Author profile OpenAlex ID
Hurriyatul Fitriyah
- Articles in Melola
- 7
- Citations (OpenAlex)
- 19
- Journals
- IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Journal of ICT Research and Applications (JICTRA); Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
- ORCID
- 0000-0002-2754-2104
- OpenAlex
- A5056867848
- Name in journal metadata
- Fitriyah, Hurriyatul
Co-authors
10 authors · 18 co-authorship links
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Rizal Maulana | University of Brawijaya | 2 |
| Eko Setiawan | University of Brawijaya | 2 |
| Edita Rosana Widasari | University of Brawijaya | 1 |
| Agung Setia Budi | University of Brawijaya | 1 |
| Gembong Edhi Setyawan | University of Brawijaya | 1 |
| Benny Adiwijaya | University of Brawijaya | 1 |
| Dahnial Syauqy | University of Brawijaya | 1 |
| Faizal Andy Susilo | University of Brawijaya | 1 |
| Fahmi Erza | University of Brawijaya | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.
Articles
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Sistem Object Tracking pada Quadcopter Menggunakan Segmentasi Citra dengan Deteksi Warna HSV dan Metode Regresi Linier Berbasis Raspberry Pi
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Accuracy of Various Methods to Estimate Volume and Weight of Symmetrical and Non-Symmetrical Fruits using Computer Vision
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Controlling the Nutrition Water Level in the Non-Circulating Hydroponics based on the Top Projected Canopy Area
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Deteksi Gulma Berdasarkan Warna HSV dan Fitur Bentuk Menggunakan Jaringan Syaraf Tiruan
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Face Detection of Thermal Images in Various Standing Body-Pose using Facial Geometry
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Deteksi Kesegaran Ikan Tongkol (Euthynnus Affinis) secara Otomatis Berdasarkan Citra Mata Menggunakan Binary Similarity
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Sistem Deteksi Jumlah, Jenis dan Kecepatan Kendaraan Menggunakan Analisa Blob Berbasis Raspberry Pi
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