Desain Prototipe Automatic Trash Rake dengan Metode Gaussian Mixture Model

Yuliadi Erdani, Wahyu Adhie Candra, Aulia Aisyah

Abstract

Trash rake is a trash netting tool used to transport trash in rivers. In its application, the operation of trash rake is still mostly done manually by the operator. In this case, there is no effectiveness in terms of the use of human resources or the effectiveness of machines. Therefore, in this study, a development was made on an automatic trash rake machine that works automatically if the waste stuck on the trash rake machine has experienced density. The image processing method used is the Gaussian Mixture Model (GMM). Used camera to capture the image of the density of the trash. The captured image is processed by GMM method. Then the data is processed on a computer and the data is displayed on the web. Arduino will drive the motor on the trash rake machine automatically with the parameters of the waste density data. The results obtained, the system can detect the level of waste density with an accuracy of 67.5% in bright, dim and dark conditions with the camera position according to the object observation area. The trash rake machine can turn on and off automatically based on the detected waste density.


Keywords

camera, opencv, image processing, trash

References

Abimanyu, K., & Rohman, S. (2019). Robot Perahu Pengangkut Sampah Berbasis Pengolahan Citra Garbage Carrier Roboboat Based On Image Processing. 7(1). https://doi.org/10.34010/telekontran.v7i1.1636

Alfaresi, B., Afandi, & Ardianto, F. (2022). Desain Dan Perancangan Miniatur Alat Penyaring Sampah Otomatis Berbasis Plc. Electrician, 16(2), 129–137. https://doi.org/10.23960/elc.v16n2.2227

Amaluddin, F., Muslim, M., & Naba, A. (2015). Klasifikasi Kendaraan Menggunakan Gaussian Mixture Model (GMM) Dan Fuzzy Cluster K Means (FCM). Jurnal EECCIS, 9(1), pp.19-24.

Cahyati, S., & Ramdhani, Y. (2021). Aplikasi Android Monitoring Tempat Sampah Pintar Berbasis Internet of Things. E-Prosiding Teknik Informatika. 2(1), 112–121.

Fatmawati, K., Sabna, E., & Irawan, Y. (2020). Design of a Smart Trash Can Using an Arduino Microcontroller-Based Proximity Senso. Riau Journal Of Computer Science, 6(2), 124–134.

Isnawaty, I., Subardin, S., & Normawan, L. L. (2022). Penerapan Internet Of Things (Iot) Pada Sistem Monitoring Tempat Sampah Rumah Tangga Menggunakan Metode Haversine Formula. Digital Transformation Technology, 2(2), 35–44. https://doi.org/10.47709/digitech.v2i2.1803

Juwariyah, T., Krisnawati, L., & Sulsasminingsih, S. (2020). Sistem Monitoring Terpadu Smart Bins Berbasis IoT Menggunakan Aplikasi Blynk. JIRE (Jurnal Informasi & Rekayasa Elektronika), 3(2), 91–99. https://e-journal.stmiklombok.ac.id/index.php/jire/article/view/247

Khoiriyah, H. (2021). Analisis Kesadaran Masyarakat Akan Kesehatan Terhadap Upaya Pengelolaan Sampah di Desa Tegorejo Kecamatan Pegandon Kabupaten Kendal. Indonesian Journal of Conservation, 10(1), 13–20. https://doi.org/10.15294/ijc.v10i1.30587

Kim, Y. Y., Kim, H., Lee, W., Choi, H. L., & Moon, I. C. (2021). Black-box expectation–maximization algorithm for estimating latent states of high-speed vehicles. Journal of Aerospace Information Systems, 18(4), 175–192. https://doi.org/10.2514/1.I010831

Nggilu, A., Raffi Arrazaq, N., & Thayban, T. (2020). Dampak Pembuangan Sampah Di Sungai Terhadap Lingkungan Dan Masyarakat Desa Karya Baru.

Pratama, G. (2020). Upaya Modernisasi dan Inovasi Pengelolaan Sampah Berbasis Masyarakat di Desa Leuwimunding Majalengka. Etos : Jurnal Pengabdian Masyarakat, 2(1), 37. https://doi.org/10.47453/etos.v2i1.209

Putra, B. C., & Afifah, Y. N. (2018). Gaussian Mixture Model Untuk Penghitungan Tingkat Kebersihan Sungai Berbasis Pengolahan Citra. 2(1), 53–58.

Putry, A. D. F., Faiqoh, D., & Widyansyah, N. H. (2020). Monitoring Level Sampah pada Sungai di Sekitar Pemukiman Melalui Sensor Alarm Berbasis Realtime. Journal of Advances in Information and Industrial Technology, 2(2), 45–51. https://doi.org/10.52435/jaiit.v2i2.71

Rima Dias Ramadhani, Nur Aziz Thohari, A., Kartiko, C., Junaidi, A., Ginanjar Laksana, T., & Alim Setya Nugraha, N. (2021). Optimasi Akurasi Metode Convolutional Neural Network untuk Identifikasi Jenis Sampah. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 5(2), 312–318. https://doi.org/10.29207/resti.v5i2.2754

Saubari, N., Gazali, M., & Ansari, R. (2019). Metode HLF untuk Deteksi Objek Terapung pada Permukaan Sungai Martapura HLF Method for Detecting Floating Objects on the Surface of Martapura River. JISKa, 4(2), 118–124.

Siregar, R. C., Hidayat, M. R., Sambasri, S., & Rahmatullah, G. M. (2020). Rancang Bangun Prototype Sistem Pendeteksian Sampah Pada Aliran Air Menggunakan Metode Background Subtraction. Researchgate.Net, September. https://doi.org/10.17977/um034v30i1p75-88

Sistem, R., Tribuana, D., & Arda, A. L. (2024). JURNAL RESTI Image Preprocessing Approaches Toward Better Learning Performance with CNN. 5(158), 6–9.

Sudarsana, P. B., Winata, I. M. P. A., & Subagia, I. D. G. A. (2022). Rancang bangun sistem penangkap sampah Daerah Aliran Sungai (DAS) berbasis integrasi screw conveyor dan sistem pemantauan menggunakan Internet of Things (IoT). Jurnal Energi Dan Manufaktur, 14(1), 1. https://doi.org/10.24843/jem.2021.v14.i01.p01

Sutiyana, L., Nugraha, R. A., & ... (2019). Optimasi Desain Trash Rack Dengan Parameter Nilai Head Loss Menggunakan Full Factorial Design. EProceedings …, 6(2), 6376–6381. https://openlibrarypublications.telkomuniversity.ac.id/index.php/engineering/article/view/9889

Wahjuni, S. R. I., & Zakiah, R. A. (n.d.). Sistem Pemantauan Volume Timbulan Sampah berbasis Internet of Things di Tempat Penampungan Sementara Kota Bogor Internet of Things based Volume Monitoring System for Waste Disposal in Bogor City. 9, 114–126.

Yuniantari, N. K. H. S., Aryana, I. K., & Jana, I. W. (2022). Hubungan Tingkat Pengetahuan Dan Pekerjaan Kepala Keluarga Dengan Tingkat Partisipasi Dalam Pelaksanaan Program Bank Sampah. Repository Poltekkes Depansar, 12(1), 7–16.

DOI

https://doi.org/10.21107/rekayasa.v17i1.21148

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