Pendeteksi Mobil Berdasarkan Merek dan Tipe Menggunakan Algoritma YOLO Article Swipe
Al Riansyah
,
Ahmad Haidar Mirza
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.32664/smatika.v13i01.719
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.32664/smatika.v13i01.719
Sistem pemeritah di suatu wilayah atau kota memiliki peraturan dalam mengatur aktivitas penduduknya, terutama yang berkaitan berkendara di jalan raya. Pelanggaran lalulintas kerap terjadi di jalan perkotaan maupun jalan raya. Hal ini dapat memicu kecelakaan akibat melanggar peraturan lalulintas. Hal tersebut mendorong pemerintah untuk mengambil tidak tegas bagi para pengendara yang melanggar peraturan. Maka dari itu diperlukan sebuah sistem yang mampu membantu memantau kondisi lalu lintas. Sehingga penelitian ini bertujuan untuk membuat sistem yang mampu mendeteksi kendaraan mobil berdasarkan merek dan tipenya dengan tingkat akurasi pendeteksian yang tinggi, sehingga dapat mepermudah dalam mengenali objek mobil yang ada di sekitar. Sistem pendeteksi akan dikembangkan menggunakan Algoritma YOLO (You Only Look Once), karena YOLO adalah salah satu metode paling cepat dan akurat dalam pendeteksian objek bahkan mampu melebihi hingga 2 kali kemampuan algoritma lain. Algoritma YOLO (You Only Look Once) merupakan arsitektur dari deep learning dan sebuah algoritma yang dikembangkan untuk mendeteksi sebuah objek secara real-time. Pendeteksian dilakukan pada gambar, dan ketika akses webcam laptop yang didalamnya terdapat objek mobil menggunakan model dari dataset yang telah di training menggunakan framework Darknet. Objek mobil yang terdeteksi akan terdapat bounding box di area objek tersebut, dan terdapat keterangan nama mobil dan tipe serta tahun produksinya pada area bounding box tersebut. Berdasarkan pengujian kinerja klasifikasi dari data yang telah dilakukan training menunjukkan bahwa nilai akurasi mencapai 92% sehingga dapat disimpulkan bahwa sistem dapat bekerja dengan baik.
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Metadata
- Type
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- id
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- https://doi.org/10.32664/smatika.v13i01.719
- https://jurnal.stiki.ac.id/SMATIKA/article/download/719/566
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4384157709Canonical identifier for this work in OpenAlex
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https://doi.org/10.32664/smatika.v13i01.719Digital Object Identifier
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Pendeteksi Mobil Berdasarkan Merek dan Tipe Menggunakan Algoritma YOLOWork title
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articleOpenAlex work type
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idPrimary language
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2023Year of publication
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2023-06-28Full publication date if available
- Authors
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Al Riansyah, Ahmad Haidar MirzaList of authors in order
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https://doi.org/10.32664/smatika.v13i01.719Publisher landing page
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https://jurnal.stiki.ac.id/SMATIKA/article/download/719/566Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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Physics, Humanities, ArtTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2024: 1, 2023: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| corresponding_institution_ids | https://openalex.org/I1325072066 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.6200000047683716 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.66671592 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |