JURNAL TEKNIK INFORMATIKA最新文献

{"title":"Virtual Reality Wisata Pesisir Pantai Timur Kabupaten Minahasa","authors":"Clayf Rantung, Nancy J. Tuturoong, Jimmy R. Robot","doi":"10.35793/jti.v19i01.51955","DOIUrl":"https://doi.org/10.35793/jti.v19i01.51955","url":null,"abstract":"Abstract — The tourism sector has been skyrocketing thanks to the information technology that keeps innovating. With blazing speed and widely available internet connection, a tourist nowadays can easily decide where they will spend their time on holiday. The Minahasa East Coast has been very popular with the people of North Sulawesi because of the white sand beaches. Unfortunately, the North Sulawesi has not been actively promoting the tourism section. This research aims to design and build a tourism application to highlight the tourism potentials that span across the Minahasa East Coast. The virtual reality application “Explore: Tondano Pante” has been successfully developed with the Multimedia Development Life Cycle (MDLC) method that consists of Concept, Design, Material Collecting, Assembly, Testing and Distribution. \u0000  \u0000Key words— Tourism; Virtual Reality; Virtual Tour; Pano2VR; Photogrammetry \u0000  \u0000Abstrak — Sektor pariwisata akhir-akhir ini berkembang dengan pesat berkat kemajuan teknologi informasi yang terus memberikan inovasi tanpa henti. Dengan akses internet yang tersedia secara luas saat ini para wisatawan akan sangat mudah untuk memutuskan dimana mereka akan menghabiskan waktu untuk berlibur. Pantai timur Minahasa sendiri sudah cukup dikenal oleh masyarakat Sulawesi Utara karena keindahan pasir putihnya, namun sayangnya upaya dari pemerintah untuk mempromosikan pariwisata di bagian pantai timur Minahasa masih sangat minim. Tujuan dari penelitian ini yaitu untuk merancang dan membangun sebuah aplikasi wisata yang bertujuan untuk meng-highlight potensi-potensi pariwisata yang ada di pesisir pantai timur Minahasa. Aplikasi Virtual Reality Wisata Pesisir Pantai Timur Kabupaten Minahasa “Explore: Tondano Pante” kemudian telah berhasil dikembangkan menggunakan metode Multimedia Development Life Cycle (MDLC) yang terdiri dari 6 tahapan, yaitu Concept, Design, Material Collecting, Assembly, Testing dan Distribution.   \u0000    \u0000  \u0000Kata kunci — Pariwisata; Virtual Reality; Virtual Tour; Pano2VR; Photogrammetry","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":" 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139623638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Klasifikasi Ikan Cakalang dan Tongkol Menggunakan Convolutional Neural Network","authors":"Wellifan Arrank Tonapa, Pinrolinvic D.K. Manembu, Feisy D. Kambey","doi":"10.35793/jti.v19i01.52013","DOIUrl":"https://doi.org/10.35793/jti.v19i01.52013","url":null,"abstract":"     Abstract — Indonesia has a rich diversity of fish species, especially marine fish species. However, the abundance of fish species also poses challenges for the community in classifying each species. This challenge becomes even more significant when dealing with species that share similar physical characteristics, such as the pelagic fish group, which includes skipjack tuna (Katsuwonus pelamis) and mackerel tuna (Euthynnus affinis). Therefore, it is essential to have a profound understanding of fisheries science to accurately classify each fish species. With advancements in current technology, species classification can be automated using image-based classification methods. This research employs the Convolutional Neural Network (CNN) method to classify skipjack tuna and mackerel tuna species. The research results in a CNN classification model constructed using a transfer learning approach by leveraging the pre-trained ResNet50 model available in Keras Applications. The CNN Classification Model generated achieves a performance with a 95% accuracy rate, an average macro precision of 95%, an average macro recall of 95%, and an average macro F1 score of 95%. \u0000Key words— Classification; Convolutional Neural Network; fish species; Transfer Learning; Image. \u0000     Abstrak — Indonesia memiliki banyak keanekaragaman spesies ikan, terutama spesies ikan laut. Namun, keberagaman spesies ikan yang banyak juga menimbulkan kesulitan bagi masyarakat dalam melakukan klasifikasi pada setiap spesies ikan yang ada. Apalagi, pada beberapa spesies ikan yang memiliki fisik yang hampir sama, seperti kelompok ikan pelagis, yaitu cakalang (Katsuwonus pelamis) dan tongkol (Euthynnus affinis). Oleh karena itu, penting untuk memiliki pemahaman mendalam tentang ilmu perikanan agar dapat melakukan klasifikasi yang benar terhadap setiap spesies ikan. Dengan kemajuan teknologi saat ini, pengklasifikasian spesies ikan dapat dilakukan secara otomatis menggunakan metode klasifikasi berdasarkan citra. Penelitian ini menggunakan metode Convolutional Neural Network (CNN) untuk mengklasifikasikan spesies ikan cakalang dan tongkol. Penelitian ini menghasilkan model klasifikasi CNN yang dibangun menggunakan pendekatan transfer learning dengan memanfaatkan model pre-trained ResNet50 yang tersedia di Keras Applications. Model Klasifikasi CNN yang dihasilkan mendapatkan nilai performa akurasi 95%, rata-rata makro precision 95%, rata-rata makro recall 95%, rata-rata makro f1 score 95%. \u0000Kata kunci — Citra; Convolutional Neural Network; Klasifikasi; Spesies Ikan; Transfer Learning.