scholarly journals Pertanggungjawaban Pidana Terhadap Pencurian Barang Penumpang Pesawat Studi Dibandara Udara Kualanamu Internasional Airport

2021 ◽  
Vol 20 (1) ◽  
pp. 118-126
Author(s):  
Anjani Sipahutar
Keyword(s):  
Air Transportation ◽  
Weather Factors ◽  
Flight Delays ◽  
Internal Factors ◽  
International Airport ◽  
Flight Delay ◽  
Transportation Company

This study aims to determine that there are still many events that are still require the liability from the commercial air transportation company, both from the carrier company and those who are related to the carrier, such as flight delays (flight delay) either caused by weather factors or internal factors from the carrier company, the occurrence of negligence from the transport officer which causes the loss of goods owned by passengers, or because of there is an event for which the reason is unknown so that the aircraft experiences interference during the flight, from the results of this research it can be seen that the carrier operating the aircraft is obliged to be responsible for losses against:a. passengers who died, disability or injury;b. lost or damaged of the cabin baggage;c. lost, destroyed, or damaged of the checked baggage;d. lost, destroyed, or damaged of the cargo;e. delay in air transportation; andf. losses suffered by third partiesas well as who are the parties involved, the requirements that must be fulfilled and how the rights and the obligations of the parties are fulfilled, as well as other provisions in its implementation if a passenger's goods are lost or damaged and provide a description of its protection.Keywords : Liability, Theft of Goods, Aircraft Passengers, Kualanamu International Airport.

KOMPENSASI SEBAGAI BENTUK TANGGUNG JAWAB PIHAK MASKAPAI PENERBANGAN DALAM KETERLAMBATAN JADWAL PENERBANGAN KOMERSIAL DI INDONESIA

2019 ◽  
Vol 7 (1) ◽  
pp. 124
Author(s):  
Asmarsha Qathrinada , ◽  
Pranoto ,
Keyword(s):  
Deductive Reasoning ◽  
Legal Protection ◽  
Air Transportation ◽  
Air Transport ◽  
Flight Delays ◽  
Reasoning Patterns ◽  
The Government ◽  
Flight Delay ◽  
Secondary Materials

<p>Abstract<br />This article aims to find out how legal protection is provided to passengers in commercial air transport <br />activities in Indonesia, especially regarding airline responsibilities to passengers and the compensation <br />provided in case of flight delays due to negligence of the carrier. This research is performed with legal <br />research, using prescriptive characteristic. The research is using statute approach by reviewing the <br />regulations related to the issues. The source of the research is derived from primary legal materials namely <br />legislation, secondary materials from legal literatures, as well as tertiary or non-legal legal material. The <br />collection of legal materials was done by literature studies, and analyzed with deductive reasoning patterns. <br />Based on the result of the research, it can be concluded that the regulation of compensations given by <br />the airlines to passengers has been quite well regulated in the Minister of Transportation Regulation <br />No. 89 of 2015, but in the implementation, the government is still less firm in cracking down on airlines <br />that do not carry out their responsibility of the compensation regulated in Regulation of the Minister of <br />Transportation Number 77 in year 2011.<br />Keywords: compensation; flight delay; commercial air transportation.</p><p>Abstrak<br />Artikel ini bertujuan mengetahui bagaimana perlindungan hukum yang diberikan kepada penumpang <br />dalam kegiatan angkutan udara komersial di Indonesia, khususnya mengenai tanggung jawab maskapai <br />penerbangan terhadap penumpang serta apa kompensasi yang diberikan apabila terjadi penundaan <br />penerbangan karena kelalaian pihak pengangkut. Penelitian ini dilakukan dengan penelitian hukum dan <br />bersifat preskriptif. Pendekatan penelitian berupa pendekatan undang-undang dengan menelaah regulasi <br />yang besangkutan dengan isu yang penulis angkat dalam penulisan ini. Sumber penelitian berasal dari <br />bahan hukum primer yaitu perundang-undangan, bahan sekunder dari kepustakaan hukum, serta bahan <br />hukum tersier atau non-hukum. Pengumpulan bahan hukum dilakukan dengan studi kepustakaan, dan <br />menganalisis dengan pola penalaran deduktif.  Berdasarkan hasil penelitian maka dapat disimpulkan <br />bahwa  pengaturan  mengenai  kompensasi  yang  diberikan  oleh  maskapai  penerbangan  terhadap <br />penumpang  telah cukup  baik  diatur dalam Peraturan Menteri Perhubungan Nomor 89 Tahun 2015, <br />namun dalam pelaksanaannya pemerintah masih kurang tegas dalam menindak maskapai yang tidak <br />melaksanakan tanggung jawabnya untuk memberikan kompensasi sesuai dengan Peraturan Menteri <br />Perhubungan Nomor 77 Tahun 2011.<br />Kata kunci: kompensasi; keterlambatan penerbangan; pengangkutan udara komersial.</p>

