1 10 7 https://repository.horizon.ac.id/files/original/82ad62cb7132e6d8ab13aa6010b342ff.pdf 6cb4c44d4a0cb7518bd27699bb9fedd3 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. 2 (2023) 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 Encoder-Decoder with Atrous Spatial Pyramid Pooling for Left Ventricle Segmentation in Echocardiography Subject The topic of the resource Echocardiography, Left Ventricle Segmentation, Deep Learning, DeeplabV3+, U-Net Description An account of the resource Assessment of cardiac function using echocardiography is an essential and widely used method. Assessment by manually labeling the left ventricle area can generally be time-consuming, error-prone, and has inter�observer variability. Thus, automatic delineation of the left ventricle area is necessary so that the assessment can be carried out effectively and efficiently. In this study, encoder-decoder based deep learning model for left ventricle segmentation in echocardiography was developed using the effective CNN U-Net encoder and combined with the deeplabv3+ decoder which has efficient performance and is able to produce sharper and more accurate segmentation results. Furthermore, the Atrous Spatial Pyramid Pooling module were added to the encoder to improve feature extraction. Tested on the Echonet-Dynamic dataset, the proposed model gives better results than the U-Net, DeeplabV3+, and DeeplabV3 models by producing a dice similarity coefficient of 92.87%. The experimental results show that combining the U-Net encoder and DeeplabV3+ decoder is able to provide increased performance compared to previous studies. Creator An entity primarily responsible for making the resource Fityan Azizi, Mgs M Luthfi Ramadhan, Wisnu Jatmiko Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v16i2.1165 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  2023-07-03 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) deep learning DeeplabV3+ echocardiography Left Ventricle Segmentation, U-Net https://repository.horizon.ac.id/files/original/4e66429152e81b8bef4b04da68fa4dc7.pdf a2ffc930bbefb845119684b9d826ad67 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. 2 (2023) 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 Fine Tuning of Interval Configuration for Deep Reinforcement Learning Based Congestion Control Subject The topic of the resource congestion control, deep reinforcement learning, interval duration Description An account of the resource It is apparent that various internet services in today’s digital ecosystem effectuate different types of networks’ quality of services (QoS) requirements. This condition, in fact, adds another level of complexity to the current network congestion control protocols. Therefore, it drives the adoption of deep reinforcement learning to improve the protocols’ adaptability to the dynamic networks’ QoS requirements. In this case, the state-of-the-art works on congestion control protocols, formulate the markov decision process (MDP) by transforming the congestion control pattern from the saw tooth congestion window to the staircase sending rate per-interval cycles. This approach treats congestion control as a sequential decision-making process that fits reinforcement learning. However, the interval configuration parameter that gives the optimum QoS has not been empirically studied. In this work, we present an extensive study on various interval configuration parameters for the deep reinforcement learning-based congestion control agent. Our work shows that various interval configuration, which consists of the RTT estimator and the n parameter, results in different QoS. The experiment shows that the RTTjk has significantly higher throughput than RTTewma and RTTmin−f iltered in various network conditions. Furthermore, we found that the RTTjk with n = 2.0 is superior to other configurations in almost all networking scenarios. Whereas the RTTjk with n = 1.0 is optimal for a network environment with fixed bandwidth scenario. Creator An entity primarily responsible for making the resource Haidlir Achmad Naqvi, Muhammad Hafizhuddin Hilman, Bayu Anggorojati Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v16i2.1159 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  2023-07-03 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) Congestion control deep reinforcement learning interval duration https://repository.horizon.ac.id/files/original/ef79ce9f1a1d53a577c2a1e2114f90b8.pdf 4733089d102c1ed26cbf3323185bdf42 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. 