This research aims to design and test a genset fuel conversion system from gasoline to HHO gas (brown gas) as a more environmentally friendly alternative. Conventional fossil-fueled generators face challenges in theform of limited resources and the impact of environmental pollution. In this study, HHO gas is produced through a water electrolysis process using an HHO generator that separates water molecules into hydrogen and oxygen using electric current. The test results show that increasing the voltage from 2.58 V to 5.12 V significantly increases the volume of gas produced. At a voltage of 2.58 V, the gas volume reached 110 ml, and increased to 750 ml at a voltage of 4.72 V. The generator set was successfully operated for 1 minute 15 seconds with HHO gas using a separate battery power source. These results demonstrate the potential of HHO gas as an efficient alternative fuel for generator sets. This study recommends further testing with voltage and current variations to find the optimal configuration, as well as the use of a larger power source to increase the efficiency of HHO gas electrolysis.

This study examines the role of Artificial Intelligence (AI) in marketing strategy through a Systematic Literature Review (SLR) approach. AI has shown a transformative impact by outperforming traditional methods, especially in optimizing big data-based marketing strategies. With the ability to analyze consumer behavior in depth, AI enables businesses to personalize marketing efforts and improve user experiences more efficiently and responsively. However, challenges such as data privacy, high initial investment, and reliance on data quality remain major concerns that must be addressed. This study also evaluates the effectiveness of using AI across marketing channels, which shows significant differences in their impact on business strategy. In addition, the integration of AI-based fitness equipment is considered to have a major contribution in increasing consumer satisfaction while driving online business growth. The results of this study provide valuable insights into the effective implementation of AI, as well as highlight the importance of maintaining data security and implementing AI strategically to provide optimal benefits for consumers and business development.

Induction motors are components that convert electrical energy into mechanical energy and are very much in demand among industries, with low prices, sturdy construction and easy maintenance making these induction motors used for heavy industrial applications. However, the 3-phase induction motor at this time chooses a low torque and speed so that it affects the efficiency of the induction motor performance, which will decrease.  This study examines the effect of unsymmetrical 2-layer 6-phase induction motor design on the torque and speed of 3-phase induction motors using the finite element method. This research was conducted using Ansys software, which aims to see the magnetic flux density and the effect of 6-phase induction motor design on the torque and speed of a 3-phase induction motor using the finite element method. The induction motor that is the reference for this research has specifications of a 3-phase induction motor: 0.75 KW, 1 HP, 220/380 V, 3.5/2 A, 50 Hz, 1390 rpm. From the results of this study, the simulation results of the shape of the flux density ... which is designed with the parameters of a 3-phase induction motor with an unsymmetrical 6-phase 2-layer induction motor coil design.