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Analisis Sentimen dan Klasifikasi Tweet Terkait Mutasi COVID-19 menggunakan Metode Naïve Bayes Classifier twitter对COVID-19突变相关的情绪和分类分析使用了天真的Bayes经典材料
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2022-07-04 DOI: 10.26905/jtmi.v8i1.6803
Aryo Dewandaru, Jati Sasongko Wibowo
{"title":"Analisis Sentimen dan Klasifikasi Tweet Terkait Mutasi COVID-19 menggunakan Metode Naïve Bayes Classifier","authors":"Aryo Dewandaru, Jati Sasongko Wibowo","doi":"10.26905/jtmi.v8i1.6803","DOIUrl":"https://doi.org/10.26905/jtmi.v8i1.6803","url":null,"abstract":"Towards the end of 2019 in Wuhan City, China, a new type of Corona Virus was discovered which has the scientific name COVID-19 and is a type of virus that causes acute disorders in the human respiratory system. The spread of this virus is very fast and causes mutations of this virus to a more lethal stage than before. Thus, sentiment analysis is expected to be able to determine the trend of public assessment of the COVID-19 mutation. Naïve Bayes Classifier is a method used in research. This method can classify data or opinions into two sentiments, namely positive and negative. The research data comes from Twitter which is taken using the Twitter API with the keyword \"covid mutation\", for data processing several processes are carried out, namely sentiment classification, data cleaning, and preprocessing so that the final result is obtained. The test results from this study show that the Naïve Bayes Classifier method has an accuracy of 86.67% with an f1-score of 82.00% on positive sentiment and 89.00% on negative sentiment. Based on the results of the study, it can be concluded that the Naïve Bayes Classifier method can be used to analyze sentiment data from tweets about the COVID-19 mutation with an accuracy of 86.67%.","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45198020","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}
引用次数: 0
Analisis Perbandingan Algoritma Forecasting dalam Prediksi Harga Saham LQ45 PT Bank Mandiri Sekuritas (BMRI) 分析预测证券自力更生银行LQ45股价的预估算法(BMRI)
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2022-07-04 DOI: 10.26905/jtmi.v8i1.6092
Viry Puspaning Ramadhan, Fandi Yulian Pamuji
{"title":"Analisis Perbandingan Algoritma Forecasting dalam Prediksi Harga Saham LQ45 PT Bank Mandiri Sekuritas (BMRI)","authors":"Viry Puspaning Ramadhan, Fandi Yulian Pamuji","doi":"10.26905/jtmi.v8i1.6092","DOIUrl":"https://doi.org/10.26905/jtmi.v8i1.6092","url":null,"abstract":"Economic development in Indonesia has slowed in recent years. This resulted in the movement of the index for several stocks listed on BEIm, especially LQ45 which also experienced increases and decreases. Therefore, it is necessary to analyze stock price movements so that the results of the analysis can be used by investors to make investment decisions. This study will apply several Forecasting algorithms such as Linear Regression and Neural Network to predict the stock price of LQ45 in the case study of Bank Mandiri Sekuritas (BMRI). By using four attributes, namely open, high, and low values as predictors and close as a class, this study focuses on determining the accuracy value, namely Root Mean Squared Error (RMSE) by optimizing parameter values. The test results obtained an RMSE value of 0.034 on the Neural Network method with the addition of a hidden layer and an RMSE value of 0.052 on the Linear Regression method with M5 Prime and Greedy Feature Selection with a min-tolerance value of 0.05.","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44637351","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}
引用次数: 2
System Quality dan Information Quality terhadap Kinerja Pegawai melalui User Satisfaction menggunakan SIPD di Dinas Ketahanan Pangan dan Pertanian Kota Madiun Medium Town和公共卫生中心使用SIPD通过用户满意度对员工的系统质量和信息质量
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2022-07-04 DOI: 10.26905/jtmi.v8i1.6739
Firdaus Miftakh Kusuma, Yusaq Tomo Ardianto, Dwi Arman Prasetya
