2 10 16 https://repository.horizon.ac.id/files/original/e7c318723a187aa461a4ee8906a4a222.pdf f61d0013cde453a0c604cbc29d9f55b9 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 5 NO 3 (2021) 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 Penentuan Klaster Koridor TransJakartadengan Metode Majority Voting pada Algoritma Data Mining Subject The topic of the resource covid-19, transjakarta, clustering, davies bouldin index, majority voting Description An account of the resource The Covid-19 pandemic has made many changes in the patterns of community activity. Large-Scale Social Restrictions were implemented to reduce the number of transmission of the virus. This clearly affects the mode of transportation. The mode of transportation makes new regulations to reduce the number of passenger capacities in each fleet, for example, TransJakarta services. This study will categorize the TransJakarta corridors before and during the Covid-19 pandemic. The clustering method of K-Means and K-Medoids is used to obtain accurate calculation results. The calculations are performed using Microsoft Excel, Rapid Miner, and Python programming language. The clustering results obtained that using K-Means algorithm before Covid-19 pandemic, an optimum number of clusters is 3 clusters with DBI (Davies Bouldin Index) value is 0.184, and during Covid-19 pandemic, the optimum number of clusters is 2 clusters with DBI value is 0.188. Meanwhile, when using the K-Medoids algorithm before the Covid-19 pandemic, an optimum number of clusters is 3 clusters with the DBI value is 0.200, and during the Covid-19 pandemic, an optimum number of clusters is 4 clusters with the DBI value is 0.190. The final cluster is determined using the majority voting approach from all the tools used. Creator An entity primarily responsible for making the resource Arief Wibowo1, Moh Makruf2,Inge Virdyna3,Farah Chikita Venna4 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Budi Luhur Date A point or period of time associated with an event in the lifecycle of the resource 26 juni 2021 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/b8048c59473ab0725a602c02bbca3b47.pdf 5b18b18be7bfb82c0da828e70c8681b8 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 5 NO 3 (2021) 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 Prediksi Indeks BEI dengan EnsembleConvolutional Neural Networkdan Long Short-Term Memory Subject The topic of the resource BEIindexes, ensemble, Convolutional Neural Network, Long Short-Term Memory, deep learning, time series data Description An account of the resource he Indonesian Stock Exchange (IDX) stock market index isone of the main indicators commonly used as a reference for national economic conditions. The value of the stock market index is often being used by investment companies and individual investors to help making investment decisions. Therefore, the ability to predict the stock market index value is a critical need. In the fields of statistics and probability theory as well as machine learning, various methods have been developed to predict the value of the stock market index with a good accuracy. However, previous research results have found that no one method is superior to other methods. Thisstudy proposes an ensemble model based on deep learning architecture, namely Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM), called the CNN-LSTM. To be able to predict financial time series data, CNN-LSTM takes feature from CNN for extraction of important features from time series data, which are then integrated with LSTM feature that is reliable in processing time series data. Resultsof experiments on the proposed CNN-LSTM model confirm that the hybrid model effectively provides better predictive accuracy than the stand-alone time series data forecasting models, such as CNN and LSTM Creator An entity primarily responsible for making the resource Harya Widiputra1, Adele Mailangkay2, Elliana Gautama Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Perbanas Institute Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 2021 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/ee25cdf936aa27e358661c18e6c6e740.pdf fc9aa4d4de618608b37e67525e58664b 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 5 NO 3 (2021) 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 Implementasi Teknologi BlockchainProof of WorkPada Penelusuran Supply ChainProdukKomputer Subject The topic of the resource blockchain, product, supply chain, proof of work, computer Description An account of the resource In recent times, the supply chain has developed into a large ecosystem. Various products moving from party to party require cooperation between stakeholders in managing the data generated. The problem is that every company has its own transaction records that can be inconsistent and their storage is centralized and not integrated between companies. This makes transaction records easy to falsify. Efficient data management is needed from the producer to the store so that consumers can trust the product. Therefore, the authors designed a product tracking system using blockchainby implementing proof of work (PoW) as the consensus algorithm, SHA-3 256 as data security, Mongo database as cloud-based data storage and QR Code as the output. As a result, transaction data from producers, distributors to retail stores are storedcompletely in MongoDB which is a cloud-based database, then the resulting QR Code can be used to view details of producers, distributors to retail stores that sell them. The simulation and trial results show the product tracing system design is successful as expected. Creator An entity primarily responsible for making the resource Annisya1, Emy Haryatmi2 