ANALISA DAN IMPLEMENTASI SISTEM PENGUKURAN UNSUR HARA TANAH PADA TANAMAN STROBERI BERBASIS IOT

Selama ini salah satu usaha yang dilakukan petani untuk meningkatkan produksi tanaman stroberi adalah dengan penggunaan pupuk anorganik. Produksi pertanian di Indonesia tidak lepas dari penggunaan pupuk anorganik dan menjadi hal yang sulit dipisahkan dalam kegiatan budidaya tanaman stroberi. Tuntutan pasar yang tidak lepas dari peningkatan produksi tanaman stroberi menjadikan salah satu faktor yang menjadikan pupuk anorganik menjadi tidak terpisahkan dari dunia pertanian kita. Pada perancangan alat untuk mengukur Nitrogen, Kalium dan Fosfor pada tanaman stroberi dengan metode topologi jaringan star, hardware yang digunakan yaitu sensor pengukur unsurhara tanah, sensor Soil Moisture, serta NodeMCU sebagai mikrokontroler. Sensor pengukur unsurhara tanah mengukur nitrogen, kalium, fosfor pada tanah, sensor Soil Moisture mengukur kelembapan tanah, NodeMCU berfungsi sebagai mikrokontroler dan mengirimkan data pengukuran unsur hara tanah ke realtime database. Real time database yang digunakan pada pengerjaan ini yaitu firebase. Sensor disusun membentuk topologi star, dan menganalisis jaringan tersebut apakah efektif atau tidak digunakan pada tugas akhir ini. Dari hasil pengujian yang dilakukan terhadap perangkat membuktikan bahwa perangkat dapat digunakan untuk mengukur unsurhara tanah pada tanaman stroberi. Pada pengujian fungsionalitas perangkat dapat melakukan fungsinya dengan sempurna. Pengujian untuk delay,throughput,packet received dan packet loss tergantung dari banyaknya device yang digunakan dan operator jarigan yang digunakan. Kata kunci : Nitrogen, Kalium, Fosfor, Stroberi, NodeMCU,Internet of Thing

IoT: smart garbage monitoring using android and real time database

Every single day, garbage is always produced and sometimes, due to the unbalance between high volume produced and the garbage volume transported to the landfill; it then leads to the buildup. To prevent any negative impact on environment, a system is needed to support the waste management process. Smart Garbage Monitoring System consists of two parts: portable garbage can and monitoring application using android smartphone. The use of ultrasonic sensor, GPS and GSM Module on the garbage can aims to provide the data on the garbage and send it to the real time database, in which the data will be processed by the monitoring application on smartphone to determine the time of garbage transport purposely to prevent any buildup. The system doesn't need a server to process, because the entire process of will be run by android application on a smartphone. Test results showed the capability of the system in monitoring the garbage can with the minimum distance between the wastes by three meters. The information on the height level of garbage can be synchronized in real time to smartphone, with an average delay on the EDGE network of 4.57 seconds, HSPA+ of 4.52 seconds and LTE of 3.85 seconds

Design and Performance Test of the Coffee Bean Classifier

Currently, some coffee production centers still perform classification manually, which requires a very long time, a lot of labor, and expensive operational costs. Therefore, the purpose of this research was to design and test the performance of a coffee bean classifier that can accelerate the process of classifying beans. The classifier used consisted of three main parts, namely the frame, the driving force, and sieves. The research parameters included classifier work capacity, power, specific energy, classification distribution and effectiveness, and efficiency. The results showed that the best operating conditions of the coffee bean classifier was a rotational speed of 91.07 rpm and a 16° sieve angle with a classifier working capacity of 38.27 kg/h: the distribution of the seeds retained in the first sieve was 56.77%, the second sieve was 28.12%, and the third sieve was 15.11%. The efficiency of using a classifier was found at a rotating speed of 91.07 rpm and a sieve angle of 16°. This classifier was simple in design, easy to operate, and can sort coffee beans into three classifications, namely small, medium, and large