{"title":"System Quality dan Information Quality terhadap Kinerja Pegawai melalui User Satisfaction menggunakan SIPD di Dinas Ketahanan Pangan dan Pertanian Kota Madiun","authors":"Firdaus Miftakh Kusuma, Yusaq Tomo Ardianto, Dwi Arman Prasetya","doi":"10.26905/jtmi.v8i1.6739","DOIUrl":"https://doi.org/10.26905/jtmi.v8i1.6739","url":null,"abstract":"The Regional Government Information System (SIPD in Bahasa) is a management information system that is used to administer, document, and process regional development data into information. It serves to make decisions, and policies and build a unified database. The data is integrated from district/city, provincial and national levels. This study uses path analysis with a total sample of 43 employees. In the research, the coefficient value of the System Quality variable on User Satisfaction has a direct effect of 0.414. The Information Quality variable on User Satisfaction has a direct effect of 0.352. The System Quality variable on Employee Performance has a direct influence of 0.229. The variable Information Quality on Employee Performance has a direct effect of 0.449. Furthermore, the influence of System Quality on Employee Performance through User Satisfaction has an indirect effect of 0.186 with a total amount of 0.415. The influence of Information Quality on Employee Performance through User Satisfaction has an indirect effect of 0.158 with a total amount of 0.610.","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47548748","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}
引用次数: 0
Analisa Prediksi Varietas Buah Salak yang Sesuai dengan Lahan Daerah Kabupaten Banjarnegara Menggunakan Algoritma C45 利用C45算法进行杂果品种与国外产能区匹配的分析预测
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2022-07-04 DOI: 10.26905/jtmi.v8i1.7521
Fitri Marisa, A. L. Maukar
{"title":"Analisa Prediksi Varietas Buah Salak yang Sesuai dengan Lahan Daerah Kabupaten Banjarnegara Menggunakan Algoritma C45","authors":"Fitri Marisa, A. L. Maukar","doi":"10.26905/jtmi.v8i1.7521","DOIUrl":"https://doi.org/10.26905/jtmi.v8i1.7521","url":null,"abstract":"Salak is a potential horticultural sector that is a leading commodity in Banjarnegara. Salak fruit varieties have fruit categories that have their advantages. Variants of salak fruit include ivory salak, granulated sugar salak, pondoh salak, and honey salak. Based on data released from the relevant government agencies, further research was carried out related to analyzing and conducting research to predict salak fruit varieties. This variety is suitable for land in every area in Banjarnegara with predictive analysis using the C4.5 algorithm. This method has been widely developed to classify and predict a case with a fairly high degree of accuracy. From this study, researchers hope that it can contribute farmers to determining the type of salak fruit that is most suitable for the land they own so that later the harvest obtained by farmers can be maximized","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45380776","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}
引用次数: 0
Klasifikasi Tanaman Beringin (Ficus Bernjamina) berdasarkan Citra Daun Menggunakan Algoritma K-Nearest Neighbors 基于Citra Daun的K-近邻算法的黄金植物分类（Ficus Bernjamina）
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2021-12-22 DOI: 10.26905/jtmi.v7i2.6758
F. Wibowo, A. Wicaksono, Lahan Adi Purwanto
{"title":"Klasifikasi Tanaman Beringin (Ficus Bernjamina) berdasarkan Citra Daun Menggunakan Algoritma K-Nearest Neighbors","authors":"F. Wibowo, A. Wicaksono, Lahan Adi Purwanto","doi":"10.26905/jtmi.v7i2.6758","DOIUrl":"https://doi.org/10.26905/jtmi.v7i2.6758","url":null,"abstract":"Salah satu masalah yang dihadapi ketika akan memilih Beringin, baik untuk dijadikan tanaman peneduh, bonsai atau tanaman obat adalah mengenali jenis beringin yang sesuai. Maka harus dilakukan sebuah penelitian agar dapat mengetahui jenis Beringin yang diinginkan. Salah satu cara yang dapat digunakan untuk mengklasifikasikan adalah dengan teknologi pengolahan citra digital, yaitu dengan mengekstrak ciri atau karakteristik dari citra atau gambar digital. Tantangannya adalah bagaimana mengklasifikasikan tanaman Beringin berdasarkan citra daun menggunakan pengolahan citra digital. Penelitian ini bertujuan merancang atau mendesain dan menyusun program pengolahan citra digital dan algoritma K-Nearest Neighbors (KNN) untuk klasifikasi jenis Beringin yang dapat dijadikan sebagai model sistem klasifikasi otomatis menggunakan perangkat komputer. Hasil penelitian pada proses pengujian klasifikasi