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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 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| cover_J0304201040_1a5dad163f5947c88161001a8bbc673a.pdf | Cover | 332.68 kB | Adobe PDF | View/Open |
| fulltext_J0304201040_df404c43cb8044cb9dfb06f385409d95.pdf Restricted Access | Fulltext | 1.12 MB | Adobe PDF | View/Open |
| lampiran_J0304201040_1a2268ea4e1b42cda4ae4d90c3424449.pdf Restricted Access | Lampiran | 7.78 MB | Adobe PDF | View/Open |
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