3 10 36 https://repository.horizon.ac.id/files/original/914375f054b6ccda7e58d94e0781d0f1.pdf 43ee7eb4034b865f47822de1c74fee51 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 5 (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 Infrastruktur Pembelajaran Daring Menggunakan Antena Unidirectional Subject The topic of the resource Online Learning, Wifi antenna, Unidirectional antenna, WELAN, Wifi extender Description An account of the resource Situation during COVID19 pandemic, requires all schools to conduct online learning. This condition is done to prevent the spread of pandemic. The problem is that the infrastructure is not fully supported. Learning in marginal areas is still constrained by the difficulty of the signal or internet connection. This research was conducted to obtain an infrastructure design that can be used in areas with minimal internet connection, or even no internet network connection. Using R&D, the research begins by designing a network device on the school side – Acces Point, also a tool to expand coverage - repeater. Furthermore, design and testing of signal amplifier antennas that can be used on the client side is carried out. For the client side, several types of amplifier antennas are made that can be used to receive Wifi frequencies. There are three types of antennas that are made and tested, namely Yagi, Yagi Cross, and cantennas. Both are Unidirectional antenna. Connection quality is measured with a Wifi analyzer device to determine network quality. As for mobile phones, it is measured using the Wifi Master Key. The result obtained is a WELAN infrastructure design which is equipped with unidirectional antenna design with a total range of 8 Km. Creator An entity primarily responsible for making the resource Rufman Iman Akbar1 , Chaerul Anwar2 , Johannes Hamonangan Siregar3 Publisher An entity responsible for making the resource available Universitas Pembangunan Jaya Date A point or period of time associated with an event in the lifecycle of the resource 24-08-2021 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/7e66fe88782f266fae197d8c5601a91a.pdf bd263585f7e7b2a138dff1a27fe7c3eb 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 5 (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 Citra Burung Lovebird Menggunakan Decision Tree dengan Empat Jenis Evaluasi Subject The topic of the resource Lovebird, ANN, Decision Tree, Precision, Recall, F-measure. Description An account of the resource Lovebird is a pet that many people in Indonesia have known. The diversity of species, coat color, and body shape gives it its charm. As well in this lovebird bird has its uniqueness of various rare colors. However, many ordinary people have difficulty distinguishing the types of lovebirds. This research is needed to improve previous study performance in classifying lovebird images using the Decision Tree J48 algorithm with 4 types of evaluation. In this case, also to reduce the stage of feature extraction to speed up the computational process. Based on available comparisons, the results obtained at the same split ratio with a comparison of 60:40 in Decision Tree J48 have the precision of 1,000, recall of 1,000, f-measure of 1,000, and accuracy value of 100%. Then the Artificial Neural Network with a split ratio of 60:40 has a precision of 0.854, recall of 0.843, f�measurement of 0.841, and an accuracy value of 84.25%. These results prove that by testing the first-level extraction on color features, Decision Tree J48 is superior in classifying images of lovebird species, and Decision Tree J48 can improve performance and produce the best accuracy Creator An entity primarily responsible for making the resource Aviv Yuniar Rahman 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 20-08-2021 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/393d5e4387c358cdb2a8ef2d54c9a596.pdf b3acbd21a34e79ed8efca290ba7c7754 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 5 (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 Semantic Approach for Big Five Personality Prediction on Twitter Subject The topic of the resource Big Five Personality, BERT, SVM, LIWC Description An account of the resource Personality provides a deep insight of someone and has an important part in someone’s job performance. Predicting personality through social media has been studied on several research. The problem is how to improve the performance of personality prediction system. The purpose of this research is to predict personality on Twitter users and increase the performance of the personality prediction system. An online survey using Big Five Inventory (BFI) questionnaire has been distributed and gathered 295 Twitter users with 511,617 tweets data. In this research, we experiment on two different methods using Support Vector Machine (SVM), and the combination of SVM and BERT as the semantic approach. This