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":" 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139623778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis UI/UX Pada Website Program Studi Teknik Informatika Menggunakan Metode System Usability Scale","authors":"Naomi Ajamsaru, S. Paturusi, Virginia Tulenan","doi":"10.35793/jti.v19i01.51375","DOIUrl":"https://doi.org/10.35793/jti.v19i01.51375","url":null,"abstract":"Usability juga bermanfaat sebagai salah satu faktor yang boleh dapat mempengaruhi pada pencapaian suatu Website. Pemakai Website akan membutuhkan kenyamanan maupun kepuasan untuk memperoleh suatu pengalaman yang baik saat Kerjasama tertentu dengan sistem atau produk.  Tentunya sangat berguna penting jika memiliki User Interface /User Experience  (UI/UX) yang bagus. Karena pada dasarnya User Experience (UI/UX)  merupakan suatu bagian komponen  yang penting, pengguna juga berinteraksi dengan bagian sistem terus merasakan kemudahan dengan efektif. Penelitian ini pun dapat dimaksudkan untuk menganalisa pengalaman pada pengguna website fatek informatika dengan mengunakan cara/metode kuesioner SUS.  SUS ini sangat cocok dipakai supaya lebih efektif dan efisien juga bisa mampu memberikan soal kepuasan segi suatu sistem sangat subjektif maka proses tahapan evaluasi dan analisis memiliki juga singkat. Dari hasil penelitian pun menunjuk akan Analisa   User Experience (UX) di Wesite Program Studi Informatika Universitas Sam Ratulangi dapat dibuat dalam mengevaluasi Usability , itu pun berdasarkan dengan pengalaman pengguna sesuai dengan perhitungan,  juga pengujian kuesioner  dari hasil perhitungan dan pengujian tersebu. Website Fatek Informatika juga termasuk dan dikategorikan dalam Acceptable.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"26 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sistem Absensi Pengenalan Wajah Bermasker","authors":"Joshua Walangitan, S. Sompie, Xaverius B. N. Najoan","doi":"10.35793/jti.v19i01.51327","DOIUrl":"https://doi.org/10.35793/jti.v19i01.51327","url":null,"abstract":"Sistem absensi yang sering di temukan di berbagai tempat masih menggunakan sistem absensi yang konvensional. Sistem ini memiliki banyak kekurangan. Contohnya waktu absensi yang tidak menentu dikarenakan seseorang bisa saja memanipulasi sistem absensi konvensional untuk kepentingan pribadi, menyulitkan pada saat rekapitulasi, dan cara ini dianggap sulit untuk diintegrasikan dengan hal lain. Pada masa sekarang juga dunia sedang dalam perlawanan terhadap virus corona, seluruh dunia sedang berpatisipasi untuk melawan virus ini dengan cara menggunakan masker, mencuci tangan secara rutin, dan tidak berkumpul di tempat yang ramai. Dengan tujuan dari penelitian ini dibuatlah sistem “Sistem Absensi Pengenanalan Wajah Bermasker”. Sistem ini dapat membantu dalam melakukan pengisian absen tanpa adanya sentuhan fisik ataupun membuka masker. Aplikasi ini berbasis sistem operasi windows, dan dibangun menggunakan metode Waterfall. Hasil dari penelitian ini adalah Sistem Absensi tidak lagi perlu sentuhan fisik yang bisa menyebarkan virus corona, melainkan sistem absen yang menggunakan wajah dan juga tanpa seseorang harus melepaskan masker mereka.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"31 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementasi RFID Pada Pengelolaan Aset Laboratorium Biomolekuler Universitas Sam Ratulangi","authors":"Putra Rivaldo Imanuel Rorimpandey, Alwin M. Sambul, Arie S. M. Lumenta","doi":"10.35793/jti.v19i01.48836","DOIUrl":"https://doi.org/10.35793/jti.v19i01.48836","url":null,"abstract":"Abstract— In the world of technology, many things are currently being developed, one of which is radio frequency identification (RFID) technology, this technology is widely used by agencies to identify an object or asset. Radio frequency identification (RFID) is a technology that can store and receive data remotely using radio frequencies or electromagnetic waves. A biomolecular laboratory is a research environment containing valuable assets, such as scientific equipment and experimental materials that require careful monitoring, protection and management. This research focuses on efforts to increase the efficiency, accuracy and security of laboratory asset management through the application of RFID technology. The research methodology involves analyzing laboratory needs, designing an appropriate RFID system, developing RFID hardware and software, and implementing trials in a biomolecular laboratory. The results of this research show that the use of RFID can speed up asset record management, reduce the risk of loss, and provide better visibility of laboratory inventory. The application of RFID technology in managing biomolecular laboratory assets at Sam Ratulangi University is expected to provide significant benefits in increasing operational efficiency, minimizing human error, and optimizing the use of laboratory assets. In addition, the results of this research can also be a basis for the development of similar systems in other laboratory environments as well as an important contribution in the context of overall university asset management..