PENGEMBANGAN SENSOR WARNA BERBASIS ARDUINO UNTUK DETEKSI WARNA KARET RSS
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Abstract
The quality of rubber products, particularly Ribbed Smoked Sheet (RSS), is crucial for Indonesia's automotive industry. Currently, quality assessment at PT KMS Rubber Factory relies on visual inspection, leading to subjective and inconsistent results. To address this, this study developed an RRS color detection system using a TCS3200 sensor and Arduino. The research followed a waterfall methodology, with testing conducted at Ahmad Dahlan University and PT KMS using RRS samples of varying quality. Results showed that the TCS3200 sensor effectively detected color variations with reasonable accuracy, though unstable lighting conditions affected performance. The use of a black box significantly minimized external light interference. Additionally, the study revealed that the factory’s RRS quality was actually categorized as RRS 2 and RRS 3, contrary to workers' visual assessment, which had classified it as RRS 1. This system offers an efficient solution for the rubber industry, particularly for small producers and farmers, to enhance quality control. Furthermore, the device serves as a practical educational tool for learning about color, light, and sensor technology. Thus, this innovation has strong potential to improve rubber product quality and production efficiency in Indonesia.
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References
Amani, R. Z., Maulana, R., & Syauqy, D. (2017). Sistem pendeteksi dehidrasi berdasarkan warna dan kadar amonia pada urin berbasis sensor TCS3200 dan MQ135 dengan metode Naive Bayes. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 1(5), 436–444.
Angela, Willy. (2022). Prototipe Penyortiran Buah Tomat Berdasarkan Tingkat Kematangan Menggunakan Sensor Warna TCS3200. Jurnal Ilmiah Teknik dan Ilmu Komputer.
Banerjee, S.&[Anonymous]. (2018). Arduino for Beginners: A Comprehensive Guide to Learn Arduino Programming and Prototyping. CreateSpace Independent Publishing Platform.
Haug, M. (2011). Smart Sensors for Industrial Applications. In Sensor Technology Handbook.
Iskandar, J., & Utami, D. K. (2019). Penerapan fuzzy logic untuk meningkatkan derajat kebenaran deteksi pada alat bantu buta warna berbasis sensor optik. Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika, 16(1), 195–202. https://doi.org/10.33751/komputasi.v16i1.1590
Kamilia, N. D., Suyanto, A., & Iswanto, I. (2021). Perancangan Prototype Pendeteksi Warna Sampah Sensor Otomatis Berbasis Arduino terhadap Ketepatan Pemilahan Sampah. Sanitasi: Jurnal Kesehatan Lingkungan, 9(2), 45–53.
Kementerian Pertanian. (2021). Analisis Kinerja Perdagangan Karet. Jakarta: Pusat Data dan Sistem Informasi Pertanian Kementerian Pertanian.
Mahendra, W., Syauqy, D., & Budi, A. S. (2020).
Rancang Bangun Sistem Klasifikasi Rasa Permen Karet Berdasarkan Warna Dengan Metode K Nearest Neighbor (KNN). Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 5(10), 3547–3555.
Mede, A. I. D., Roessali, W., & Nurfadillah S (2021). Analisis Risiko Produksi Karet Ribbed Smoked Sheet (Studi Kasus Di Kebun Merbuh, PTPN IX).Jurnal Litbang Provinsi Jawa Tengah,19(1), 57-70.
Oktavia, V., Suroso, E., & Utomo, T.P. (2014). Strategi Optimalisasi Bahan Baku Lateks Pada Industri Karet Jenis Ribbed Smoked Sheet(RSS). Jurnal Teknologi & Industri Hasil Pertanian, 19(2), 179-193.
Oney, A. B. (2021). Color Sensors and Their Applications in Agriculture. Journal of Agricultural Engineering, 15-22. Press, U. (2020). Pengantar Metode Penelitian Berbasis Proyek.
Rahman, M. & [Anonymous]. (2021). Penggunaan Mikrokontroler Arduino pada Sistem Pertanian Cerdas. Jurnal Pertanian Digital, 210-225.
Raut, R. D., Kamble, S. S., & Prasad, R. (2020).
Application of Internet of Things (IoT) for sustainable agriculture.
Information Processing in Agriculture, 7(3), 370–382.
Sasmoko, D., Sanjaya, E., & Veliyanti, R. (2024). Sistem deteksi warna dengan TCS3200 dan BH1750 untuk penentuan warna karpet yang valid pada proses inspeksi [Makalah seminar, SEMNASTEKMU]. Prosiding Seminar Nasional Teknologi dan Multidisiplin Ilmu. https://doi.org/10.51903/semnastekmu.v1i1.111
Sharma, A. & [Anonymous]. (2019). Role of Modern Technology in Agriculture: A Review. International Journal of Agriculture and Food Science Technology, 51-60.
Sharma, K. (2020). Implementation of Color Sensors in Agriculture for Real-time Crop Monitoring. Journal of Agricultural Sciences and Applications, 110-118.
TAOS. TCS3200 TCS3210 Programmable Color Light to Frequency Converter TAOS009. United States, 2009.
Wibowo, A., Poningsih, I., Parlina, I., Suhada, & Wanto, A. (2022). Rancang bangun mesin sortir buah kelapa sawit berdasarkan tingkat kematangan menggunakan sensor warna TCS3200 berbasis Arduino Uno. Universitas Islam Riau Pekanbaru.
Zulkarnain, I., Ramadhan, M., & Anwar, B. (2019, July 8). Implementasi alat pendeteksi warna benda menggunakan fuzzy logic dengan sensor TCS3200 berbasis Arduino. Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD, 2(2), 106–117.