research also implements Linguistic Inquiry Word Count (LIWC) as the linguistic feature for personality prediction system. The results showed that combination of these two methods achieve 79.35% accuracy score and with the implementation of LIWC can improve the accuracy score up to 80.07%. Overall, these results showed that the combination of SVM and BERT as the semantic approach with the implementation of LIWC is recommended to gain a better performance for the personality prediction system Creator An entity primarily responsible for making the resource Ghina Dwi Salsabila1 , Erwin Budi Setiawan 2 Publisher An entity responsible for making the resource available Telkom University Date A point or period of time associated with an event in the lifecycle of the resource : 20-08-2021 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/48717f97aa5e525cc69dbf6d2e9a3eda.pdf ddc47f0128ac5928d914e79d559d62bd 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 5 (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 Prototype Sistem Pakan Ikan dan Pemantauan PH Berbasis Android dengan Metode PLC Subject The topic of the resource NodeMCU ESP 8266, Arduino Uno, Internet of Things, Android, PH Sensor Description An account of the resource During the pandemic of covid-19, betta fish cultivation is one of the income alternatives. It makes the cultivation of betta fish is increasing. However, not all cultivators can successfully cultivate betta fish. Water quality and fish feed must be maintained in order for betta fish can grow perfectly and attractive. The problems that often encountered to the betta fish cultivator is about feeding and monitoring pH levels, which is still manual. This is can failure in betta fish cultivation of the cultivators are not disciplined. To minimize it, then will be made “Prototype Fish Feeding System and PH Monitoring Based Android”. This research is used PLC method: (a) Requirements Analysis, (b) Design, and (c) Implementation. Divided into 2 functions: Automatic Betta Fish Feeding System Based Android Function using Node MCU ESP8266 and Monitoring PH Levels Function using Arduino Uno. The result from this research is the user can control the open and close feed on the servo through an android application, the system can provide a distance of the feed supply to a user in real-time by notifications, the LCD always display pH value, the buzzer provides a sound when the water quality has reached the acid or alkaline index Creator An entity primarily responsible for making the resource Maria Rosaria Oktaviani1 , Rizky Pradana2 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 20-08-2021 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/ccc1888742b1076b19e4351b7d4491d6.pdf cc5ef6cbb42510440b6608f226682d42 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 5 (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 Simulator Proses Pengisian dan Pemasangan Tutup Botol Terkendali PLC Berbantuan Miniatur Konveyor Subject The topic of the resource : A miniature of the conveyor machine, embedded system, programmable logic controller system, simulator for the process of filling and installing bottle caps. Description An account of the resource A miniature conveyor machine assisted by embedded systems and controlled by a programmable logic controller (PLC) has been fabricated with the operating mechanism is based on the detection of two different colors. The objectives of this research are to obtain a miniature machine is controlled by the PLC system, create a ladder diagram-based program structure, and measure the performance of the embedded system. Obtaining the machine is carried out through assembly of the conveyor frame, installation of all devices, and integrated wiring. The programming for the Omron PLC system is based on providing the CX-Programmer 64 bits, establishing algorithms and compiling ladder diagrams, and compiling and uploading processes. The performance measurement includes synchronization conditions between the simulator and the control system, observations of the readings of installed sensors for activating all devices on the output side, and observing the measurement of the filling process time and the installation of bottle caps assisted by the pneumatic system. The results of the performance during the process of filling and installing the lid obtained a success rate of 75%, based on four trials, three successes, and one failure. The general conclusion is that the embedded system that has been built can be used as a simulator for the mechanism of filling liquid into bottles and installing bottle caps, and it is as an implementation of instrumentation and automation processes. Creator An entity primarily responsible for making the resource Anang Dwi Purnomo1 , Arief Goeritno2* , Danang Adi Nugroho3 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 : 25-08-2021 