MALCOM: Indonesian Journal of Machine Learning and Computer Science最新文献

Analysis of the Interconnection between Digital Skills of Human Resources in SMEs and the Success of Digital Business Strategy Implementation 中小企业人力资源数字技能与数字商业战略成功实施之间的相互联系分析

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1282

Sutrisno Sutrisno, Kraugusteeliana Kraugusteeliana, S. Syamsuri

{"title":"Analysis of the Interconnection between Digital Skills of Human Resources in SMEs and the Success of Digital Business Strategy Implementation","authors":"Sutrisno Sutrisno, Kraugusteeliana Kraugusteeliana, S. Syamsuri","doi":"10.57152/malcom.v4i2.1282","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1282","url":null,"abstract":"The advancement of information technology has transformed the way SMEs operate, from marketing aspects to inventory management. Digital business opens up new opportunities for SMEs but also demands new skills from human resources to keep up with these developments. The objective of this research is to analyze the interconnection between the digital skills of human resources in SMEs and the success of implementing digital business strategies. This research method focuses on qualitative literature review using Google Scholar as the data source, especially for articles published between 2021 and 2024. The study results indicate that the role of human resources in an increasingly digital business world is crucial. The digital skills possessed by human resources not only affect the effectiveness of implementing digital business strategies but also impact the competitiveness and sustainability of SMEs in the constantly changing market. A deep understanding of the market, creativity in innovation, and adaptability are important factors in ensuring business success in this digital era.","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"6 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140234623","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

Outpacing Competitive Challenges in the Online Market: An Effective Digital Entrepreneurship Approach 应对网络市场的竞争挑战：有效的数字创业方法

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1278

Prety Diawati

{"title":"Outpacing Competitive Challenges in the Online Market: An Effective Digital Entrepreneurship Approach","authors":"Prety Diawati","doi":"10.57152/malcom.v4i2.1278","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1278","url":null,"abstract":"The online market has become one of the primary battlegrounds for businesses in this digital era. With the increasing use of the internet and the adoption of digital technology, society at large has shifted to online platforms for various activities, including shopping. This research aims to analyze the strategies and factors influencing success in facing the fiercely competitive online market challenges through a digital entrepreneurship approach. The research method employed in this study is a qualitative literature review using Google Scholar as the data source. This study focuses on scholarly articles published between 2013 and 2024. The results of the study indicate that in confronting the fierce and dynamic challenges of the online market, a digital entrepreneurship approach is key to business success. Intense competition and complex consumer dynamics demand business operators to have a deep understanding of the market, as well as the ability to leverage technology and effective marketing strategies. Through in-depth market analysis, personalization, the use of cutting-edge technology, collaboration, consumer engagement, and sustainable innovation, business operators can build resilient and sustainable businesses in this digital era.","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"178 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235816","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

Peningkatan Cakupan Sinyal Wi-Fi dengan Penempatan Access Point Menggunakan Metode Probabilitas Bayesian 利用贝叶斯概率法通过接入点布局改善 Wi-Fi 信号覆盖范围

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1291

Nurhas Linda, I. Ali

{"title":"Peningkatan Cakupan Sinyal Wi-Fi dengan Penempatan Access Point Menggunakan Metode Probabilitas Bayesian","authors":"Nurhas Linda, I. Ali","doi":"10.57152/malcom.v4i2.1291","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1291","url":null,"abstract":"Saat pemasangan jaringan Wi-Fi, posisi Access point merupakan salah satu pengaruh besar terhadap kualitas sinyal Wi-Fi. Maka, dalam pemasangan alat jaringan diperlukan penempatan Access point yang tepat. Laboraturium Teknik Elektro Universitas Riau merupakan salah satu lokasi yang memanfaatkan jaringan Wi-Fi untuk aktivitas akademik jurusan Teknik Elektro. Namun, penempatan posisi Access point di Laboraturium Teknik Elektor Universitas Riau tidak melalui tahap perencanaan penempatan Access point yang matang dan terdapat penumpukan Access point sehingga cakupan sinyal Wi-Fi di Laboraturium Teknik Elektro Universitas Riau belum optimal. Untuk menyelesaikan permasalahan tersebut, penelitian ini menggunakan metode probabilitas bayesian untuk mengatasi ketidakpastian data dan memerlukan pengetahuan awal untuk mengambil suatu keputusan. Tujuan penelitian ini untuk meningkatkan cakupan sinyal Wi-Fi di Laboraturium Teknik Elektro universitas Riau. Hasil penelitian sebelumnya memiliki luas cakupan sinyal W-Fi sebesar 2,031,04 M2, jika dipersentasekan menjadi 53% dari luas area Laboraturium Teknik Elektro. Setelah dilakukan penelitian terjadi peningkat luas cakupan sinyal Wi-Fi menjadi 3,308,8 M2","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"94 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140234952","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

