1 10 7 https://repository.horizon.ac.id/files/original/5bdd2ae8fd3042db248fe390ce0a0bc4.pdf b2692b08667d0977b37025e0d5650bd2 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 6 (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 Telegram Bot as a Data Collection Tool for Progress Reports in Area Mapping Progress Monitoring System Subject The topic of the resource chatbot, instant messaging, data collection tool, monitoring system, surveyor, real-time Description An account of the resource In the Area Mapping Project (Preparation for the 2020 Population Census), there is monitoring and collecting data process on the progress of activities in the field. There are weaknesses in data collection on the progress of activities in the field; The manual recapitulation of progress reporting makes the progress data not displayed in real-time, the SMS Gateway is often interrupted, and progress data collection through the monitoring website is less effective if reported directly by field officers. Telegram Bot is used as a data collection tool for field progress reports on Area Mapping activities to overcome these weaknesses. This study aims to prove that Telegram Bot can be used as a real-time data collection tool, has good performance, and is acceptable to users. Telegram Bot is integrated with Monitoring Website into one system and database in this research. This system uses PHP, Yii2, and MySQL, and communication between the web server and Telegram Server uses the webhook method. Based on the Black Box test results, all functions in this system run as expected. The average bot response time was 7.72 seconds for images and 2.25 seconds for text data in the performance test. In the usability test, Telegram Bot obtained a SUS Score of 66 and an NPS of 12.195. These results show that Telegram Bot can be used as a real�time data collection tool, has good performance, and is well accepted by users. Creator An entity primarily responsible for making the resource Apriela Trirahma Publisher An entity responsible for making the resource available BPS - Statistics of Kepulauan Bangka Belitung Province Date A point or period of time associated with an event in the lifecycle of the resource 30-12-2021 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/980d17e846a9e69222c312fa07a4ba8c.pdf 886bd51097743cfe11640338781fd28f 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 6 (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 Pengembangan Embedded Device Berbasis PLC untuk Simulator Rejection System dengan Penambahan Human Machine Interface Subject The topic of the resource analogy of conveyor, HMI, PLC, simulator of rejection system. Description An account of the resource Changes to the simulator rejection system from the previous research were carried out by replacing all sensors, drive motors, PLC systems, and adding HMI systems. The objectives in this research, namely (i) changing and developing a rejection system simulator, creating a ladder-based program structure and configuring HMI systems and (ii) measuring the performance of the simulators. Rejection system simulator is fabricated and reassembled, ladder-based syntax into PLCs and HMI is also configured, and observing the performance is done through the HMI layer. The results of programming is carried out through (i) providing software for PLCs, (ii) programming the PLC system, (iii) compiling and uploading programs from PC to PLC, (iv) configuring PLC and HMI via ethernet, and (v) compiling and uploading the program structure from PC to HMI. The performance for observing the condition of the bottle cap through the HMI is observed when (i) synchronization between the simulator system and the HMI-assisted PLC control, (ii) the reading of the sensors installed on the simulator, and (iii) the rotation process of the rejector arm. Overall, the rejection system simulator with a PLC-based assisted by HMI can be used as a process simulation against the implementation of the rejection system. Creator An entity primarily responsible for making the resource Riyandar1 , Muhamad Wildan2 , Arief Goeritno3* , Joki Irawan3 Publisher An entity responsible for making the resource available Universitas Ibn Khaldun Bogor Date A point or period of time associated with an event in the lifecycle of the resource : 30-12-2021 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/86fa8000a9f0be087c994b7afc9ce2a1.pdf 63b621e108d3418cd6a1969a7bbbf0a4 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 6 (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 BGP dan Resource Public Key Infrastructure menggunakan BIRD untuk Keamanan Routing Subject The topic of the resource Border Gateway Protocol, Resource Public Key Infrastructure, Bird Internet Routing Daemon, RPKI Validator Description An account of the resource The validity of the routing advertisements sent by one router to another is essential for Internet connectivity. To perform routing exchanges between Autonomous Systems (AS) on the Internet, a protocol known as the Border Gateway Protocol (BGP) is used. One of the most common attacks on routers running BGP is prefix hijacking. This attack aims to disrupt connections between AS and divert routing to destinations that are not