2 (2023) 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 Biometric System for Person Authentication Using Retinal Vascular Branching Pattern Subject The topic of the resource Biometric, Blood Vessels, , Branches, Pattern, Retina. Description An account of the resource The person’s retina has its uniqueness that can be used as biometric recognition. The use of the retina as a marking feature in biometrics is more accurate in making calls, verification, and authentication. Retinal biometric characteristics are unique and difficult to manipulate, thus making the retinal biometric system one of the most reliable biometrics compared to other biometric characteristics. The retinal biometric system can be formed using extracted retinal vessels. The difficulty in extracting retinal vessels is a characteristic of retinal vessels. itself includes (central artery, central branch artery, central vein and central branch vein), the ratio of the thickness ratio between the different retinal arteries and veins (2:3), the location of the retinal artery and vein and the color. This complexity often results in errors in the retinal blood vessel extraction process, where not all blood vessel objects can be extracted properly which can reduce the accuracy of the retinal biometric system. This study will address the problem of extracting retinal vessels by proposing the use of an extraction method to produce truly unique retinal features to be included in the retinal biometric system by tracing all branches of the retinal vessels (consisting of: bifurcation, trifurcation and crossover). ). The accuracy results show that 99.81% of the images were correctly detected. The blood pattern is obtained by doing extraction which includes the preprocessing stage and is continued by doing the blood extraction stage. This pattern extraction result is used as a unique pattern to be included in the feature vector of the biometric system in identifying person based on the retina. Creator An entity primarily responsible for making the resource Diana Tri Susetianingtias, Sarifuddin Madenda, Rodiah, and Rini Arianty Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v16i2.1156 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  2023-07-03 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) Biometric Blood Vessels Branches pattern Retina https://repository.horizon.ac.id/files/original/75d512581df83a6e29dc96bd4b55836c.pdf 32f60c5716026e6699ed3b7bb7019538 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. 2 (2023) 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 A Hybrid Virtual Assistant for Legal Domain Based on Information Retrieval and Knowledge Graphs Subject The topic of the resource Law; Virtual Assistant; Information Retrieval; Knowledge Graph Description An account of the resource Virtual assistants have gained popularity across various domains, including the legal field, where they serve to offer guidance and aid in the form of law retrieval. In this research, our aim is to develop a legal virtual assistant that combines knowledge graphs (KGs) and information retrieval (IR) techniques. This hybrid approach allows us to provide accurate answers extracted from structured interconnected data while simultaneously cater to a diverse range of legal inquiries. We categorize these inquiries into a few distinct use cases: definition lookup, law component lookup, sanctions, and domain knowledge. Our system encompasses a chatbot platform, knowledge graph querying, and information retrieval. Specifically, we construct a VA system over a legal knowledge graph pertaining to the Indonesian Act concerning Manpower or Labor (UU Ketenagakerjaan) and the Indonesian Act concerning the Creation of Jobs (UU Cipta Kerja). This marks the creation of the first legal virtual assistant in the Indonesian context that combines KG and IR methodologies. To evaluate the effectiveness of our prototype system, we conduct tests using a variety of labor law-related questions, ranging in difficulty. The integration of knowledge graphs and information retrieval proves to significantly improve the support provided for a wide range of potential applications in the legal field. Creator An entity primarily responsible for making the resource Douglas Raevan Faisal, Fariz Darari, Muhammad Ilham Al Ghifari, Muhammad Zuhdi Zamrud, Marcellino Chris O’Vara, Berty Chrismartin Lumban Tobing, On Lee Source A related resource from which the described resource is derived : http://dx.doi.org/10.21609/jiki.v16i2.1152 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 2023-07-03 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) Information retrieval Knowledge Graph Law Virtual Assistant https://repository.horizon.ac.id/files/original/3a1d0aa076aad70e57f74fa754016068.pdf d3465a63897cbaca9af4b0b61a17657f 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. 