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/2a7675a53a1be925f215dd72ecec8385.pdf 0e68ec9aa8fd12a53391659b6e14b40e 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 5 (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 Convolutional Neural Network Untuk Deteksi Nyeri Bayi Melalui Citra Wajah Dengan YOLO Subject The topic of the resource NVDIA Jetson Nano Developer Kit, Pain, Baby, YOLO, PyTorch, CNN, Facial Expresion. Description An account of the resource Pain in a baby is difficult to detect is because the method for detecting pain is self-reporting even though babies themselves still cannot describe the pain verbally, then by observing changes in behavior in the form of facial expressions. Statistically, it is also recorded that about 80% of the world's population pays less attention to pain assessment, especially for children, even though this pain gives children a bad experience so that it can interfere with pain responses in the future or psychological trauma. Based on these problems, a prototype system was made using the NVIDIA Jetson Nano Developer kit to help detect pain, especially in infants 0-12 months by using the Convolutional Neural Network (CNN) model with the PyTorch framework and the You Only Look Once (YOLO) algorithm with three detection classification is sad, neutral and sick. From the results of the study, it was found that the YOLO algorithm was able to detect the three classifications with mAP@0.5 value of sad 97,9%, neutral 99,2%, pain 96,9%, model accuracy 70%. The result of random check and the data from Puskesam Imogiri 1 have accuracy value 90%. Creator An entity primarily responsible for making the resource Tomy Abuzairi1 , Nurdina Widanti2 , Arie Kusumaningrum3 , Yeni Rustina4 Publisher An entity responsible for making the resource available Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 20-08-2021 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/52c80e50b0501edc5a93ba8da0c705f4.pdf 0754d2d29670ae70e7330147d88a41e4 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 5 (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 Implementation of Verification and Matching E-KTP with Faster R-CNN and ORB Subject The topic of the resource Detection, Matching, Identity Card, EKTP, ORB, Faster R-CNN. Description An account of the resource An EKTP image repository can be a helpful tool to assist human operators in EKTP image pair checking. But, such a repository needs a solid validation that has verification and matching uploaded images. To solve this problem, this paper implementing a detection model using Faster R-CNN and a matching method using ORB (Oriented FAST and Rotated BRIEF) and KNN-BFM (K-Nearest Neighbor Brute Force Matcher). The goal of the implementations is to reach both an 80% mark of accuracy and prove matching using ORB only can be a replaced OCR technique. The implementation accuracy resultsin the detection model reach mAP (Mean Average Precision) of 94%. But, the matching process only achieves an accuracy of 43,46%. The matching process using only image feature matching underperforms the previous OCR technique but improves processing time from 4510ms to 60m). Image matching accuracy has proven to increase by using a high-quality dan high quantity dataset, extracting features on the important area of EKTP card images Creator An entity primarily responsible for making the resource Muhammad Muttabi Hudaya1 , Siti Saadah2 , Hendy Irawan3 Publisher An entity responsible for making the resource available Telkom University Date A point or period of time associated with an event in the lifecycle of the resource 25-08-2021 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/77f639c63983c756b1da9a36caac831d.pdf 63ce31039ccc4a1d17195efeb0686642 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 5 (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 Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis Subject The topic of the resource Centrality, Covid-19, Follower Rank, Social Network Analysis, Twitter Description An account of the resource Covid-19 is a disease of the virus that is shaking the world and has been designated by WHO as a pandemic. This case of Covid-19 can be a place of dissemination of disinformation that can be utilized by some parties. The dissemination of information in this day and age has turned to the internet, namely social media, Twitter is one of the social media that is often used by Indonesians and the data can be analyzed. This study uses the social network analysis method, conducted to be able to find nodes that affect the ongoing interaction in the interaction network of information dissemination related to Covid-19 in Indonesia and see if the node is directly proportional to the value of its popularity. As well as to know in identifying the source of Covid-19 information, whether dominated by competent Twitter accounts in their fields. The