scholarly journals Weather Analysis of Flight Delay at Husein Sastranegara Airport

2019 ◽  
Vol 4 (2) ◽  
pp. 89-98
Author(s):  
Yedi Dermadi ◽  
Shinta Devi Lukitasari ◽  
Annisaa Nurhayati
Keyword(s):  
Weather Conditions ◽  
Air Transportation ◽  
Weather Data ◽  
Flight Delays ◽  
Weather Forecasts ◽  
Weather Information ◽  
Directorate General ◽  
Flight Delay ◽  
Flight Cancellations ◽  
Bad Weather

Flight is an activity that is very vulnerable to weather conditions. The accuracy of weather information strongly supports flight activities. The effects of bad weather on flights include flight delays and flight cancellations. Based on data on flight delays from the Directorate General of Air Transportation of the Ministry of Transportation from January to March 2019 at Husein Sastranegara Airport, it is known that 20-30% of flight delays are caused by weather constraints. To estimate flight delays based on weather forecasts, weather data analysis is carried out to determine the type of weather that is endangering flights and causing flight delays. The analysis was carried out using the K-NN and Random Forest algorithms

scholarly journals Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 152
Author(s):  
Micha Zoutendijk ◽  
Mihaela Mitici
Keyword(s):  
Assignment Problem ◽  
Absolute Error ◽  
Aviation Industry ◽  
Probabilistic Forecasting ◽  
Flight Delays ◽  
Mixture Density ◽  
Assignment Model ◽  
Gate Assignment ◽  
Flight Delay ◽  
Delay Prediction

The problem of flight delay prediction is approached most often by predicting a delay class or value. However, the aviation industry can benefit greatly from probabilistic delay predictions on an individual flight basis, as these give insight into the uncertainty of the delay predictions. Therefore, in this study, two probabilistic forecasting algorithms, Mixture Density Networks and Random Forest regression, are applied to predict flight delays at a European airport. The algorithms estimate well the distribution of arrival and departure flight delays with a Mean Absolute Error of less than 15 min. To illustrate the utility of the estimated delay distributions, we integrate these probabilistic predictions into a probabilistic flight-to-gate assignment problem. The objective of this problem is to increase the robustness of flight-to-gate assignments. Considering probabilistic delay predictions, our proposed flight-to-gate assignment model reduces the number of conflicted aircraft by up to 74% when compared to a deterministic flight-to-gate assignment model. In general, the results illustrate the utility of considering probabilistic forecasting for robust airport operations’ optimization.

Ultrafine particles in the cabin of a waiting commercial airliner at Tianjin International Airport, China

2017 ◽  
Vol 27 (9) ◽  
pp. 1247-1258 ◽  
Author(s):  
Jianlin Ren ◽  
Junjie Liu ◽  
Xiaodong Cao ◽  
Fei Li ◽  
Jianmin Li
Keyword(s):  
Particle Size ◽  
Ultrafine Particles ◽  
Size Range ◽  
Environmental Control ◽  
Particle Dynamic ◽  
Ground Vehicles ◽  
Flight Delays ◽  
Penetration Factor ◽  
International Airport ◽  
Outdoor Concentration

