Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/157047
Title: Sistem Monitoring Smart Trash Bin Pendeteksi Jenis Sampah Organik, Anorganik, dan Logam
Other Titles: Smart Trash Bin Monitoring System Detects Organic, Inorganic, and Metal Waste Types
Authors: Mindara, Gema Parasti
Mawaddah, Mutiara
Issue Date: 2024
Publisher: IPB University
Abstract: Permasalahan yang terjadi di gedung-gedung tinggi seperti perkantoran dan mall adalah tumpukkan sampah yang tidak dikelola melalui proses pemilahan sampah. Meskipun telah disediakan tempat sampah dengan berbagai jenisnya, masyarakat masih tidak aware dalam melakukan pemilahan sampah. Untuk mengatasinya, dibuatlah smart trash bin berbasis IoT yang menggunakan sensor kapasitif, induktif, dan infrared untuk mendeteksi sampah organik, anorganik, dan logam. Monitoring dilakukan dengan sensor ultrasonik HC-SR04 dan aplikasi Blynk untuk pemantauan real-time. Penerapan logika fuzzy membantu mengatasi ketidakpastian dan kompleksitas, menghasilkan keputusan yang lebih akurat dalam pemantauan sampah. Hasil pengujian sistem pemilah dalam mendeteksi jenis sampah menunjukkan bahwa tingkat akurasi untuk jenis organik sebesar 86.66%, anorganik sebesar 96.66%, dan logam sebesar 93.33%. Hasil pengujian sensor ultrasonik dalam mengonversi ketinggian sampah (cm) ke bentuk kapasitas (%) didapatkan tingkat akurasi untuk jenis organik sebesar 98.68%, anorganik sebesar 98.78%, dan logam 98.65% dengan hasil pengujian pengujian jarak sensor ultrasonik HC-SR04 pada ketiga jenis sampah organik, anorganik dan logam memiliki nilai toleransi sebesar ±0.2667 cm.
The problem that occurs in tall buildings such as offices and malls is piles of rubbish that are not managed through a waste sorting process. Even though various types of waste bins have been provided, people are still unaware of how to sort waste. To overcome this, an IoT-based smart trash bin was created which uses capacitive, inductive, and infrared sensors to detect organic, inorganic, and metal waste. Monitoring is carried out with the HC-SR04 ultrasonic sensor and the Blynk application for real-time monitoring. Applying fuzzy logic helps overcome uncertainty and complexity, resulting in more accurate decisions in waste monitoring. The results of testing the sorting system in detecting types of waste show that the level of accuracy for organic types is 86.66%, inorganic is 96.66%, and metal is 93.33%. The results of ultrasonic sensor testing in converting waste height (cm) to capacity (%) showed that the accuracy level for organic types was 98.68%, inorganic was 98.78%, and metal was 98.65% with the results of the HCSR04 ultrasonic sensor distance test on the three types of waste. organic, inorganic and metal have a tolerance value of ±0.2667 cm.
URI: http://repository.ipb.ac.id/handle/123456789/157047
Appears in Collections:UT - Computer Engineering Tehcnology

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