data examined 19,939 nodes and 12,304 edges were taken from data provided by the web academic.droneemprit.id on the project "Analisis Opini Persebaran Virus Corona di Media Sosial", using the period of December 2019 to December 2020 on social media Twitter. The results showed that the @do_ra_dong account is an influential actor with the highest degree centrality of 860 and the @detikcom account is the actor with the highest popularity value of follower rank of 0.994741605. Thus actors who have a high degree of centrality value do not necessarily have a high follower rank value anyway. The study ignores if there are buzzer accounts on Twitter. Creator An entity primarily responsible for making the resource Aprillian Kartino1 , M. Khairul Anam2 , Rahmaddeni3 , Junadhi4 Publisher An entity responsible for making the resource available STMIK Amik Riau Date A point or period of time associated with an event in the lifecycle of the resource 20-08-2021 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/e65a4eb687376411d5171bcd259f4d3e.pdf 761a63832259689a4b4d5efd70677cd4 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 5 (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 Network pada Citra Rontgen Paru-Paru untuk Deteksi SARS-CoV-2 Subject The topic of the resource : convolutional neural network, covid-19, image, chest, x-ray Description An account of the resource COVID-19 was officially declared as a pandemic by the WHO on March 11, 2020. For COVID-19, the testing methods commonly used are the Antibody Testing and RT-PCR Testing. Both methods are considered to be the most effective in determining whether a person has been suffered from COVID-19 or not. However, alternative testing methods need to be tried. One of them is using the Convolutional Neural Network. This study aims to measure the performance of CNN in classifying x�ray image of a person’s chest to determine whether the person is suffered from COVID-19 or not. The CNN model that was built consists of 1 convolutional 2D layer, 2 activation layers, 1 maxpooling layer, 1 dropout layer, 1 flatten layer, and 1 dense layer. Meanwhile, the chest x-ray image dataset used is the COVID-19 Radiography Database. This dataset consists of 3 classes, i.e. COVID-19 class, NORMAL class, and VIRAL_PNEUMONIA. The experiments consisted of 4 scenarios and were carried out using Google Colab. Based on the experiments, the CNN model can achieve an accuracy of 98.69%, a sensitivity of 97.71%, and a specificity of 98.90%. Thus, CNN has a very good performance to classify the disease based on a person’s chest x-ray Creator An entity primarily responsible for making the resource Bambang Pilu Hartato Publisher An entity responsible for making the resource available Universitas Amikom Purwokerto Date A point or period of time associated with an event in the lifecycle of the resource 24-08-2021 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/371404b59a23d086b4904c3b90c94da4.pdf c1d95ff56c7ebde17e84379a7d8bf522 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 5 (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 Algoritma Multinomial Naïve Bayes Untuk Klasifikasi Sentimen Pemerintah Terhadap Penanganan Covid-19 Menggunakan Data Twitter Subject The topic of the resource : opinion, sentiment, twitter, covid-19, multinomial naïve bayes Description An account of the resource Currently, the spread of information Covid-19 is spreading rapidly. Not only through electronic media, but this information is also disseminated by user posts on social media. Due to the user text posted is varies greatly, it’s needs a special approach to classify these types of posts. This research aims to classify the public sentiment towards the handling of COVID-19. The data from this study were obtained from the social media application i.e., Twitter. This study uses a derivative of the Naïve Bayes algorithm, namely Multinomial Nave Bayes to optimize the classification results. Three class labels are used to classify public sentiment namely positive, negative, and neutral sentiments. The stage starts with text preprocessing; cleaning, case folding, tokenization, filtering and stemming. Then proceed with weighting using the TF-IDF approach. To evaluate the classification results, data is tested using confusion matrix by testing accuracy, precision, and recall. From the test results, it is found that the weighted average for precision, recall and accuracy is 74%. Research shows that the accuracy of the proposed method has fair classification levels. Creator An entity primarily responsible for making the resource Yuyun1 , Nurul Hidayah2 , Supriadi Sahibu3 Publisher An entity responsible for making the resource available STMIK Handayani Makassar Date A point or period of time associated with an event in the lifecycle of the resource 30-08-2021 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