1 10 8 https://repository.horizon.ac.id/files/original/a0d3c85e7936dc9cbce2eec8fd827a24.pdf 296202bced95dbb6c0e60b56f822275e 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. 15 NO. 2 (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 Optimization of 2D-CNN Setting for the Classification of Covid Disease Using Lung CT Scan Subject The topic of the resource 2D-CNN, Covid, Lung CT Scan, classification Description An account of the resource RT-PCR is considered the best diagnostic tool. Previous studies have demonstrated the reliability of CNN in classifying classifications, but CNN requires a lot of training data. Meanwhile, at the CT Scan clinic, patients are limited. Therefore, exploration of 2D-CNN settings is proposed to optimize CNN performance on limited data. We compare: (1) activation models, (2) output shapes per layer,(3) dropout layers, and (4) early stopping values. The test results show that RELU activation is better than Sigmoid. Rescaling (128x128) is better for scala (64x64) and (256x256) which affects the output shape model of each layer. In this learning stage, the use of dropouts in the CNN architecture achieves robust accuracy than the architecture that ignores dropouts. The use of 15 early stoppings is better than other values compared. 20 images of pneumonia and 20 images of covid have been tested using the proposed method and achieved 87.50% accuracy, 80.00% precision, 100% recall, and 99.89% F1-Score. Our method is superior to the the comparison method in terms of accuracy, precision, recall, and f1-score, which achieves 85%, 70%, 100%, and 82.35%, respectively Creator An entity primarily responsible for making the resource Kartika Candra Kirana, Slamet Wibawanto, Achmad Hamdan, Wahyu Nur Hidayat Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i2.1083 Publisher An entity responsible for making the resource available Faculty of Computer Science Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 2022-07-02 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource e-ISSN : 2502-9274 printed ISSN : 2088-7051 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 Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information) 2D-CNN classification COVID Lung CT Scan https://repository.horizon.ac.id/files/original/119f7c32e9bca588193455788fbf178c.pdf b2d33ceaa70b0692fd076a07dd4ea68c 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. 15 NO. 2 (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 Gender Prediction of Indonesian Twitter Users Using Tweet and Profile Features Subject The topic of the resource gender, Twitter, user, classification, feature extraction, demography Description An account of the resource The increasing use of social media generates huge amounts of data which in turn triggers research into social media analytics. Social media contents can be analyzed to explore public opinion on an issue or provide the insights reflecting proxy indicators towards real-world events. Understanding the demographics of social media users can increase the potential for applications of sentiment analysis, topic modeling, and other analytical tasks. To map demographics, we need to know the latent attributes of users, such as age, gender, occupation and location of residence. Since this attribute is not directly available, we need to do some inference from the social media data. This study aims to predict the gender attribute given a Twitter user account. We conducted experiments with several supervised classifiers with feature extraction, including the use of word embedding representations. The results of this study indicate that the combination of features extracted from Tweet contents and user profile structured data can predict the gender of Twitter users in Indonesia with accuracy above 80%. Creator An entity primarily responsible for making the resource Rahmad Mahendra, Hadi Syah Putra, Douglas Raevan Faisal, Fadzil Rizki Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i2.1079 Publisher An entity responsible for making the resource available Faculty of Computer Science Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 2022-07-02 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource e-ISSN : 2502-9274 printed ISSN : 2088-7051 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 Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information) classification demography Feature extraction Gender Twitter user https://repository.horizon.ac.id/files/original/0e69344ba5d35fdaf75fc536f72c0ef1.pdf aa08dcc4957184aad3ec904d5ca1650b 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. 15 NO. 2 (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 UML Transformation to Java-based Software Product Lines Subject The topic of the resource model transformation, software product line engineering, uml profile, variability modules for java Description An account of the resource Software product line engineering (SPLE) is an emerging approach that enables variability management in software development. SPLE offers tremendous benefits, but lack of tool support becomes a barrier in the adoption of SPLE. Variability modules for Java (VMJ) is an implementation approach that is defined based on the variability modules (VM) concept to support SPLE. VMJ combines Java modules system and design patterns that are commonly used by software developers. VMJ is accompanied by a UML profile, called UML-VM profile, which extends UML notation to model variability in the UML diagram. UML-VM diagram is used to model the problem domain, and VMJ is used in the domain implementation. In this research, we design a model