Nowadays consumers tend to substitute their habits in consuming cow milk into soy milk since it has reliability on health issue, taste, and healthy lifestyle. Referencing to prior researches, health consciousness and main theory of planned behavior (TPB) factors including attitude, subjective norms, and perceived behavioral control significantly influence consumer purchase intention. Researchers aimed to analyze health consciousness influence toward consumer purchase intention to cow milk and soy milk and formulate managerial implications to escalate consumer purchase intention to cow milk and soy milk. This research was conducted in Jakarta, Bogor, Depok, Tangerang, and Bekasi (Jabodetabek) area from October 2023 until April 2024 with 300 respondents. Researchers used voluntary response sampling as sampling method. Analysis methods used by researchers were descriptive analysis, structural equation modelling-partial least square (SEM-PLS) analysis, and importance performance matrix (IPMA) analysis. Results showed that health consciousness doesn’t influence purchase intention to cow milk significantly yet influences purchase intention to soy milk significantly. Otherwise trust, attitude, subjective norms, and perceived behavioral control influence purchase intention to both milks significantly. Furthermore, consumer purchase intention toward cow milk and soy milk can be escalated through improving performances of trust and subjective norms. For trust, producer needs to promote producer reputation, keep up the production standards, and design informative and attractive packaging. For subjective norms, producer needs to conceptualize informative and attractive advertising, conducting sales promotion, public relation, personal selling, and direct marketing.

<p class="IndexTerms">Along with the development of the times the need for electrical energy is increasing. PT. PLN (Persero) as a company that supplies electrical energy must be able to meet the needs of electrical energy to run a business to supply electric power in an even amount to meet the needs of the household, industrial, social and business sectors.. The purpose of this research to determine how much the growth of electrical loads in 2020 to 2025 at PT. PLN (Persero) Rayon Juwana. To find out the amount of increase in electrical energy required. Electrical data used data for 8 years, from 2012 to 2019. The results of this study are in the form of an estimate of the use and need for load electrical energy load for the next 5 years, from 2020 to 2025, the data used are the number of subscribers, connected power, and the amount of energy using a simulated neural network with the method (radial basis function). the results of this study an increase per year an average of 1% per year. in 2019 the value is 1.07%, in 2020 it is 1.10%, 2021 is 1.21%, for 2022 it is 1.27%, 2023 is 1.28%, 2024 is 1.17% and 2025 is 1.31 %.</p>

<p><em>Solar power inverter is one of the main components in the PLTS system in order to produce the power or energy needed by the load. Solar power inverter is used to convert from DC energy (Direct Current) to AC (Alternating Current) to load. In this research a simulation of a solar power inverter system on a photovoltaic system will be designed. Simulation is done using SIMULINK-MATLAB software. Solar power inverter is designed using a boost converter as a controller and a Full-Bridge Inverter. Boost Converter is designed from 12VDC - 17 VDC to 300 VDC. Full Bridge Inverter produces AC voltage of 240 VAC with modulation index 0.8 and frequency 60 Hz. Total Harmonic Distortion is 46.07%. Power of Photovoltaic Solar panels generated at 3500 Watts at 1000 Watt / m2 irradiation conditions and temperature temperatures of 25 degrees Celsius.</em></p>

Electric power is one of the main needs of society today, ranging from household consumers to industry. The demand for electricity increases every year. So as to achieve adjustments between power generation and power demand, the electricity provider (PLN) must know the load needs or electricity demand for some time to come. There are many studies on the prediction of electricity loads in electricity, but they are not specific to each consumer sector. One of the predictions of this electrical load can be done using the Radial Basis Function Artificial Neural Network (ANN) method. This method uses training data learning from 2010 - 2017 as a reference data. Calculations with this method are based on empirical experience of electricity provider planning which is relatively difficult to do, especially in terms of corrections that need to be made to changes in load. This study specifically predicts the electricity load in the Semarang Rayon network service area in 2019-2024. The results of this Artificial Neural Network produce projected electricity demand needs in 2019-2024 with an average annual increase of 1.01% and peak load in 2019-2024. The highest peak load in 2024 and the dominating average is the household sector with an increase of 1% per year. The accuracy results of the Radial Basis Function model reached 95%.

<p class="Abstract">Industrial sterilization is a very important problem. Ozone is a powerful oxidizer that can function for sterilization and is environmentally friendly. Plasma DBD (Dielectric Barrier Discharge) is one of the effective technologies to obtain ozone. The ozone generator currently uses a lot of manual control operations. Manual control uses a mechanical system in the form of a potentiometer to calibrate the frequency and output of the ozone generator output, so that digitization and automation are needed to operate to replace human labor. The design of the digital ozone control generator is done using an AVR microcontroller. Programming used in this research is basic language (BASCOM), then uses a DAC (Digital to Analog Converter) system which is the output of a Microcontroller with a Weighted Binnary Resistor. The output of the microcontroller is frequency and 8 bit digital with a decimal parameter of 200. The result of automation is that the timer works for 2 hours. The greater frequency the ozone produced. At a frequency of 1500Hz the power produced is 308.58 watts with an ozone concentration of 59 ppm. Efficiency using a switching system&gt; 90%.</p><p>                                                                                                                                                                                                  </p><p class="IndexTerms"><strong>Keywords</strong>: Plasma, AVR Microcontroller, Ozone.</p>