Passengers and crew on board of commercial airliners often spend extra time in the cabin waiting for departure due to flight delays. During the waiting period, a large amount of ambient ultrafine particles (UFPs) may penetrate into the aircraft cabin through the environmental control system (ECS) and ground air-conditioning cart (GAC). However, limited data are available for human exposure, in waiting commercial airliners, to freshly emitted UFPs from the exhaust of ground vehicles and airliners. To address this issue, we measured the ambient and in-cabin particle number concentrations and particle size distributions (PSDs) simultaneously in an MD-82 airliner parked at Tianjin International Airport, China. When air was supplied to the cabin by GAC, particle counts variation outdoors caused in-cabin variation with a 1–2 min delay. The in-cabin and ambient PSDs ranged from 15 to 600 nm were bimodal, with peaks at 30–40 and 70–90 nm. The GAC and ECS removed 1–73% particles in the size range of 15–100 nm and 30–47% in the size range of 100–600 nm. The relationship between the penetration factor and particle size was an inverted U-curve. An improved particle dynamic model from this study was used to calculate the time-dependent in-cabin UFPs concentrations with dramatic changes in outdoor concentration.

scholarly journals Flight delay performance at Hartsfield-Jackson Atlanta International Airport

2014 ◽  
Vol 4 (1) ◽  
Author(s):  
Grigoriy Yablonsky ◽  
Richard Steckel ◽  
Denis Constales ◽  
John Farnan ◽  
Damon Lercel ◽  
...  
Keyword(s):  
Delay Performance ◽  
International Airport ◽  
Flight Delay

Assessing the effects of flight delays, distance, number of passengers and seasonality on revenue

Kybernetes ◽  
2019 ◽  
Vol 48 (9) ◽  
pp. 2138-2149
Author(s):  
Murat Guven ◽  
Eyup Calik ◽  
Basak Cetinguc ◽  
Bulent Guloglu ◽  
Fethi Calisir
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Future Research ◽  
Negative Effects ◽  
Flight Delays ◽  
Content Type ◽  
Positive Effects ◽  
Common Correlated Effects ◽  
Flight Delay ◽  
Airline Company

Purpose This study aims to investigate the effects of flight delays, distance, number of passengers and seasonality on revenue in the Turkish air transport industry. Design/methodology/approach The domestic return routes of a Turkish airline company were examined to address this issue. Among five cities and six airports, 14 major domestic return routes were selected. The augmented mean group (AMG) estimator and common correlated effects mean group (CCEMG) estimator were conducted with a two-way fixed effects (FE) robustness test in this study. Findings The results show that arrival flight delay and departure flight delay had negative effects on revenue, whereas the distance between airports, the number of air passengers and seasonality had positive effects on revenue. Research limitations/implications The data used in this study were retrieved from a Turkish airline company; for future research, other airline companies operating in Turkey may be included. Practical implications These findings could be evaluated by air transportation leaders to provide a guide to make strategic decisions to achieve greater performance in this competitive environment. Originality/value The originality of the paper comes from the facts that besides distance and number of passengers, the authors control for the seasonality when assessing the effects of flight delay on revenue; they use panel data techniques, which permit them to control for individual heterogeneity, and create more variability, more efficiency and less collinearity among the variables; they use two recent panel data techniques, CCEMG and AMG, allowing for cross-section dependence.

scholarly journals Amsterdam to Dublin Eventually Delayed? LSTM and Transfer Learning for Predicting Delays of Low Cost Airlines

2019 ◽  
Vol 33 ◽  
pp. 9541-9546
Author(s):  
Nicholas McCarthy ◽  
Mohammad Karzand ◽  
Freddy Lecue
Keyword(s):  
Transfer Learning ◽  
Short Term Memory ◽  
Low Cost ◽  
Learning Approaches ◽  
Flight Delays ◽  
Commercial Aviation ◽  
Feature Spaces ◽  
Flight Delay ◽  
Delay Prediction ◽  
Heterogeneous Feature

