This experiment focuses on the analysis of green tea aroma using a set of gas sensors. Specifically, the gas sensors selected for this research are the TGS822, TGS2602, TGS2620, MQ138, MQ5, and MQ3. The experiment involved testing a total of 78 different tea samples (chops), with each sample being observed three times. To conduct the experiment, a tea chamber was utilized, capable of accommodating 125 grams of dry green tea. The tea chamber was connected to a sensor chamber through a hose and intake micro air pump. During data acquisition, air from the tea chamber flowed into the sensor chamber for a duration of 60 seconds. Once the airflow from the tea sample was complete, the gas sensors recorded the aroma data for 60 seconds, resulting in 60 data records. These records were then saved into a CSV file for further processing and labeling. The labeling process involved referencing the Indonesian National Standard (SNI) 3945:2016, which defines the quality parameters for green tea according to ISO 11287 Green tea - definition and basic requirements. The SNI 3945:2016 standard specifies both special requirements and general requirements for green tea quality assessment. Special requirements encompass aspects such as water content, soluble ash, ash alkalinity, crude fiber, polyphenols, metal contamination, and microbial contamination. On the other hand, general requirements cover the physical and organoleptic characteristics of the tea, including dryness, steeping water, and steeping dregs. To evaluate the quality of Gambung green tea, an organoleptic test was conducted by a tea tester. The results of this test were used to label the data set obtained from the e-nose. The data set had two labels: quality standard ("good" and "quality defect") for the discrete classification task, and organoleptic score, which combined ratings for dry appearance, brew color, taste, aroma, and dregs of brewing, for the continuous regression task. In summary, this study aimed to predict the quality standard and organoleptic score of green tea samples using gas sensor data. The gas sensors were selected based on their suitability for analyzing the tea's aroma. The labeled data set, obtained through experimentation and organoleptic testing, would serve as the basis for training models for classification and regression tasks.