Internet of things (IoT) and fuzzy logic are very useful in increasing the efficiency and effectiveness of a system; this study applies both to the street lighting systems. The prototype of a street lighting control and monitoring system has been completed. The status of lights that are on or off and the value of the light intensity can be monitored by using IoT. The intensity of the light is fuzzy controlled by utilizing the presence of vehicles and pedestrians around the lights. The prototype is made with a scale against real conditions. Data is processed and transmitted using a microcontroller and Wi-Fi on the IoT module. Mobile applications have been used on smartphone interfaces to monitor and control lamps wherever they are connected to the Internet. Changes in the status of lights to turn on or off are done by the relay module. The fuzzy light intensity control system uses sensors and microcontrollers by utilizing the presence of vehicles and pedestrians around the lights. Performance evaluation has been carried out on a miniature street lighting with the results of monitoring and control following its function. An analysis of the resulting energy savings has been demonstrated.

This paper aims the street lighting efficiency optimization of street lighting on Dr. Setiabudhi street, Bandung city. Particle Swarm Optimization (PSO) algorithm is used to get maximum lighting efficiency values with constraints in the form of lamp height, the distance between lights, lamp power, type/width of the street, the average illuminance and minimum illuminance according to Indonesian national standards (SNI) standards. Parameter optimization to obtain optimal values based on global standards and Indonesian national standards (SNI) has been done. PSO using MATLAB® (R2017a, MathWorks Inc, USA) has produced a street lighting optimization model with the level of lighting efficiency twice higher than the evaluation of existing conditions. Testing the results of the PSO algorithm shows a difference of 9.7% higher than the DIALux evo (8.0, Ludenscheid, Germany) software design. The test results show that the PSO algorithm can be used to obtain optimum lighting efficiency from a public street lighting system following SNI.

The public health monitoring system at the Integrated Service Post (Posyandu) is a form of integrated health service carried out in a Puskesmas working area where the implementation is carried out in each Kelurahan or RW. It can be said that the system is not optimal because during the Covid-19 virus pandemic we have to minimize activities that are physical in nature, such as the use of health books which are currently being used less than optimally for the community because it allows for the spread of the Covid-19 virus. Then the monitoring system still uses email for sending data from Posyandu to Puskesmas, Puskesmas to the Health Office and Health Office to the Ministry of Health. This system is not profitable, because in addition to requiring a lot of time for data transmission, the data sent may fail or not be successfully sent. Solutions related to these problems can be solved by creating a multi-platform-based maternal and child health monitoring system, the monitoring system here can already be done in real time using a database so there is no need for manual data transmission such as via email. In just a few seconds, the data received by the Posyandu from the community will be monitored directly by the Puskesmas, the Health Service and the Ministry of Health. In addition, the data that was previously collected in the form of a book is now replaced with an application that can be opened via a smartphone which contains data along with children's development charts. So that the community and other health care parties can access children's development simply by using a smartphone. In addition, the data will also be managed very well and the data will be maintained when using the application when compared to using a book, the data can be damaged or lost.

The clothing and food industry had to require for each product which is produced by them is free of dangerous metal. To handle the problem, the industry did anyways to decreasing metal contents that might be involved in the product. One of the methods that the industry able to do is metal sorter automatically system that used to do when the product is on the conveyor. This method is counted so efficiently if we know that the conveyor is used for moving an item from a place to another place by using an induction motor as a mover. This research purposes of presenting an example of a Programmable Logic Controller (PLC) uses as an electronic device that able to control the conveyor metal sorter system automatically. We used a photoelectric sensor to detect an item on the conveyor. Meanwhile, inductive proximity is used to detect metal content behind the item. This research also is written on how this PLC is more efficient if we compared it with using the conventional relay.

Abstrak : Teknologi Soft Computing telah membantu banyak peneliti dalam mengembangkan sebuah penelitiannya. Contohnya adalah pengembangan model prediksi beban listrik harian non linier berbasis kecerdasan buatan yang menggunakan algoritma Backporpagation dan algoritma Kohonen Map. Kode computer yang dikembangkan menggunakan software Matlab R2008b dari Mathwork Corp. Dapat dilihat dari hasil perhitungan bahwa keakuratan model Backpropagation 99,83 % sedangkan model Kohonen Map hanya 97,53 %. Dengan demikian dapat disimpulkan bahwa model prediksi menggunakan algoritma Backpropagation lebih baik tingkat akurasinya dibandingkan dengan model prediksi menggunakan metoda Kohonen Map.