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Aircraft pollutant emissions are an important part of sources of pollution that directly or indirectly affect human health and ecosystems. This research suggests an Artificial Neural Network model to determine the healthy risk level around Soekarno Hatta International Airport-Cengkareng Indonesia. This ANN modeling is a flexible method, which enables to recognize highly complex non-linear correlations. The network was trained with real measurement data and updated with new measurements, enhancing its quality and making it the ideal method for this research. Measurements of aircraft pollutant emissions are carried out with the aim to be used as input data and to validate the developed model. The obtained results concerned the improved ANN architecture model based on pollutant emissions as input variables. ANN model processes variables-hidden layers-and gives an output variable corresponding to a healthy risk level. This model is characterized by a 4-10-1 scheme. Based on ANN criteria, the best validation performance is achieved at epoch 28 from 34 epochs with the Mean Squared Error (MSE) of 9 × 10 −3. The correlation between targets and outputs is confirmed. It validated a close relationship between targets and outputs. The network output errors value approaches zero. Further research is needed with the aim to enlarge the scheme of the ANN model by increasing its input variables. This is one of the major key defining environmental capacities of an airport that should be applied by Indonesian airport authorities. These would institute policies to manage or reduce pollutant emissions considering population and income growth to be socially positive.

Some of the efforts that can be made to improve aviation security performance are by implementing security screening and airport security programme. The study was conducted at Sentani Airport in 2019 using quantitative methods, with the number of research samples taken in total saturation of 50 personnel at Sentani Airport. Data collected through instruments in the form of statement sheets with ordinal scale models that have been tested, linear regression, partial or simultaneous. The research is using path analysis technique. Based on the results of the study show that security screening has a direct effect on flight aviation security of 2.224 and there is a direct influence of airport security programme on Aviation Security Performance of 4.186 and there is a significant positive effect of security screening on airport security programme is 5.491 and based on the results of the study shows that Security screening indirectly has an effect of 1320,879 on Aviation Security Performance through mediation of Airport Security Programme.

This study aims to determine the effect of ticket price and service quality on customer loyalty through passenger satisfaction as an intervening variable on the Low Cost Carrier (LCC ) of Lion Air airlines. Low Cost Carrier airlines which have relatively cheap ticket price, but due to the economic crisis in Indonesia, these air transportation services are relatively expensive compared to the previous year, which according to the Indonesian National Air Carrier Association, the increase reached almost 40-120% for each airline, because the increase that occurred made LCC airlines, especially Lion Air, experience a very drastic decrease in passengers by 35% in 2019, apart from ticket price increases, the quality of service provided by lion air airlines is also still not good so that passengers are not satisfied with Lion Air airlines. This research was conducted at Soekarno Hatta International Airport. The study was conducted using quantitative methods, with a sample of 100 respondents and data were taken using a questionnaire and processed using smart-PLS 3. The results of this study are from 7 proposed hypotheses, 6 of which are accepted and 1 of the hypothesis is rejected, for the rejected hypothesis is the effect of ticket price on the loyalty of Lion Air airline passengers.