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Gunadarma Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 2021 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/53f159c20b7b59f9c236242695c2116c.pdf 40d65a2070894594750010f2c14ef520 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 5 NO 3 (2021) 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 The Number of Tourists Based on Backpropagation Algorithm Subject The topic of the resource Artificial Neural Networks, BackpropagationAlgorithm, Prediction, Tourist Description An account of the resource The number of tourists always fluctuates every month, as happened in Kaliadem Merapi, Sleman. The purpose of this research is to develop a prediction system for the number of tourists based on artificial neural networks. This study uses an artificial neural network for data processing methods with the backpropagation algorithm. This study carried out two processes, namely the training process and the testing process with stages consisting of: (1) Collecting input and target data, (2) Normalizinginput and target data, (3) Creating artificial neural network architecture by utilizing GUI (Graphical UserInterface)Matlabfacilities. (4) Conducting training and testing processes, (5) Normalizing predictive data, (6) Analysis of predictive data. In the data analysis, the MSE (Mean Squared Error) value in the training process is 0.0091528 and in the testingprocess is0.0051424. Besides, the validity value of predictive accuracy in the testing process is around 91.32%. The resulting MSE (Mean Squared Error) value is relatively small,and the validity value of prediction accuracy is relatively high, so this system can be used to predict the number of tourists in Kaliadem Merapi, Sleman Creator An entity primarily responsible for making the resource Dwi Marlina1, Fatchul Arifin2 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Yogyakarta State University Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 2021 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/0e2dc4d63201c68f3a61ead04f083b35.pdf df3533b6ebbdc8dce71d4f5c3b781f37 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 5 NO 3 (2021) 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 Identifikasi Level Pengelolaan Tata Kelola SIPERUMKIM Kota Salatiga berdasarkanCOBIT 2019 Subject The topic of the resource COBIT 2019, Design Factor, IT Governance, Capability Level, Gap Description An account of the resource SIPERUMKIM is the digitization process of public service licensing recommendations for housing implementation. The utilization of information technology governance is used to facilitate monitoring and evaluating the performance of SIPERUMKIM information technology which has been implemented in Housing and Settlement Area in Salatiga city. Information technology governance is a process that can manage investment decisions related to information technology within the company to achieve goals and meet company needs. The use of COBIT 2019 analysis in information technology governance aims to help organizations achieve risk optimization, governance, and information technology management. The results of this study are in the design form of corporate information technology governance and knowing the important process recommendations for the Department of Housing and Settlement of the City of Salatiga.Thesethree important process recommendations areAPO12, DSS02, and DSS03 Creator An entity primarily responsible for making the resource Adila Safitri1, Imam Syafii2,Kusworo Adi Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Universitas Diponegoro Date A point or period of time associated with an event in the lifecycle of the resource 20 Juni 2021 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/686473e018a68cddf5eac9e36a18d58e.pdf a4f41a2c655a7e79e0cb278b8a10a94c 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 5 NO 3 (2021) 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 Adaptive Streaming Server dengan FFMPEG dan Golang Subject The topic of the resource Adaptive Streaming, Video Streaming, DASH, FFMPEG, Golang Description An account of the resource Quality of experience (QoE) when accessing video streaming becomes a challenge in varieties of network bandwidth/speed. Adaptive streaming becomes an answer to gain good QoE. An architecture system of the adaptive streaming server with Dynamic Adaptive Streaming over HTTP (DASH) was proposed. The system was consistsof two services e.g transcoding and streaming. Transcoding service encodes an audio file, multi-bitrates video files, and manifest.mpd files. Streaming service serves client streaming requests that appropriate to client networkprofiles. The system is built using the Golang programming environment and FFMPEG. Transcoding service has some execution mode(serial and concurrent) and passing mode (1 pass and 2 passes). The transcoding service test results show that concurrent execution is faster 11,5% than the serial execution and transcoding using 1 pass is faster 46,95% than 2 passes but the bitrate of output video lower than the determinate bitrate parameter. The streaming service has a good QoE. In the 5 scenarios, buffer level=0happens 5 times, and its total duration is 64 seconds. Buffer level=0 happens when extreme changes happen in network speed from fast to too slow Creator An entity primarily responsible for making the resource David Kristiadi1, Marwiyati2 Source A related resource from which the described resource is derived https://jurnal.iaii.or.id/index.php/RESTI/issue/view/23 Publisher An entity responsible for making the resource available Sekolah Tinggi Multi Media Yogyakarta Date A point or period of time associated with an event in the lifecycle of the resource 20 juni 2021 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text