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.

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.

Nowadays, some coffee production centers are still classification manually, so it requires a very long time, a lot of labor, and expensive operational costs. Therefore, the purpose of this research was to design and performance of the coffee bean classifier that can accelerate the process of classification beans. The classifier used consists of three main parts, namely the frame, driving force, and sieves. Research parameters include 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 found at a rotational speed of 91.07 rpm and a 16° sieves 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 sieves was 28.12%, and the third sieves was 15.11%. The efficiency of using a classifier was found at a rotating speed of 91.07 rpm and a sieves angle of 16°. This classifier was simple in design, easy to operate, and can sort coffee beans into three classification, namely small, medium, and large.