Said Al Faraby
About
In The Last Decade
Said Al Faraby
48 papers receiving 391 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 291
- Information Systems 224
- Computer Vision and Pattern Recognition 38
- Sociology and Political Science 33
- Management Science and Operations Research 21
Countries citing papers authored by Said Al Faraby
This map shows the geographic impact of Said Al Faraby's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Said Al Faraby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Said Al Faraby more than expected).
Fields of papers citing papers by Said Al Faraby
This network shows the impact of papers produced by Said Al Faraby. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Said Al Faraby. The network helps show where Said Al Faraby may publish in the future.
Co-authorship network of co-authors of Said Al Faraby
This figure shows the co-authorship network connecting the top 25 collaborators of Said Al Faraby. A scholar is included among the top collaborators of Said Al Faraby based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Said Al Faraby. Said Al Faraby is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 7 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | Analisis Sentimen Mengenai Rencana Vaksinasi Covid-19 Menggunakan Support Vector Machine Dengan String Kernel | 1 |
| 8 | 2 | |
| 9 | Klasifikasi Topik Multi Label pada Hadis Bukhari dalam Terjemahan Bahasa Indonesia Menggunakan Random Forest | 3 |
| 10 | Implementasi Alignment Point Pattern Pada Sistem Pengenalan Sidik Jari Menggunakan Template Matching | 1 |
| 11 | Klasifikasi Topik Ayat Al-Qur’an Terjemahan Berbahasa Inggris Menggunakan Metode Support Vector Machine Berbasis Vector Space Model dan Word2Vec | 2 |
| 12 | KLASIFIKASI DOKUMEN MENGGUNAKAN METODE KNN DENGAN INFORMATION GAIN | 1 |
| 13 | Klasifikasi Sentiment Analysis pada Review Film Berbahasa Inggris dengan Menggunakan Metode Doc2Vec dan Support Vector Machine (SVM) | 2 |
| 14 | Analisis Dan Implementasi Support Vector Machine Dengan String Kernel Dalam Melakukan Klasifikasi Berita Berbahasa Indonesia | 5 |
| 15 | Klasifikasi Sidik Jari Menggunakan Metode Minutiae | 2 |
| 16 | Analisis Churn Prediction Pada Data Pelanggan Pt. Telekomunikasi Menggunakan Underbagging Dan Logistic Regression | 1 |
| 17 | Klasifikasi Anjuran, Larangan Dan Informasi Pada Hadis Sahih Al-bukhari Berdasarkan Model Unigram Menggunakan Artificial Neural Network (ann) | 0 |
| 18 | ANALISIS CHURN PREDICTION MENGGUNAKAN METODE LOGISTIC REGRESSION DAN SMOTE (Synthetic Minority Over-sampling Technique) PADA PERUSAHAAN TELEKOMUNIKASI | 2 |
| 19 | Klasifikasi Sentimen Pada Movie Review Dengan Metode Multinomial Naïve Bayes | 2 |
| 20 | Implementasi Dan Analisis Kesamaan Semantik Pada Bahasa Indonesia Dengan Metode Berbasis Vektor | 1 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.