Sukemi Sukemi
About
In The Last Decade
Sukemi Sukemi
58 papers receiving 272 citations
Peers
Comparison fields: 5 of 95
- Information Systems 64
- Artificial Intelligence 54
- Cardiology and Cardiovascular Medicine 49
- Insect Science 37
- Cognitive Neuroscience 30
Countries citing papers authored by Sukemi Sukemi
This map shows the geographic impact of Sukemi Sukemi'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 Sukemi Sukemi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sukemi Sukemi more than expected).
Fields of papers citing papers by Sukemi Sukemi
This network shows the impact of papers produced by Sukemi Sukemi. 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 Sukemi Sukemi. The network helps show where Sukemi Sukemi may publish in the future.
Co-authorship network of co-authors of Sukemi Sukemi
This figure shows the co-authorship network connecting the top 25 collaborators of Sukemi Sukemi. A scholar is included among the top collaborators of Sukemi Sukemi 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 Sukemi Sukemi. Sukemi Sukemi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | Penghapusan Noise Pada Citra Kamera CCTV Menggunakan Metode Gaussian Filter | 0 |
| 10 | Agglomerative Hierarchical Clustering Dengan Berbagai Pengukuran Jarak Dalam Mengklaster Daerah Berdasarkan Tingkat Kemiskinan | 3 |
| 11 | UPAYA MENINGKATKAN KOMPETENSI GURU DALAM MENGELOLA ADMINISTRASI KELAS MELALUI SUPERVISI KLINIS PADA GURU DI SD NEGERI SENDANG 01 TAHUN PELAJARAN 2018/2019 | 0 |
| 12 | Pengaruh Model Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) Terhadap Penerapan Aplikasi Shopee | 2 |
| 13 | Optimasi QR-Code pada Sistem Kasir di Industri Retail | 2 |
| 14 | Noise Removal Pada Citra Digital Menggunakan Metode Gaussian filter | 2 |
| 15 | Akurasi Klasifikasi Citra Digital Scenes RGB Menggunakan Model K-Nearest Neighbor dan Naive Bayes | 2 |
| 16 | Klasifikasi Sentimen Analisis Kartun Dengan Metode Optical Character Recognition (OCR) Dan Algoritma K-Nearest Neighbour (KNN) | 1 |
| 17 | Analisis Penyakit Jantung Menggunakan Metode KNN Dan Random Forest | 7 |
| 18 | Perhitungan Peramalan Harga Emas Menggunakan Metode Single Exponential Smoothing Dan Single Moving Average | 2 |
| 19 | Klasifikasi Tingkat Kematangan Buah Tomat Berdasarkan Fitur Warna Menggunakan K-Nearest Neighhbor | 1 |
| 20 | PENINGKATAN MINAT BELAJAR SISWA KELAS VA SD NEGERI JETIS 1 YOGYAKARTA MELALUI PROBLEM SOLVING SYSTEMATIC | 0 |
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.