appropriate for crimes, such as fraud and data breach. One of the methods developed to prevent prefix hijacking is the Resource Public Key Infrastructure (RPKI). RPKI is a public key infrastructure (PKI) developed for BGP routing security on the Internet and can be used by routers to validate routing advertisements sent by their BGP peers. RPKI utilizes a digital certificate issued by the Certification Authority (CA) to validate the subnet in a routing advertisement. This study aims to implement BGP and RPKI using the Bird Internet Routing Daemon (BIRD). Simulation and implementation are carried out using the GNS3 simulator and a server that acts as the RPKI validator. Experiments were conducted using 4 AS, 7 routers, 1 server for BIRD, and 1 server for validators, and there were 26 invalid or unknown subnets advertised by 2 routers in the simulated topology. The experiment results show that the router can successfully validated the routing advertisement received from its BGP peer using RPKI. All invalid and unknown subnets are not forwarded to other routers in the AS where they are located such that route hijacking is prevented. Creator An entity primarily responsible for making the resource Valen Brata Pranaya1 , Theophilus Wellem2 Publisher An entity responsible for making the resource available Universitas Kristen Satya Wacana Date A point or period of time associated with an event in the lifecycle of the resource 30-04-2021 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/c2456f65f67cfe19d3f19dccb73f2b2c.pdf d243ac0a5b599ec371b291a9d9f58410 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 6 (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 Penerapan Convolutional Neural Networks untuk Mesin Penerjemah Bahasa Daerah Minangkabau Berbasis Gambar Subject The topic of the resource Convolutional Neural Networks, Translation, Indonesia Language, Local Language Minangkabau, Optical Character Recognition (OCR) Description An account of the resource One of efforts by the Indonesian people to defend the country is to preserve and to maintain the regional languages. The current era of modernity makes the regional language image become old-fashioned, so that most them are no longer spoken. If it is ignored, then there will be a cultural identity crisis that causes regional languages to be vulnerable to extinction. Technological developments can be used as a way to preserve regional languages. Digital image-based artificial intelligence technology using machine learning methods such as machine translation can be used to answer the problems. This research will use Deep Learning method, namely Convolutional Neural Networks (CNN). Data of this research were 1300 alphabetic images, 5000 text images and 200 vocabularies of Minangkabau regional language. Alphabetic image data is used for the formation of the CNN classification model. This model is used for text image recognition, the results of which will be translated into regional languages. The accuracy of the CNN model is 98.97%, while the accuracy for text image recognition (OCR) is 50.72%. This low accuracy is due to the failure of segmentation on the letters i and j. However, the translation accuracy increases after the implementation of the Leveinstan Distance algorithm which can correct text classification errors, with an accuracy value of 75.78%. Therefore, this research has succeeded in implementing the Convolutional Neural Networks (CNN) method in identifying text in text images and the Leveinstan Distance method in translating Indonesian text into regional language texts Creator An entity primarily responsible for making the resource Mayanda Mega Santoni1 , Nurul Chamidah2 , Desta Sandya Prasvita3 , Helena Nurramdhani Irmanda4 , Ria Astriratma5 , Reza Amarta Prayoga Publisher An entity responsible for making the resource available UPN Veteran Jakarta Date A point or period of time associated with an event in the lifecycle of the resource 30-12-2021 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/269ca8f0a9a4eba5d787ad61120526c1.pdf 5a3ccb67c29a1795f4382414c69d1c83 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 6 (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 Perbandingan Metode CBR dan Dempster-Shafer pada Sistem Pakar Terintegrasi Layanan Kesehatan Subject The topic of the resource expert system, health care system, infectious disease, Dempster-Shafer, Case Based Reasoning Description An account of the resource Infectious disease is a very dangerous disease with a high mortality rate. Delays in handling the spread of an infectious disease can be minimized using an expert system. This study uses an expert system as a disease consulting service that is integrated with the health care system. Integration with the health care system is used for the knowledge acquisition process. The knowledge base on the expert system uses patient medical record data obtained through the health care system. The expert system can diagnose infectious diseases of sore throat (Pharyngitis), diphtheria, dengue fever, Typhoid fever, tuberculosis, and leprosy. The knowledge acquisition process produces 43 symptoms. These symptoms are used to diagnose new cases using Case-Based Reasoning (CBR) and Dempster-Shafer