transformation from Unified Modeling Language (UML) diagram into VMJ. The transformation rules are defined based on the UML-VM profile and implemented in the Eclipse Acceleo model to text transformation. As a result, a UML diagram can be transformed automatically into Java-based software product lines. The transformation tool is evaluated using a case study by comparing the generated code and the actual implementation. Creator An entity primarily responsible for making the resource Falah Prasetyo Waluyo, Maya R.A. Setyautami, Ade Azurat Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i2.1070 Publisher An entity responsible for making the resource available Faculty of Computer Science Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 2022-07-02 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource e-ISSN : 2502-9274 printed ISSN : 2088-7051 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 Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information) model transformation Software product line engineering uml profile variability modules for java https://repository.horizon.ac.id/files/original/0e050f8f9c6a11b2dafa9034d05dc920.pdf b707d0e5c98ad16810ff8b69b4cf5e27 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. 15 NO. 2 (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 Towards Erlang-based ABS Microservices Framework for Software Product Line Development Subject The topic of the resource Software product line engineering, Web engineering, Delta Oriented Programming, Microservices Description An account of the resource Software Product Line Engineering (SPLE) is one of the approaches that can manage the variability in developing sets of products. However, there is a need for development tools such as programming language and toolchain in realising SPLE. One language that supports the SPLE process is Abstract Behavioral Specification (ABS). ABS Microservices is one research that utilises ABS to create a web framework that supports the SPLE process. This framework uses ABS to generate Java-based applications. However, there is a need for renewal to the ABS Microservices framework. Deprecation of the Java backend of the ABS opens a new exploration of another web framework that uses other ABS backend languages. We present the ABS Microservices web framework based on Erlang OTP. We choose Erlang because it promises more efficient resource usage and the Erlang backend is one of the ABS backends with the most available features. This research aims to create an entry point for ABS Microservices to support more language. We use a case study and apply the six quality factors of software product line implementation to evaluate our framework. This research shows that the Erlang variant of ABS Microservices has less resource usage than the Java variant. Hence, this promises more options to develop product lines using ABS Microservices. Creator An entity primarily responsible for making the resource Adrika Novrialdi, Daya Adianto, Aulia Rosyida, Priambudi Lintang Bagaskara, Ade Azurat Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i2.1065 Publisher An entity responsible for making the resource available Faculty of Computer Science Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 2022-07-02 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource e-ISSN : 2502-9274 printed ISSN : 2088-7051 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 Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information) Delta Oriented Programming Microservices Software product line engineering Web engineering https://repository.horizon.ac.id/files/original/ac34558c3d03a66274734075475201b2.pdf 4a71ecc6fd5c575d89d8b8a6f79de8a4 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. 15 NO. 2 (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 Myers-Briggs Type Indicator Personality Model Classification in English Text using Convolutional Neural Network Method Subject The topic of the resource classification, natural language processing, MBTI personality model, GloVe word embedding, convolutional neural network Description An account of the resource Myers-Briggs Type Indicator (MBTI) is a personality model developed by Katharine Cooks Briggs and Isabel Briggs Myers in 1940. It displays a combination of preferences from four domains. Generally, test takers need to answer about 50 to 70 questions, and it is relatively expensive to know MBTI personality. The researcher developed a personality classification system using the Convolutional Neural Network (CNN) method and GloVe (Global Vectors for Word Representation) word embedding to solve this problem. The dataset used in this research consists of 8,675 data from the Kaggle site. The steps in this research are downloading the dataset from Kaggle, text preprocessing, GloVe weighting, classification using the CNN method, and evaluation using accuracy from the Confusion Matrix. Based on the tests carried out, using GloVe weighting can improve the model accuracy rather than random weighting. The best GloVe word dimensions depend on the metrics used to measure the model performance and the data of the classes contained in the dataset. From the CNN hyperparameter tuning test, the Adamax optimizer performs better and produces higher accuracy than the Adam optimizer. In addition, the CNN hyperparameter tuning increased model accuracy more significantly compared with the best GloVe word embedding dimensions. Creator An entity primarily responsible for making the resource Joseph A. Sugihdharma, Fitra A. Bachtiar Source A related resource from which the described resource is derived : http://dx.doi.org/10.21609/jiki.v15i2.1052 Publisher An entity responsible for making the resource available Faculty of Computer Science Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 2022-07-02 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource e-ISSN : 2502-9274 printed ISSN : 2088-7051 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 Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information) classification Convolutional neural network GloVe word embedding MBTI personality model natural language processing https://repository.horizon.ac.id/files/original/40ccb02e0d64c9e50f0669ed1990d07c.pdf e11cab049142c2c60411f1ae24c03bc7 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. 