Penelitian ini bertujuan untuk merancang dan membangun sistem multi daya berbasis Neural Network untuk pengendalian dan pemantauan energi yang cerdas, yang dapat menangani gangguan pada jaringan distribusi listrik secara otomatis dan efisien. Sistem ini menggunakan komponen utama seperti Arduino Uno Mega, relay, dan sensor tegangan ZMPT101B. Tujuan utama dari sistem ini adalah untuk memastikan kontinuitas suplai listrik kepada konsumen meskipun terjadi gangguan pada saluran distribusi.Prototipe sistem ini dirancang untuk mendeteksi gangguan dengan cepat dan mengalihkan suplai listrik melalui jalur alternatif sehingga lampu yang terganggu dapat tetap menyala. Setiap lampu dilengkapi dengan tombol ON/OFF untuk menciptakan gangguan buatan yang digunakan dalam pengujian sistem.Hasil pengujian menunjukkan bahwa sistem ini mampu mendeteksi gangguan dalam waktu kurang dari 2 detik dan mengalihkan suplai listrik dalam waktu kurang dari 5 detik. Kesimpulannya, sistem multi daya berbasis Neural Network yang dirancang dan dibangun dalam penelitian ini berhasil mencapai tujuan yang diharapkan, yaitu menangani gangguan pada jaringan distribusi listrik dengan cepat dan efisien, serta memastikan kontinuitas suplai listrik kepada konsumen. Implementasi sistem ini diharapkan dapat menjadi solusi yang efisien dan andal dalam penanganan gangguan pada jaringan distribusi listrik di masa depan.

This study aims to design and build a multi-power system based on Neural Network for intelligent energy control and monitoring, which can handle disturbances in the electricity distribution network automatically and efficiently. This system uses main components such as Arduino Uno Mega, relay, , and ZMPT101B voltage sensor. The main purpose of this system is to ensure continuity of electricity supply to consumers even though there is a disturbance in the distribution channel. The prototype of this system is designed to detect disturbances quickly and divert the electricity supply through an alternative path so that the disturbed lights can remain on. Each lamp is equipped with an ON/OFF button to create artificial disturbances used in system testing. Testing was carried out in the laboratory to evaluate the performance of the system in detecting and handling disturbances, as well as measuring the energy efficiency achieved. The test results show that this system is able to detect disturbances in less than 2 seconds and divert the electricity supply in less than 5 seconds. This system also managed to reduce energy waste by up to 15% compared to manual disturbance handling methods. The reliability of the system was tested by simulating various disturbance scenarios, and the results showed that the system could handle 95% of the simulated disturbances effectively. In conclusion, the multi-power system based on Neural Network designed and built in this study successfully achieved the expected goals, namely handling disturbances in the electricity distribution network quickly and efficiently, and ensuring the continuity of electricity supply to consumers. The implementation of this system is expected to be an efficient and reliable solution in handling disturbances in the electricity distribution network in the future.