\u0000Key words — Technology; RFID; Biomolecular Laboratory; Assets.\u0000Abstrak — Dunia teknologi saat ini banyak hal yang sedang di kembangkan salah satunya yaitu teknologi radio frequency identification (RFID), teknologi ini banyak digunakan oleh instansi untuk mengidentifikasi suatu objek atau aset. Radio frequency identification (RFID) merupakan teknologi yang dapat menyimpan dan menerima data dari jarak jauh menggunakan frekuensi radio atau gelombang elektromagnetik. Laboratorium biomolekuler adalah lingkungan penelitian yang memiliki aset berharga, seperti peralatan ilmiah dan bahan eksperimental yang memerlukan pemantauan, perlindungan, dan manajemen yang cermat. Penelitian ini berfokus pada upaya meningkatkan efisiensi, akurasi, dan keamanan pengelolaan aset laboratorium melalui penerapan teknologi RFID. Metodologi penelitian melibatkan analisis kebutuhan laboratorium, perancangan sistem RFID yang sesuai, pengembangan perangkat keras dan perangkat lunak RFID, serta uji coba implementasi di laboratorium biomolekuler. Hasil dari penelitian ini menunjukkan bahwa penggunaan RFID dapat mempercepat dalam pengelolaan pencatatan aset, mengurangi risiko kehilangan, dan memberikan visibilitas yang lebih baik terhadap inventaris laboratorium. Penerapan teknologi RFID dalam pengelolaan aset laboratorium biomolekuler di Universitas Sam Ratulangi diharapkan dapat memberikan manfaat signifikan dalam meningkatkan efisiensi","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139536217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hoax News Detection Using Passive Aggressive Classifier And TfidfVectorizer","authors":"Maulana Fajar Lazuardi, Renaldy Hiunarto, Kareena Futri Ramadhani, Noviandi Noviandi, Riya Widayanti, Muhamad Hadi Arfian","doi":"10.15408/jti.v16i2.34084","DOIUrl":"https://doi.org/10.15408/jti.v16i2.34084","url":null,"abstract":"Indonesia is one of the countries with the highest number of social media users. Million social media users in Indonesia reached 167 million in January 2023. These users are spread, across various social media, including Twitter with 24 million users. The high number of social media users on Twitter makes the information validation process even more neglected. Moreover, the trend of news interest read by social media users is only adjusted to their individual tastes. This phenomenon is evidenced by the large number of fake news (hoaxes) circulating in society which are spread through social media. Therefore, an accurate machine learning model is needed to classify \"real\" and \"hoax\" news. This study uses the TfidfVectorizer algorithm and Passive Aggressive Classifier for datasets that are shared through the Kaggle site. The contents of the dataset were sourced via social media Twitter over a span of 5 years, namely 2015-2020. At the preprocessing stage to making the Confusion Matrix, the machine learning model shows that it can work well as expected, namely getting Accuracy, Precision, and Recall scores of 82.44%, 80.66%, and 82.44%. In addition, the results of the confusion matrix show that in the dataset used, there is more \"real\" news than \"hoaxes\", that is, the model is able to predict 1059 real news and 211 hoax news, with actual conditions 1106 real news and 164 hoax news.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"132 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139164014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cucumber Disease Classification with Ensemble Learning Method for Complex Datasets","authors":"Franz Adeta Junior, Muhammad Rizki Nur Majiid","doi":"10.15408/jti.v16i2.34618","DOIUrl":"https://doi.org/10.15408/jti.v16i2.34618","url":null,"abstract":"Many researchers are taking into account the algorithm's ability to detect diseases in plants since it can save expenses and deliver more accurate results. However, there are various obstacles in detecting diseases, particularly in cucumber plants, such as disease similarities and the ability of models to adapt to the information they have. To address this issue, we propose an ensemble learning strategy based on the averaging method to improve the model's ability to generalize to different cucumber plant environments. According to the results, the ensemble learning approach outperforms the feature fusion method with a test accuracy of 94.20% and a loss of 0.01105. Feature fusion and ensemble learning techniques, in general, have the potential to increase the model's capacity to classify difficult data.