1 10 8 https://repository.horizon.ac.id/files/original/27ed6f687b95f20249c38e76ed7ce2df.pdf 5c1958fa530a90ab57edff1c0b54fcf0 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. 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 SGCF: Inductive Movie Recommendation System with Strongly Connected Neighborhood Sampling Subject The topic of the resource recommendation system, collaborative filtering, graph neural network Description An account of the resource User and item embeddings are key resources for the development of recommender systems. Recent works has exploited connectivity between users and items in graphs to incorporate the preferences of local neighborhoods into embeddings. Information inferred from graph connections is very useful, especially when interaction between user and item is sparse. In this paper, we propose graphSAGE Collaborative Filtering (SGCF), an inductive graph-based recommendation system with local sampling weight. We conducted an experiment to investigate recommendation performance for SGCF by comparing its performance with baseline and several SGCF variants in Movielens dataset, which are commonly used as recommendation system benchmark data. Our experiment shows that weighted SGCF perform 0.5% higher than benchmark in NDCG@5 and NDCG@10, and 0.8% in NDCG@100. Weighted SGCF perform 0.79% higher than benchmark in recall@5, 0.4% increase for recall@10 and 1.85% increase for recall@100. All the improvements are statistically significant with p-value < 0.05. Creator An entity primarily responsible for making the resource Jatmiko Budi Baskoro, Evi Yulianti Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i1.1066 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 022-02-27 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) Collaborative Filtering graph neural network Recommendation system https://repository.horizon.ac.id/files/original/fdf73f895fe711fb65adfbe1a310024f.pdf e8777b0a4d38093697987b0c78efb811 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. 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 Epidemic Data Analysis of Three Variants of COVID-19 Spread in Indonesia Subject The topic of the resource effective reproductive number, COVID-19, exponential, Bayesian, infectious disease Description An account of the resource Three variants of COVID-19 had been found in Indonesia. A control strategy may rely on the transmission rate of the variant. This study aims to investigate how the variants spread in Indonesia by computing a basic and effective reproduction number on the national and province scale. The basic reproduction number shows the indicator of initial transmission rate of alpha variant computed by an exponential growth rate model. The effective reproduction number describes the dynamic of the transmission rate estimated based on a Bayesian approach. This study revealed that each variant shows different characteristics. The alpha variant of COVID-19 in Indonesia was mainly initiated from big cities, then it spread to all provinces quickly because the control strategies were not established well at the beginning. A rapid increase of the effective reproduction number about July 2021 showed a novel delta variant, but it could be managed quite well by a large number of testing and stronger restrictions. Before the end of 2021, a novel variant omicron was also shown by the steeper change of the effective reproduction number. Thus, the variant spread rate can be estimated by how steep the effective reproduction number change is. Creator An entity primarily responsible for making the resource Inna Syafarina, Taufiq Wirahman, Syam Budi Iryanto, Arnida L. Latifah Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i1.1055 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 022-02-27 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) Bayesian COVID-19 effective reproductive number exponential Infectious disease https://repository.horizon.ac.id/files/original/1c256f4856235e5f252ada672d1e5a88.pdf 211326fdf6eec1d44c0a1ab75a4a371a 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. 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 Sentiment Analysis of COVID-19 Vaccines in Indonesia on Twitter UsingPre-Trained and Self-Training Word Embeddings Subject The topic of the resource Sentiment Analysis, Twitter, Bidirectional LSTM, Word Embedding, fastText, GloVe Description An account of the resource Sentiment analysis regarding the COVID-19 vaccine can be obtained from social media because users usually express their opinions through social media. One of the social media that is most often used by Indonesian people to express their opinion is Twitter. The method used in this research is Bidirectional LSTM which will be combined with word embedding. In this study, fastText and GloVe were tested as word embedding. We created 8 test scenarios to inspect performance of the word embeddings, using both pre-trained and self-trained word embedding vectors. Dataset gathered from Twitter was prepared as stemmed dataset and unstemmed dataset. The highest accuracy from GloVe scenario group was generated by model which used self�trained GloVe and trained on unstemmed dataset. The accuracy reached 92.5%. On the other hand, the highest accuracy from fastText scenario group generated by model which used self�trained fastText and trained on stemmed dataset. The accuracy reached 92.3%. In other scenarios that used pre-trained embedding vector, the accuracy was quite lower than scenarios that used self-trained embedding vector, because the pre-trained embedding data was trained using the Wikipedia corpus which contains standard and well-structured language while the dataset used in this study came from Twitter which contains non-standard sentences. Even though the dataset was processed using stemming and slang words dictionary, the pre-trained embedding still can not recognize several words from our dataset. Creator An entity primarily responsible for making the resource Kartikasari Kusuma Agustiningsih, Ema Utami, and Omar Muhammad Altoumi Alsyaibani Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i1.1044 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 022-02-27 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) Bidirectional LSTM fastText GloVe sentiment analysis Twitter Word Embedding https://repository.horizon.ac.id/files/original/22548aee4918fb02a4e670139167e434.pdf 69cae94daf5bb91b5ee2e2c534d42801 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. 