Flight delays impact airlines, airports and passengers. Delay prediction is crucial during the decision-making process for all players in commercial aviation, and in particular for airlines to meet their on-time performance objectives. Although many machine learning approaches have been experimented with, they fail in (i) predicting delays in minutes with low errors (less than 15 minutes), (ii) being applied to small carriers i.e., low cost companies characterized by a small amount of data. This work presents a Long Short-Term Memory (LSTM) approach to predicting flight delay, modeled as a sequence of flights across multiple airports for a particular aircraft throughout the day. We then suggest a transfer learning approach between heterogeneous feature spaces to train a prediction model for a given smaller airline using the data from another larger airline. Our approach is demonstrated to be robust and accurate for low cost airlines in Europe.

scholarly journals Flight Delay Prediction Using Machine Learning

2021 ◽  
pp. 473-476
Author(s):  
Prajwal Dhone ◽  
Uday Kirange ◽  
Rushabh Satarkar ◽  
Prof. Shashant Jaykar
Keyword(s):  
Machine Learning ◽  
Negative Impact ◽  
Weather Conditions ◽  
Current Data ◽  
Environmental Harm ◽  
Flight Delays ◽  
Adverse Weather Conditions ◽  
Adverse Weather ◽  
Flight Delay ◽  
Delay Prediction

In this fast growing world as airplanes continue flying, flight delays are the part of the experience. According to the Bureau Of Statistics(BOS), about 20% of all flights are delayed by 15 minutes or more. Flight delays causes a negative impact, mainly economical for airport authorities, commuters and airline industries as well. Furthermore, in the domain of sustainability, it can even cause environmental harm by the rise in fuel consumption and gas emissions and also some of the important factors including adverse weather conditions, preparing the aircraft, fixing of mechanical issue, getting security clearance, etc. Hence, these are the factors which indicates the necessity it has become to predict the delays of airline problems. To carry out the predictive analysis, which includes a range of statistical techniques from machine learning, this studies historical and current data to make predictions about the future delays, taking help of Regression Analysis using regularization technique used in Python.

scholarly journals TANGGUNG JAWAB PERUSAHAAN ANGKUTAN UDARA TERHADAP KETERLAMBATAN PENERBANGAN (STUDI PADA PT. LION MENTARI AIRLINES)

2020 ◽  
Vol 8 (10) ◽  
pp. 1540
Author(s):  
Desak Putu Dian Sucitawati ◽  
Ida Bagus Putra Atmadja
Keyword(s):  
Research Method ◽  
Air Transport ◽  
Flight Delays ◽  
Descriptive Research ◽  
Legal Relationship ◽  
Qualitative Descriptive ◽  
Aviation Transportation ◽  
Transportation Company

Tujuan dari penulisan artikel dalam jurnal ini untuk mengkaji mengenai hubungan hukum antara perusahaan penerbangan dengan penumpang, serta untuk mengetahui tanggungjawab perusahaan penerbangan terhadap penumpang apabila terjadi penundaan penerbangan. Tulisan ini menggunakan metode penelitian yuridis empiris dengan dengan sifat penelitian deskriptif kualitatif. Hasil studi menunjukkan bahwa hubungan hukum antara Perusahaan Angkutan Penerbangan dengan penumpang adalah hubungan hukum yang sifatnya perjanjian berkala yaitu perjanjian dengan syarat dilakukan hanya untuk waktu tertentu dan perbuatan tertentu. Sesuai dengan Peraturan Menteri Nomor 77 tahun 2011 tentang Tanggung Jawab Pengangkut Angkutan Udara di Pasal 10, yaitu keterlambatan lebih dari 4 (empat) jam akan mengakibatkan pembayaran kompensasi sebesarRp.300.000,00 (tiga ratus ribu Rupiah) untuk masing-masing penumpang. The purpose of articles in this journal is to examine the legal relationship between airline companies and passengers, as well as to find out the responsibility of airlines to passengers in the event of flight delays. This paper uses an empirical juridical research method with qualitative descriptive research characteristics. The results of the study show that the legal relationship between the Aviation Transportation Company and passengers is a legal relationship which is a periodic agreement, namely an agreement with the condition that it is carried out only for a certain time and for certain actions. In accordance with Ministerial Regulation Number 77 of 2011 concerning the Responsibility of Air Transport Carriers in Article 10, namely a delay of more than 4 (four) hours will result in the payment of compensation of Rp. 300,000.00 (three hundred thousand Rupiah) for each passenger.

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