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"47 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139164702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing ITIL Incident Management: Innovative Machine Learning Approaches for Efficient Incident Prioritization and Resolution","authors":"Alifia Ayu Zahrothul Ain, Cutifa Safitri","doi":"10.15408/jti.v16i2.31439","DOIUrl":"https://doi.org/10.15408/jti.v16i2.31439","url":null,"abstract":"Incident Management in ITIL requires an effective process so the incidents do not disrupt business processes for too long. This research aims to automate decision-making in Incident Management process. To perform the automation in decision-making process requires machine learning algorithms. The development of machine learning method in this research will bring significance result such as a new technique of decision-making process in Incident Management, accelerate decision-making process in Incident Management by implementing machine learning to determine the category, group, and priority. By combining supervised and unsupervised machine learning, this research can help to determine the priority of the incident, so IT Operation Teams know which incident should resolve first. By training historical full description, short description, and title, machine learning can classify the new incident. In this research different classification algorithms are used to automate decision making process. Performances of automated decision-making are evaluated with accuracy, precision, recall, and f1-score. Based on the result of various performance metrics, classifier based on K-Nearest Neighbor performed well on predicting Priority, and both category and priority get the best performance with Support Vector Machine.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"106 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139165003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IoT Based Early Flood Detection System with Arduino and Ultrasonic Sensors in Flood-Prone Areas","authors":"Muhammad Darwis, Hafiizh Asrofil Al Banna, Setiawan Restu Aji, Dinda Khoirunnisa, Nakia Natassa","doi":"10.15408/jti.v16i2.32161","DOIUrl":"https://doi.org/10.15408/jti.v16i2.32161","url":null,"abstract":"IoT is one of the focuses of application development carried out by various developers today. The aim is to enable various devices and work independently to meet the various needs of their users. The flood early warning system is one of the much-needed IoT-based applications, enabling users to quickly obtain water level information in an area. This application can help people to be more aware of flood disasters, especially during the rainy season. This research develops a flood early warning system application by utilizing Arduino and ultrasonic sensors installed in flood-prone areas. The sensor is used to measure the water level at a time based on the distance from the water surface to the sensor. When the distance between the water surface and the sensor is less than or equal to the set threshold, the sensor will send data and alerts to the user via email. This research applies the IoT design and development method. In addition, this research also used the C and Python programming language for application prototypes and the MySQL database to store the data. the application in this study was tested using the blackbox method and the results showed that all application functions could run properly.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"13 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139164538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Design Thinking Method in UI/UX Redesign of Public Complaint Application (Case Study: Go Siaga App)","authors":"Rafi Kurnia Pangestu, M. B. Ulum","doi":"10.15408/jti.v16i2.27416","DOIUrl":"https://doi.org/10.15408/jti.v16i2.27416","url":null,"abstract":"Go Siaga App is a mobile-based application by Tangerang Sub-district Police Office that provides special community services for the Tangerang sub-district community which provides features in the form of reports of disturbances in public security and reports of loss or damage. Since it is a new application released in March 2021 on Google Playstore, there are several things that need to be considered to maintain the usability of the application. This research aims to redesign the user interface and user experience (UI/UX) of the Go Siaga application using Design Thinking Method in the design process. Some of the supporting aspects for testing the user satisfaction such as effectiveness, efficiency, usefulness, satisfaction, and learnability are met in the usability testing. The results showed that the percentage of all the aspects in usability from the redesigned version were all higher than the current one with 80% of effectiveness, 80% of efficiency, 80% of usefulness, 86.67% of satisfaction, and 73.33% of learnability. Therefore, based on the research results, the redesign of Go Siaga is more effective, more efficient, more useful, more satisfying, and also easy to learn.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"109 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139163684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}