15 NO. 2 (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 Bimodal Keystroke Dynamics Based Authentication for Mobile Application Using Anagram Subject The topic of the resource biometrics, keystroke dynamic, identification, authentication Description An account of the resource Currently, most of the smartphones recognize uses based on static biometrics, such as face and fingerprint.However, those traits were vulnerable against spoofing attack. For overcoming this problem, dynamic biometrics like the keystroke and gaze are introduced since it is more resistant against spoofing attack. This research focuses on keystroke dynamics for strengthening the user recognition system against spoofing attacks. For recognizing a user, the user keystrokes feature used in the login process is compared with keystroke features stored in the keystroke features database. For evaluating the accuracy of the proposed system, words generated based on the Indonesian anagram are used. Furthermore, for conducting the experiment, 34 participants were asked to type a set of words using the smartphone keyboard. Then, each user’s keystroke is recorded. The keystroke dynamic feature consists of latency and digraph which are extracted from the record. According to the experiment result, the error of the proposed method is decreased by 23.075% of EER with FAR and FRR are decreased by 16.381% and 10.41% respectively, compared with Kim’s method. It means that the proposed method is successful increase the biometrics performance by reducing the error rates. Creator An entity primarily responsible for making the resource Prasti Eko Yunanto, Ari Moesriami Barmawi Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i2.1015 Publisher An entity responsible for making the resource available Faculty of Computer Science Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 2022-07-02 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource e-ISSN : 2502-9274 printed ISSN : 2088-7051 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 Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information) Authentication Biometrics identification keystroke dynamic https://repository.horizon.ac.id/files/original/d4f0d5fc780103bd8a1466e79b45ad46.pdf 94bc48a3e8ad650cda55f002d9a31719 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. 15 NO. 2 (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 Improving Recognition of SIBI Gesture by Combining Skeleton and Hand Shape Features Subject The topic of the resource SIBI, Long Short Term Memory, Gated Recurrent Unit, Feature Concatenation Description An account of the resource SIBI (Sign System for Indonesian Language) is an official sign language system used in school for hearing impairment students in Indonesia. This work uses the skeleton and hand shape features to classify SIBI gestures. In order to improve the performance of the gesture classification system, we tried to fuse the features in several different ways. The accuracy results achieved by the feature fusion methods are, in descending order of accuracy: 88.016%, when using sequence-feature-vector concatenation, 85.448% when using Conneau feature vector concatenation, 83.723% when using feature-vector concatenation, and 49.618% when using simple feature concatenation. The sequence-feature-vector concatenation techniques yield noticeably better results than those achieved using single features (82.849% with skeleton feature only, 55.530% for the hand shape feature only). The experiment results show that the combined features of the whole gesture sequence can better distinguish one gesture from another in SIBI than the combined features of each gesture frame. In addition to finding the best feature combination technique, this study also found the most suitable Recurrent Neural Network (RNN) model for recognizing SIBI. The models tested are 1-layer, 2-layer LSTM, and GRU. The experimental results show that the 2-layer bidirectional LSTM has the best performance. Creator An entity primarily responsible for making the resource Erdefi Rakun and Noer Fitria Putra Setyono Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i2.1014 Publisher An entity responsible for making the resource available Faculty of Computer Science Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 2022-07-02 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource e-ISSN : 2502-9274 printed ISSN : 2088-7051 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 Jurnal IlmuKomputer dan Informasi (Journal of Computer Science and Information) Feature Concatenation Gated recurrent unit Long Short Term Memory SIBI https://repository.horizon.ac.id/files/original/adc49a9261f0dbb0dda3edbe18b43aa7.png 253ebe2ac3663341ee1aa4d7d237754f 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. 15 NO. 2 (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 Jurnal IlmuKomputer dan Informasi (Journal of Computer Science and Information)