tanaman ficus berdasarkan ciri tekstur dan bentuk pada citra daun menggunakan algoritma k-Nearest Neighbor dapat disimpulan bahwa aplikasi telah berhasil dirancang dan dibangun dan dapat digunakan untuk proses ekstraksi fitur tekstur dan bentuk serta dapat digunakan untuk proses klasifikasi. Dari ekstraksi fitur diperoleh tujuh fitur tekstur GLCM yaitu energi, entropy, contras, homogenity, idm, variance dan dissimilarity, dan 2 fitur bentuk yaitu roundness, dan compactness. Hasil pengujian menunjukan nilai akurasi yang relatif rendah yaitu 56,25% dengan data jumlah citra dikenali sesuai jenis ficus sebanyak 18 dan tidak dikenali sebanyak 5 citra","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46041295","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}
引用次数: 1
Perbandingan Model Deep Learning untuk Klasifikasi Sentiment Analysis dengan Teknik Natural Languange Processing 基于深度学习、情感分析和自然语言处理的深度学习模型
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2021-12-22 DOI: 10.26905/jtmi.v7i2.6506
Firman Pradana Rachman
{"title":"Perbandingan Model Deep Learning untuk Klasifikasi Sentiment Analysis dengan Teknik Natural Languange Processing","authors":"Firman Pradana Rachman","doi":"10.26905/jtmi.v7i2.6506","DOIUrl":"https://doi.org/10.26905/jtmi.v7i2.6506","url":null,"abstract":"Setiap orang mempunyai pendapat atau opini terhadap suatu produk, tokoh masyarakat, atau pun sebuah kebijakan pemerintah yang tersebar di media sosial. Pengolahan data opini itu di sebut dengan sentiment analysis. Dalam pengolahan data opini yang besar tersebut tidak hanya cukup menggunakan machine learning, namun bisa juga menggunakan deep learning yang di kombinasikan dengan teknik NLP (Natural Languange Processing). Penelitian ini membandingkan beberapa model deep learning seperti CNN (Convolutional Neural Network), RNN (Recurrent Neural Networks), LSTM (Long Short-Term Memory) dan beberapa variannya untuk mengolah data sentiment analysis dari review produk amazon dan yelp.","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46458738","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}
引用次数: 3
Peramalan Stock Barang Dagangan Menggunakan Metode Single Exponential Smoothing 基于单指数平滑方法的交通存量行为
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2021-12-22 DOI: 10.26905/jtmi.v7i2.6727
Saiful Nur Budiman
{"title":"Peramalan Stock Barang Dagangan Menggunakan Metode Single Exponential Smoothing","authors":"Saiful Nur Budiman","doi":"10.26905/jtmi.v7i2.6727","DOIUrl":"https://doi.org/10.26905/jtmi.v7i2.6727","url":null,"abstract":"Peramalan bisa digunakan dibidang manapun yang mana membutuhkan sebuah prediksi akan keberadaan data di masa yang mendatang. Forecasting bisa diterapkan salah satunya untuk membantu anggaran penjulan ke periode berikutnya. Data time series diperoleh dari data penjualan selama periode tertentu penjualan suatu produk bisa digunakan sebagai dasar forecasting-nya. Restock barang yang berlebih tidak baik untuk sebuah toko, karena ada kemungkinan barang yang dibeli tidak laku kedepannya. Perlu adanya proses kontrol yang baik untuk restock barang, salah satunya yang bisa digunakan adalah menggunakan prediksi restock barang dagangan menggunakan single exponential smoothing (SES). Data penjulan yang digunakan ada dua macam yaitu Beras Koi 5kg-an dan Minyak Bimoli 900ml-an. Dari hasil perhitungan SES diperoleh nilai alpha yang bagus untuk peramalan Beras Koi 5kg-an adalah 0,46. Sedangkan nilai alpha untuk Minyak Bimoli 900ml-an adalah 0,704. Nilai alpha tersebut diperoleh dari perhitungan nilai MSE yang terkecil. Hasil prediksinya menunjukkan pada periode berikutnya (15-30 September 2021) menunjukkan adanya penurunan jumlah penjualan barang dari kedua produk tersbut, sehingga pemilik toko bisa mengurangi jatah belanjanya.","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44557969","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}
引用次数: 7
Pengembangan Aplikasi Android MVTE dengan Metode RAD 用RAD方法开发MVTE Android应用程序
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2021-12-22 DOI: 10.26905/jtmi.v7i2.6754
F. Amrullah, Mardiana Andarwati, Galandaru Swalaganata, Hudan Eka Rosyadi