methods. In the CBR method, the similarity measurement process is determined by comparing the K-Nearest Neighbor, Minkowski Distance, and 3W-Jaccard similarity measurement methods. The expert system obtains accuracy values for the CBR K-Nearest Neighbor, CBR Minkowski Distance, and CBR 3W-Jaccard methods at a threshold of 70%, respectively 65.71%, 80%, and 85.71%. The average length of retrieve time required for each similarity method is 0.083s, 0.107s, and 6.325s, respectively. While the diagnosis of disease with Dempster-Shafer gets an accuracy value of 88.57%. Creator An entity primarily responsible for making the resource Istiadi1 , Emma Budi Sulistiarini2 , Rudy Joegijantoro3 , Affi Nizar Suksmawati4 Publisher An entity responsible for making the resource available Universitas Widyagama Malang Date A point or period of time associated with an event in the lifecycle of the resource 30-12-2021 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/73bae65d49363be74b742493eb4bce7a.pdf bf08b6b994fd950fff07e86ffb1811b6 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 6 (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 Klasifikasi Penyakit Padi berdasarkan Citra Daun Menggunakan Model Terlatih Resnet101 Subject The topic of the resource Classification, Disease, Rice, Image, Pretrained model, ResNet101. Description An account of the resource Rice is a staple food source for most countries in the world, including Indonesia. The problem of rice disease is a problem that is quite crucial and is experienced by many farmers. Approximately 200,000 - 300,000 tons per year the amount of rice attacked by pests in Indonesia. Considerable losses are caused by the disease of rice plants that are too late to be diagnosed so that they reach a severe stage and cause crop failure. Ignorance of farmers as well as limited and lack of information about diseases and proper treatment are factors that cause delays in handling rice diseases. Therefore, in this study the developed model can classify three types of rice plant diseases using Rice Leaf Disease images. The three types of disease include: Bacterial Leaf Blight, Brown Spot, and Leaf Smut. The model developed using the transfer learning method with a pretrained model of Resnet101 with additional architectural layer in the Fully Connected Layer section in the form of: Dense Layer, Dropout Layer, and Batch Normalization Layer. The proposed method shows a classification performance of 100% on validation data, with a loss value of 5.61%. Creator An entity primarily responsible for making the resource Ulfah Nur Oktaviana 1 , Ricky Hendrawan 2 , Alfian Dwi Khoirul Annas3 , Galih Wasis Wicaksono4 Publisher An entity responsible for making the resource available Universitas Muhammadiyah Malang Date A point or period of time associated with an event in the lifecycle of the resource : 31-12-2021 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/9b081c2cdeff8a4ba5ab91cf92d24367.pdf 3fc99e5b076b1f37d71e8ba6bdbab011 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 6 (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 Sistem Keamanan Gedung Menggunakan Kinect Xbox 360 Dengan Metode Skeletal Tracking Subject The topic of the resource Kinect Xbox 360, Skeletal Tracking, Internet of Things Description An account of the resource The incidence of fire and theft is very threatening and causes disruption to people's lifestyles, both due to natural and human factors resulting in loss of life, damage to the environment, loss of property and property, and psychological impacts. The purpose of this study is to create a building security system using Kinect Xbox 360 which can be used to detect fires and loss of valuable objects. The data transmission method uses the Internet of Things (IoT) and skeletal tracking. Skeletal detection uses Arduino Uno which is connected to a fire sensor and Kinect to detect suspicious movements connected to a PC. Kinect uses biometric authentication to automatically enter user data by recognizing objects and detecting skeletons including height, facial features and shoulder length. The ADC (Analog to Digital Converter) value of the fire sensor reading has a range between 200-300. The fire sensor detects the presence of fire through optical data analysis containing ultraviolet, infrared or visual images of fire. The data generated by Kinect by detecting the recognition of the skeleton of the main point of the human body known as the skeleton, where the reading point is authenticated by Kinect from a range of 1.5-3 meters which is declared the optimal measurement, and if a fire occurs, the pump motor will spray water randomly. to extinguish the fire that is connected to the internet via the wifi module. The data displayed is in the form of a graph on the Thingspeak cloud server service. Notification of fire and theft information using the delivery system from input to database Creator An entity primarily responsible for making the resource Hamdi Alchudri1 , Zaini2 Publisher An entity responsible for making the resource available Universitas Andalas Date A point or period of time associated with an event in the lifecycle of the resource 30-12-2021 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