Deteksi Tingkat Kematangan Buah Tomat Menggunakan YOLOv5 使用 YOLOv5 检测番茄果实成熟度

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1270

Suhardi Aras, Putriana Tanra, Muhammad Bazhar

引用次数: 0

The Impact of Digital Transformation on Human Resource Development in the Online Business Paradigm 数字化转型对在线业务范式中人力资源开发的影响

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1281

Itot Bian Raharjo

{"title":"The Impact of Digital Transformation on Human Resource Development in the Online Business Paradigm","authors":"Itot Bian Raharjo","doi":"10.57152/malcom.v4i2.1281","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1281","url":null,"abstract":"As digital technology continues to evolve, there is a significant shift from conventional business models towards online business models. This change encompasses various aspects, ranging from how products and services are marketed to interactions with customers. This research aims to understand the influence of digital transformation on Human Resource Development (HRD) in the context of online businesses. The research method employed in this study is a qualitative literature review, drawing data from Google Scholar from 2019 to 2023. The results indicate that in the continuously evolving digital era, digital transformation has become a necessity for every business seeking to survive and thrive, particularly in the realm of online business. HRD is a highly impacted aspect of this transformation. The paradigm shift in HRD development is not only related to technical skills but also to adaptability, continuous learning, and holistic understanding of the online business ecosystem. The urgency of this research is crucial because a deep understanding of how digital transformation affects HRD development can assist organizations and stakeholders in designing effective strategies to address challenges and capitalize on opportunities in this dynamic era of online business.","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235193","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

Implementasi Pencarian Rute Terbaik untuk Mengetahui Lokasi Tempat Parkir pada Sistem E-Parking Menggunakan Algoritma Dijkstra dan Best First Search 使用 Dijkstra 算法和最佳初选搜索实现最佳路径搜索，以了解电子停车系统中的停车位位置

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1261

Nava Gia Ginasta, Supriady Supriady

{"title":"Implementasi Pencarian Rute Terbaik untuk Mengetahui Lokasi Tempat Parkir pada Sistem E-Parking Menggunakan Algoritma Dijkstra dan Best First Search","authors":"Nava Gia Ginasta, Supriady Supriady","doi":"10.57152/malcom.v4i2.1261","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1261","url":null,"abstract":"Pencarian rute terbaik yaitu untuk permasalahan mencari sebuah rute terbaik dari titik awal ke titik tujuan tempat parkir. Dengan menggunakan algoritma yang dapat digunakan untuk menyelesaikan suatu masalah pencarian rute terbaik adalah Algoritma Dijkstra. Algoritma Dijkstra digunakan untuk mencari rute terbaik yang akan dilalui oleh pencari tempat parkir untuk menyimpan kendaraannya. Pemilihan rute terbaik dengan algoritma dijkstra dan Best First Search (BFS), Best First Search (BFS) diperbolehkan dalam mencari untuk mengunjungi suatu node pada levelnya yang lebih rendah, jika node pada levelnya lebih tinggi maka memiliki nilai tidak baik, terdapat 10 titik objek lokasi blok parkir, dari titik lokasi tempat masuk ke lokasi blok parkir tujuan. Untuk mempercepat waktu tempuh dan arah tujuan yang sudah ditentukan oleh Algoritma Dijkstra maka pencari tempat parkir untuk mengoptimalkan jarak tempuh menuju lokasi tujuan sehingga dapat mengefesiensi waktu yang dibutuhkan. Selain itu penyimpanan kendaraan pada tempat parkir akan lebih cepat karena sudah ditentukan jalur tujuan kendaraan yang akan disimpan.","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"4 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235446","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

Implementasi Teknologi Berbasis Web untuk Efesiensi Waktu Pencarian Lahan Parkir 采用基于网络的技术实现高效的停车场时间搜索