{"title":"Pengembangan Aplikasi Android MVTE dengan Metode RAD","authors":"F. Amrullah, Mardiana Andarwati, Galandaru Swalaganata, Hudan Eka Rosyadi","doi":"10.26905/jtmi.v7i2.6754","DOIUrl":"https://doi.org/10.26905/jtmi.v7i2.6754","url":null,"abstract":"Kegiatan diskusi mahasiswa Tuli dengan mahasiswa lain, mahasiswa Tuli membutuhkan alat bantu dalam mengikuti kegiatan diskusi, dimana selama ini, mahasiswa Tuli hanya mengandalkan kemampuan membaca bibir lawan bicaranya. Penelitian ini menghasilkan sebuah teknologi bantu atau asistif yaitu aplikasi MVTe (Mobile Voice To Text) berbasis Android dimana aplikasi ini secara sederhana merubah suara dalam bentuk tulisan. Aplikasi ini dikembangan menggunakan metode RAD (Rapid Application Development). Metode RAD mempercepat proses pengerjaan dikarenakan proses kerjanya yang ringkas. Uji coba aplikasi dilakukan kepada seorang ahli IT, 5 mahasiswa Tuli, dan 5 Dosen yang ada di lingkungan Fakultas Teknologi Informasi Universitas Merdeka Malang. Rata-rata hasil uji sebesar 81,3% dengan kategori layak untuk digunakan.","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45557254","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}
引用次数: 2
Analisis dan Perancangan Sistem Manajemen Inventaris Menggunakan Metode Fishbone 鱼骨法库存管理系统的分析与设计
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2021-12-22 DOI: 10.26905/jtmi.v7i2.6501
H. Hijrah, Maulidar Maulidar
{"title":"Analisis dan Perancangan Sistem Manajemen Inventaris Menggunakan Metode Fishbone","authors":"H. Hijrah, Maulidar Maulidar","doi":"10.26905/jtmi.v7i2.6501","DOIUrl":"https://doi.org/10.26905/jtmi.v7i2.6501","url":null,"abstract":"Penelitian ini dilakukan dengan pendekatan kualitatif serta dilakukan wawancara, observasi dan telaah dokumentasi untuk memperoleh data primer dan data sekunder. Data yang diperoleh dari proses tahapan penelitian akan dianalisis menggunakan metode fishbone untuk memperoleh akar masalah dengan melihat sebab dan akibat dari permasalahan tersebut. Setelah semua tahapan analisis dilakukan maka akan direkomendasikan aplikasi yang dapat membantu bisnis perusahaan yang bergerak dibidang jasa pelayanan internet untuk meminimalisir kerugian yang diperoleh akibat kelebihan stock. Aplikasi yang direkomendasikan dirancang dengan menggunakan metode atau alat bantu perancangan sistem informasi yang menggambarkan alur sistem, struktur data serta relasi yang terkait sehingga memudahkan dalam penerapan serta pengembangan aplikasi. Dari hasil analisis dari penelitian yang dilakukan maka dapat disimpulkan rancangan inventaris sangat dibutuhkan sehingga dirancang aplikasi inventaris yang sesuai dengan kebutuhan perusahaan tersebut.","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44154376","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}
引用次数: 6
Implementasi Algoritma K-Means untuk Menentukan Persediaan Barang pada Poultry Shop 确定家禽店供应量的K-Means算法的实现
Jurnal Teknologi dan Manajemen Informatika Pub Date : 2021-12-22 DOI: 10.26905/jtmi.v7i2.6377
Firman Nurdiyansyah, I. Akbar
{"title":"Implementasi Algoritma K-Means untuk Menentukan Persediaan Barang pada Poultry Shop","authors":"Firman Nurdiyansyah, I. Akbar","doi":"10.26905/jtmi.v7i2.6377","DOIUrl":"https://doi.org/10.26905/jtmi.v7i2.6377","url":null,"abstract":"Menjaga persediaan barang agar barang tidak sampai kosong termasuk salah satu menjaga kepuasan pelanggan. Untuk melaksanakan hal tersebut manajemen perusahaan harus dapat menganalisa mana barang yang laku dan mana barang yang kurang laku, khususnya pada bagian penjualan. Hal ini tidak mudah bagi CV. Muria PS dikarenakan memiliki jumlah item barang yang cukup banyak, sehingga dibutuhkan sedikit teknik komputasi untuk mempermudah permasalahan tersebut. Algoritma K-Means clustering dipilih dalam mengatasi permasalahan tersebut karena mampu mengelompokkan produk yang terjual dan masih tersedia menjadi beberapa cluster. Dari tiga cluster yang dibentuk menghasilkan cluster 1 terdiri dua barang, cluster 2 terdiri 9 barang dan sisanya dari 25 barang masuk pada cluster 3. Dari hasil ini bisa dimanfaatkan oleh manajemen CV. Muria PS untuk meningkatkan stok persediaan barang dan strategi penjualannya.","PeriodicalId":31840,"journal":{"name":"Jurnal Teknologi dan Manajemen Informatika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46199137","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}
引用次数: 2
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