This paper aims to tune the Kalman filter (KF) input variables, namely measurement error and process noise, based on two-level factorial design. Kalman filter then was applied in inexpensive temperature-acquisition utilizing MAX6675 and K-type thermocouple with Arduino as its microprocessor. Two levels for each input variable, respectively, 0.1 and 0.9, were selected and applied to four K-type thermocouples mounted on MAX6675. Each sensor with a different combination of input variables was used to measure the temperature of ambient-water, boiling water, and sudden temperature drops in the system. The measurement results which consisted of the original and KF readings were evaluated to determine the optimum combination of input variables. It was found that the optimum combination of input variables was highly dependent on the system's dynamics. For systems with relatively constant dynamics, a large value of measurement error and small value of process noise results in higher precision readings. Nevertheless, for fast dynamic systems, the previous input variables' combination is less optimal because it produced a time-gap, which made the KF reading differ from the original measurement. The selection of the optimum input combination using two-level factorial design eased the KF tuning process, resulting in a more precise yet low-cost sensor.

Temperature is one of the crucial parameters in every aspect of life; therefore, it is essential to be able to measure it accurately. Temperature data acquisition utilizing a K-type thermocouple and MAX6675 module as cold junction compensation is being increasingly used by researchers because of its availability and relative ease of use. Ktype thermocouple and MAX6675 can be used as valid data acquisition if the sensors are properly calibrated. This research proposes a calibration method for K-type thermocouple and MAX6675 sensors based on Arduino microprocessor with DS18B20 thermistor as the reference, which has been previously calibrated with the ASTM-117C thermometer. Calibration was performed at ambient conditions utilizing the energy from the environment where four K-type thermocouple and MAX6675 sensors were calibrated alongside two DS18B20 sensors in ambient water for 24 hours. To increase the accuracy of the K-type thermocouple and MAX6675 sensors, simple mathematical methods were used in Arduino coding, thereby providing automatically calibrated values. After calibration using the proposed method, the sensors then were used in reading temperatures of ambient air and water. The result of this study is simple methods to improve the accuracy of K-type thermocouples and MAX6675 sensors to be used for reading temperature values in different working fluids using Arduino Microprocessor. The error value before calibration was 4.9% compared to 0.42% and 0.61% after calibration in ambient-water and ambient-air respectively.

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