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1269

Sandy Yudha, Yuri Rahmanto, Styawati Styawati

{"title":"Implementasi Teknologi Berbasis Web untuk Efesiensi Waktu Pencarian Lahan Parkir","authors":"Sandy Yudha, Yuri Rahmanto, Styawati Styawati","doi":"10.57152/malcom.v4i2.1269","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1269","url":null,"abstract":"Penelitian ini bertujuan untuk mengimplementasikan teknologi berbasis web guna meningkatkan efisiensi waktu pencarian lahan parkir di kota-kota metropolitan. Sistem yang dikembangkan diharapkan dapat memberikan informasi real-time tentang ketersediaan lahan parkir, memandu pengguna menuju tempat parkir yang sesuai, dan mengurangi waktu pencarian secara signifikan. Metode penelitian ini melibatkan perancangan sistem berbasis web, dan pembuatan prototipe. Data ketersediaan lahan parkir akan dikumpulkan melalui sensor IR. Dan akan dikirimkan dari Mikrokontroler ESP 8266 Ke Website parkir. Implementasi teknologi berbasis web untuk efisiensi waktu pencarian lahan parkir diharapkan dapat memberikan hasil positif. Pengguna akan dapat mengakses informasi real-time tentang ketersediaan lahan parkir, mengurangi waktu pencarian, dan menghindari kepadatan lalu lintas yang tidak perlu. Selain itu, penerapan teknologi ini diharapkan dapat meningkatkan pengelolaan lahan parkir secara keseluruhan dan memberikan efek positif terhadap keberlanjutan lingkungan. Dengan menggabungkan teknologi berbasis web dan sensor IR, sistem ini dapat menjadi solusi efektif untuk meningkatkan efisiensi waktu pencarian lahan parkir yang semula tanpa website parkir memakan waktu 29 detik menjadi 16 detik saja sehingga dapat meminimalisir waktu sebanyak 13 detik. Implikasi positif dari penelitian ini diharapkan dapat memberikan kontribusi terhadap kemajuan kota-kota modern menuju sistem transportasi yang lebih efisien dan berkelanjutan.","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140234628","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

Implementasi Algoritma Decision Tree untuk Rekomendasi Film dan Klasifikasi Rating pada Platform Netflix 在 Netflix 平台上实现用于电影推荐和评级分类的决策树算法

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1255

Dimas Aditya Mukhsinin, M. Rafliansyah, Sang Adji Ibrahim, Rahmaddeni Rahmaddeni, Denok Wulandari

{"title":"Implementasi Algoritma Decision Tree untuk Rekomendasi Film dan Klasifikasi Rating pada Platform Netflix","authors":"Dimas Aditya Mukhsinin, M. Rafliansyah, Sang Adji Ibrahim, Rahmaddeni Rahmaddeni, Denok Wulandari","doi":"10.57152/malcom.v4i2.1255","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1255","url":null,"abstract":"Sebagai salah satu platform video streaming terbesar di dunia, Netflix telah berkembang pesat sejak pendiriannya pada tahun 1997, awalnya berfokus pada penyewaan DVD, namun kemudian beralih ke layanan streaming online pada tahun 2007. Dengan jutaan pelanggan global, Netflix terus berinovasi dengan paket langganan, produksi konten eksklusif, dan teknologi analisis data serta machine learning untuk meningkatkan pengalaman pengguna. Penelitian ini menerapkan algoritma Decision Tree untuk meningkatkan sistem rekomendasi dan klasifikasi rating di Netflix. Menggunakan dua dataset utama, movies_df dan ratings_df, penelitian melibatkan langkah-langkah pengumpulan dan penggabungan data, penentuan fitur dan variabel target, pembagian data, pelatihan model, serta evaluasi. Hasilnya mencakup evaluasi model Decision Tree dengan metrik akurasi, precision, recall, dan F1-score untuk setiap kategori rating, serta visualisasi grafik batang tentang jumlah rating film dan presentase rating dari 1-5. Rekomendasi film berdasarkan model Decision Tree juga disajikan, memberikan wawasan tentang peningkatan sistem rekomendasi di Netflix. Kesimpulan menunjukkan bahwa implementasi algoritma Decision Tree dapat meningkatkan akurasi rekomendasi film dan klasifikasi rating di Netflix, berkontribusi pada pengalaman pengguna yang lebih personal di era layanan streaming online.","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"12 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235090","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 Faktor-faktor Penentu Adopsi E-Wallet di Papua Barat: Extended UTAUT 2 dan Perceived Risk 西巴布亚省采用电子钱包的决定因素分析：扩展的 UTAUT 2 和感知风险

