Klasifikasi Sampah Plastik di Laut Menggunakan Algoritma Faster R-CNN (Studi Kasus Tanjungpinang)

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Published: Jun 3, 2026
DOI: https://doi.org/10.34128/jsi.v12i1.1606
Keywords:
Faster R-CNN, Pre-Trained Model, Floating Plastic Waste Classification, mAP, Test Data Accuracy

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Novrizal Fattah Fahmitra
Universitas Maritim Raja Ali Haji
Farel Putra Albana
Universitas Maritim Raja Ali Haji
Muhamad Radzi Rathomi
Universitas Maritim Raja Ali Haji

Abstract

The global environment is facing a serious challenge in the form of increasing plastic waste. Indonesia is one of the world’s largest producers of plastic waste, and Tanjungpinang City faces a similar issue, generating approximately 100–150 tons of waste per day, predominantly plastic waste. A significant portion of this waste originates from marine environments, while its management remains limited by inadequate facilities and technological resources. Therefore, a waste detection solution is needed to improve the efficiency of plastic waste management in the region.. This study aims to evaluate the detection performance of a Faster R-CNN model using pre-trained weights with a ResNet-50 Feature Pyramid Network (FPN) backbone. Experimental results show an [email protected]:0.95 of 59.55% and an [email protected] of 82.64%. Further evaluation for each plastic waste category resulted in accuracies of 90% for plastic bottles, 88% for food wrappers, 78% for beverage wrappers, and 86% for plastic bags. These findings indicate that the pre-trained Faster R-CNN model with a ResNet-50 FPN backbone is capable of effectively detecting and classifying different types of plastic waste in marine environments. Consequently, this model has the potential to support more effective waste management and sorting processes in the coastal waters of Tanjungpinang City.

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How to Cite
[1]
N. F. Fahmitra, F. P. Albana, and M. R. Rathomi, “Klasifikasi Sampah Plastik di Laut Menggunakan Algoritma Faster R-CNN (Studi Kasus Tanjungpinang)”, JSI, vol. 12, no. 1, pp. 1–10, Jun. 2026.
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Vol. 12 No. 1 (2026): Jurnal Sains dan Informatika
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Author Biographies

Novrizal Fattah Fahmitra, Universitas Maritim Raja Ali Haji

Penulis merupakan dosen Program Studi Teknik Informatika di Universitas Maritim Raja Ali Haji. Penulis memperoleh gelar Sarjana Teknik Informatika di STMIK Amikom pada Tahun 2015 dan gelar Magister Komputer bidang Informatika Medis di Universitas Islam Indonesia pada tahun 2023.

Farel Putra Albana, Universitas Maritim Raja Ali Haji

Penulis merupakan mahasiswa lulusan di Universitas Maritim Raja Ali Haji pada program studi Teknik Informatika. Penulis pernah menjadi salah satu bagian dari Program Pertukaran Mahasiswa Merdeka Batch 4 di Universitas Dian Nuswantoro dan Program Kreativitas Mahasiswa bidang Pengabdian kepada Masyarakat tahun 2024.

Muhamad Radzi Rathomi, Universitas Maritim Raja Ali Haji

Penulis merupakan dosen Program Studi Teknik Informatika di Universitas Maritim Raja Ali Haji. Penulis memperoleh gelar Sarjana Sistem Informasi di Universitas Lancang Kuning pada Tahun 2011 dan gelar Magister Ilmu Komputer di Universitas Gadjah Mada pada tahun 2016.

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