2 (2023) 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 Yoga Pose Rating using Pose Estimation and Cosine Similarity Subject The topic of the resource Yoga, Pose Estimation, Resnet, Cosine Similarity Description An account of the resource One type of exercise that many people do today is yoga. However, doing yoga yourself without an instructor carries a risk of injury if not done correctly. This research proposes an application in the form of a website that can assess the accuracy of a person's yoga position, by using ResNet for pose estimation and cosine similarity for calculating the similarity of positions. The application will recognize a person's body pose and then compare it with the poses of professionals so that the accuracy of their position can be assessed. There are three types of datasets used, the first is the COCO dataset to train a pose estimation model so that it can recognize someone's pose, the second is a reference dataset that contains yoga poses performed by professionals, and the third is a dataset that contains pictures of yoga poses that are considered correct. There are 9 yoga poses used, namely Child's Pose, Swimmers, Downdog, Chair Pose, Crescent Lunge, Planks, Side Plank, Low Cobra, Namaste. The optimal pose estimation model has a precision value of 87% and a recall of 88.2%. The model was obtained using the Adam optimizer, 30 epochs, and a learning rate of 0.0001. Creator An entity primarily responsible for making the resource Ani Dwi Astuti, Tita Karlita, Rengga Asmara Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v16i2.1151 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 2023-07-03 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) Cosine Similarity Pose Estimation ResNet Yoga https://repository.horizon.ac.id/files/original/9cc51899e537cd002f55c56648e11fdd.pdf ca618f6010896991155c8449e68cce2f 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. 2 (2023) 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 Knowledge Management for Electronic-Based Government System Using Semantic Thesaurus Subject The topic of the resource SPBE, thesaurus, ISO 25964, SKOS, semantic, e-government, word2vec, doc2vec Description An account of the resource Sistem Pemerintahan Berbasis Elektronik (SPBE), the electronic-based government system, is Indonesia’s e�government policy providing services to citizens through information and communication technology. Knowledge containing SPBE must be managed in various ways, one of which is the creation of an SPBE thesaurus to facilitate access and search for SPBE-related items using words or terms about it. In this study, we provide an overview of the thesaurus development process that has complied with the ISO 25964 standard and uses the Simple Knowledge Organization System (SKOS) as the application of the thesaurus in the web environment. Basic concepts or related terms and relationships between concepts have been linked with similar concepts in other thesauri that have existed before. This research also looks at the process of automating the recognition of related terms in internet articles using Word2Vec and Doc2Vec. In the process of adding terms, we discover challenges in filtering terms, determining relationships between terms, and determining reciprocal relationships between terms. Creator An entity primarily responsible for making the resource Nuraisa Novia Hidayati, Agoeng Srimoeljanto Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v16i2.1148 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  2023-07-03 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) doc2vec e-Government ISO 25964 semantic SKOS SPBE thesaurus word2vec https://repository.horizon.ac.id/files/original/58a2ca5739d7cfb6c4a525b4bb8709ab.pdf fce55d6c8a2a3a7987ffb8a06d51a88b 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. 2 (2023) 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 Design and Development of EcoSense: Android-Based Incentivized Environmental Campaign App Subject The topic of the resource environment, campaign, incentivized, Android Description An account of the resource This research paper presents the design and development of EcoSense, an Android-based incentivized environmental campaign app, using the Design Science Research Methodology (DSRM). The DSRM approach involved six steps: problem identification, objective definition, design and development, demonstration, and evaluation. The problem of insufficient participation in environmental activities in Indonesia was identified using the Five Whys method, and user requirements were collected through an online survey. Various design artifacts were created to ensure the app is user-friendly, and the app was evaluated based on user engagement and participation. The results suggested that the app has the potential to effectively engage users in environmental campaigns, as evidenced by the relatively high retention and conversion rates. The study has some limitations, such as a small sample size and limited evaluation metrics, but future research can address these limitations and expand on the findings. Creator An entity primarily responsible for making the resource Deddy Romnan Rumapea, Kenrick Tandrian, Rivano Ardiyan Taufiq Kurniawan, Mirsa Salsabila, Darren Ngoh, Kenji Marwies, Bukhori Muhammad Aqid, Ade Azurat Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v16i2.1144 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 2023-07-03 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) Android campaign Environment incentivized