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-03-17 DOI: 10.57152/malcom.v4i2.1277

Agnes Dwi Oktavia, D. Inan, Rully N. Wurarah, Obadja A. Fenetiruma

{"title":"Analisis Faktor-faktor Penentu Adopsi E-Wallet di Papua Barat: Extended UTAUT 2 dan Perceived Risk","authors":"Agnes Dwi Oktavia, D. Inan, Rully N. Wurarah, Obadja A. Fenetiruma","doi":"10.57152/malcom.v4i2.1277","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1277","url":null,"abstract":"E-Wallet merupakan layanan elektronik yang digunakan sebagai tempat penyimpanan data instrumen pembayaran. LinkAja sebagai studi kasus dalam penelitian ini. Tujuan dari penelitian ini adalah mengetahui serta memahami faktor – faktor yang mempengaruhi seseorang untuk mengadopsi penggunaan E-Wallet LinkAja di Provinsi Papua Barat menggunakan model UTAUT 2, persepsi risiko dan control variable yang diukur melalui SEM-PLS. Kuesioner disebar secara online kepada masyarakat Papua Barat. Sebanyak 310 responden yang pernah menggunakan dan pengguna pasti dari aplikasi E-Wallet LinkAja diperoleh dalam penyebaran kuesioner selama satu bulan. Dari hasil penelitian, hubungan antara persepsi risiko dan niat perilaku ditolak, maka persepsi risiko tidak menjadi faktor yang mempengaruhi niat adopsi E-Wallet LinkAja di Papua Barat. Adanya hubungan antara keuntungan , kemudahan, dan pengaruh sosial terhadap niat perilaku serta hubungan antara kondisi yang memfasilitasi, persepsi risiko, dan niat perilaku terhadap niat penggunaan diterima. Maka hubungan variabel tersebut menjadi faktor yang mempengaruhi pengguna memiliki niat untuk menggunakan aplikasi E-Wallet LinkAja di Papua Barat.","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"13 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235188","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

Perbandingan Algoritma SVM dan Naïve Bayes dalam Analisis Sentimen Twitter pada Penggunaan Mobil Listrik di Indonesia 比较 SVM 算法和 Naïve Bayes 算法在有关印度尼西亚电动汽车使用情况的 Twitter 情绪分析中的应用

MALCOM: Indonesian Journal of Machine Learning and Computer Science Pub Date : 2024-02-29 DOI: 10.57152/malcom.v4i2.1253

W. Ningsih, Baginda Alfianda, Rahmaddeni Rahmaddeni, Denok Wulandari

{"title":"Perbandingan Algoritma SVM dan Naïve Bayes dalam Analisis Sentimen Twitter pada Penggunaan Mobil Listrik di Indonesia","authors":"W. Ningsih, Baginda Alfianda, Rahmaddeni Rahmaddeni, Denok Wulandari","doi":"10.57152/malcom.v4i2.1253","DOIUrl":"https://doi.org/10.57152/malcom.v4i2.1253","url":null,"abstract":"Analisis sentimen dapat mengklasifikasikan sentimen berdasarkan polaritas teks dalam sebuah frasa dan menentukannya sebagai sentimen positif, negatif, atau netral. Data sentimen ini diperoleh dari jejaring sosial Twitter berdasarkan kueri bahasa Indonesia. Tujuan dari penelitian ini adalah untuk memahami opini publik mengenai topik tertentu yang dikomunikasikan di Twitter dalam bahasa Indonesia dan untuk mendukung upaya melakukan riset pasar terhadap opini publik. Data yang dikumpulkan melalui proses pelabelan manual, preprocessing, dan pemodelan, dan model klasifikasi dibuat melalui proses pelatihan. Teknik pengumpulan data dilakukan dengan mencari catatan menggunakan istilah pencarian “kendaraan listrik” di website Kaggle.com. Algoritma yang digunakan untuk membangun model klasifikasi berdasarkan data yang diperoleh pada penelitian ini adalah Algoritma Naive Bayes dan Support Vector Machine. Nilai akurasi implementasi klasifikasi yang diperoleh algoritma Naive Bayes sebesar 63,02% dan akurasi support vector machine sebesar 70,82%. Dapat disimpulkan bahwa algoritma support vector machine mempunyai nilai akurasi yang paling tinggi.","PeriodicalId":507205,"journal":{"name":"MALCOM: Indonesian Journal of Machine Learning and Computer Science","volume":"25 31","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140408820","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