| dc.contributor.advisor | Marcelita, Faldiena | |
| dc.contributor.author | Istiqomah, Iklima | |
| dc.date.accessioned | 2025-10-17T07:27:02Z | |
| dc.date.available | 2025-10-17T07:27:02Z | |
| dc.date.issued | 2025 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/171322 | |
| dc.description.abstract | Perkembangan teknologi Internet of Things (IoT) memberikan peluang besar dalam meningkatkan efisiensi dan keandalan mesin pertanian, termasuk mesin pencacah daun yang berfungsi mengolah limbah organik menjadi kompos maupun
pakan ternak. Penelitian ini menerapkan sensor infrared (IR) untuk mengukur Revolution per Minute (RPM) dan sensor DS18B20 untuk memantau suhu dinamo yang diintegrasikan dengan mikrokontroler ESP32 berbasis IoT sehingga memungkinkan pemantauan real-time serta pencatatan data performa mesin secara akurat. Selanjutnya, analisis regresi linier digunakan untuk mengetahui hubungan antara kecepatan dinamo sebagai variabel independen dengan suhu dinamo sebagai variabel dependen, sehingga sistem tidak hanya melakukan monitoring, tetapi juga mampu memprediksi kondisi operasional berdasarkan data historis. Hasil penelitian diharapkan dapat meningkatkan efektivitas pemantauan, mendukung pengambilan keputusan operasional, serta berkontribusi terhadap penerapan IoT dalam bidang pertanian dan pengolahan limbah organik. | |
| dc.description.abstract | The development of Intenet of Things (IoT) technology provides great opportunities to improve the efficiency and reliability of agricultural machines, including leaf choppers that process organic waste into compost or animal feed. This study applies an infrared (IR) sensor to measure Revolutions per Minute (RPM) and a DS18B20 sensor to monitor the dinamo temperature, both integrated with an IoT-based ESP32 microcontroller, enabling real-time monitoring and accurate recording of machine performance data. Furthermore, linear regression analysis is used to determine the relationship between dinamo speed as the independent variable and dinamo temperature as the dependent variable, allowing the system not only to perform monitoring but also to predict operational conditions based on historical data. The results of this study are expected to enhance monitoring effectiveness, support operational decision-making, and contribute to the implementation of IoT in agriculture and organic waste processing. | |
| dc.description.sponsorship | | |
| dc.language.iso | id | |
| dc.publisher | IPB University | id |
| dc.title | Analisis Penerapan Sensor IR dan DS18B20 pada Mesin Pencacah Daun Berbasis IoT Menggunakan Regresi Linier | id |
| dc.title.alternative | Analysis of the Application of IR Sensors and DS18B20 on an IoT-Based Leaf Shredder Machine Using Linear Regression | |
| dc.type | Tugas Akhir | |
| dc.subject.keyword | IoT | id |
| dc.subject.keyword | DS18B20 sensor | id |
| dc.subject.keyword | IR Sensor | id |
| dc.subject.keyword | Leaf Chopping Machine | id |
| dc.subject.keyword | Linear Regression | id |
