. The RPROP MLP neural network technique was used to predict the Sidoarjo mud-flowing area in 2021 to 2025. Surprisingly the results of these calculations showed that the RPROP MLP neural network with three hidden layers and 20 neurons performed the best, with an R square value for training of 0.77915565 and for testing of 0.78321550. Creator An entity primarily responsible for making the resource Wishnumurti Wicaksono & Sani M. Isa Source A related resource from which the described resource is derived DOI: 10.5614/itbj.ict.res.appl.2022.16.1.4 Publisher An entity responsible for making the resource available IRCS-ITB Date A point or period of time associated with an event in the lifecycle of the resource 01 Desember 2021 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 2337-5787 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 Jurnal Nasional Informatika MNDWI neural network regression remote sensing Sidoarjo mudflow https://repository.horizon.ac.id/files/original/d73d848a8f6b81b2a1c0f5c7f4e44f18.pdf 489deaf4749bc87846b1960904e15cab Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL. 16 NO. 1 2022 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 Wireless Vibration Monitoring System for Milling Process and Analysis of the Influence of Processing Parameters Subject The topic of the resource milling process; monitoring system; vibration sensor; wireless sensor. Description An account of the resource Abstract. Milling is commonly applied in manufacturing industries to make engineering products. Vibrations that occur in the milling process can disturb the continuity of the process. Vibration monitoring systems are used in manufacturing industries to prevent further issues. Industrial Revolution 4.0 makes it necessary for manufacturing industries to adapt to rapidly developing technology. Wired vibration monitoring systems used in manufacturing industries will be replaced with wireless monitoring systems. For this reason, a wireless vibration monitoring system was developed in this study to solve the problems with wired monitoring systems, whose main challenges are tucked cables and high cost. A wireless monitoring system setup was built using three groups of components: a sensor node, a monitoring node, and a base station. Milling experiments with various depths of cut, feed rates, and spindle speeds were conducted to examine the performance of the wireless monitoring system. The results indicate that the wireless system recorded almost identical data as the wired system. The wireless vibration monitoring system could identify the effect of milling parameter variation such as depth of cut, feed rate, and spindle speed on the vibration level. The effect of depth of cut was more significant than that of spindle speed and feed rate. Creator An entity primarily responsible for making the resource Muhamad Rausyan Fikri, Kushendarsyah Saptaji & Fijai Naja Azmi Source A related resource from which the described resource is derived DOI: 10.5614/itbj.ict.res.appl.2022.16.1.3 Publisher An entity responsible for making the resource available IRCS-ITB Date A point or period of time associated with an event in the lifecycle of the resource 01 Desember 2021 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN: 2337-5787 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Journal of ICT Research and Applications ITB Bandung Vol. 16 No. 1 2022 Jurnal Nasional Informatika milling process monitoring system vibration sensor wireless sensor