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 Predicting Analysis of User’s Interest from Web Log Data in e-Commerce using Classification Algorithms Subject The topic of the resource user interest; web usage mining; classification; e-commerce; web log data Description An account of the resource The accelerated development of e-commerce has been a concern for businesspeople. Businesspeople should be able to gain customer interest in a variety of ways so that their companies can compete with others. Analyzing click-flow data will help organizations or firms assess customer loyalty, provide advertising privileges, and develop marketing strategies through user interests. By understanding consumer preferences, clickstream data analysis may be used to determine who is participating, assist companies in evaluating customer contentment, boost productivity, and design marketing strategies. This research was performed by defining experimental user interests using Dynamic Mining and Page Interest Estimation methods. The findings of this analysis, using three algorithms at the pattern discovery page, demonstrated that the Decision Tree method excelled in both methods. It indicated that the operational performance of the Decision Tree performed well in the assessment of user interests with two different approaches. The findings of this experiment can be used as a proposal for researching the field of web usage mining, collaborating with other approaches to achieve higher accuracy values. Creator An entity primarily responsible for making the resource Saucha Diwandari, Ahmad Tri Hidayat Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i1.1024 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 e-commerce user interest web log data web usage mining https://repository.horizon.ac.id/files/original/a96c7e982f17ef1235d4f6e649e5bb9d.pdf 599bf38d91f10c23e39c4df3ba20a0c4 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. 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 A Systematic Literature Review on SOTA Machine learning-supported Computer Vision Approaches to Image Enhancement Subject The topic of the resource Image enhancement, Machine learning, Computer vision, ML, CV Description An account of the resource Image enhancement as a problem-oriented process of optimizing visual appearances to provide easier-to�process input to automated image processing techniques is an area that will consistently be a companion to computer vision despite advances in image acquisition and its relevance continues to grow. For our systematic literature review, we consider the major peer-reviewed journals and conference papers on the state of the art in machine learning-based computer vision approaches for image enhancement. We describe the image enhancement methods relevant to our work and introduce the machine learning models used. We then provide a comprehensive overview of the different application areas and formulate research gaps for future scientific work on machine learning based computer vision approaches for image enhancement based on our results. Creator An entity primarily responsible for making the resource Marco Klaiber, Jonas Klopfer Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i1.1017 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 022-02-27 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) Computer Vision CV image enhancement machine learning MI https://repository.horizon.ac.id/files/original/9c3dafd86a15ad547fa360661bd4fd60.pdf 6a52e955c8567248685a97137123305f 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. 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 Wavelet Transformation and Spectral Subtraction Method in Performing Automated Rindik Song Transcription Subject The topic of the resource Rindik, Automatic Music Transcription, Wavelet Transformation, Spectral Subtraction Description An account of the resource Rindik is Balinese traditional music consisting of bamboo rods arranged horizontally and played by hitting the rods with a mallet-like tool called "panggul". In this study, the transcription of Rindik's music songs was carried out automatically using the Wavelet transformation method and spectral subtraction. Spectral subtraction method is used with iterative estimation and separation approaches. While the Wavelet transformation method is used by matching the segment Wavelet results with the Wavelet result references in the dataset. The results of the transcription were also synthesized again using the concatenative synthesis method. The data used is the hit of 1 Rindik rod and a combination of 2 Rindik rods that are hit simultaneously, and for testing the system, 4 Rindik songs are used. Each data was recorded 3 times. Several parameters are used for the Wavelet transformation method and spectral subtraction, which are the length of the frame for the Wavelet transformation method and the tolerance interval for frequency difference in spectral subtraction method. The test is done by measuring the accuracy of the transcription from the system within all Rindik song data. As a result, the Wavelet transformation method produces an average accuracy of 83.42% and the spectral subtraction method produces an average accuracy of 78.51% in transcription of Rindik songs. Creator An entity primarily responsible for making the resource Yuriko Christian, I Dewa Made Bayu Atmaja Darmawan Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i1.1009 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 022-02-27 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) Automatic Music Transcription Rindik Spectral Subtraction Wavelet Transformation https://repository.horizon.ac.id/files/original/378d94a0437e158ff107148ee53a1594.pdf 0637d6a75ce8283c654fd9fa8d34a49f 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. 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 Analysis of Livestock Meat Production in Indonesia Using Fuzzy C-Means Clustering Subject The topic of the resource Province in Indonesia, Livestock Meat Production, Fuzzy C-Means, Clustering,Silhouette Index Description An account of the resource The production of livestock in Indonesia is one type of food that the public can consume. Indonesia is still importing meat for food for its people. This study aims to classify provinces in Indonesia with high livestock meat production and low livestock meat production so that the government can maximize areas with high livestock meat production and can seek to increase livestock meat production in areas with low production. Clustering is needed to identify groups of livestock meat-producing provinces with high and low production. The data is grouped into 2 clusters using FCM with a silhouette index value of 0.95664, the first cluster with the highest meat production total in three provinces (West Java, Central java and east Java) and the second cluster with the lowest meat production total 31 provinces. West Java, Central java and east Java mostly work as livestock breeders due to the availability of sufficient land. Creator An entity primarily responsible for making the resource Chalawatul Ais, Abdulloh Hamid, Dian Candra Rini Novitasari Source A related resource from which the described resource is derived http://dx.doi.org/10.21609/jiki.v15i1.993 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 022-02-27 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) Clustering Fuzzy C-Means Livestock Meat Production Province in Indonesia Silhouette index https://repository.horizon.ac.id/files/original/dd5e755b080c16830e89d7ad2e485122.jpg 0e4e0bc781e9435c7e178e0ab152959a 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. 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 Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)