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All Journal Jurnal Praksis dan Dedikasi Sosial Langit Biru: Jurnal Ilmiah Aviasi
Globalisasi, Safitri Era
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Decision Sciences, Operations Research & Management Education Engineering Environmental Science Social Sciences Transportation Other

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PREDICTION OF SEA LEVEL MEASUREMENT IN PANGPANG BAY FOR SEAPLANE LANDING SEAPLANE LANDING USING ID CONVOLUTIONAL NEURAL NETWORK Setiawan, Ariyono; Islam, Fajar; Efendi, Efendi; Globalisasi, Safitri Era; Hammad, Jehad A. H
Jurnal Praksis dan Dedikasi Sosial (JPDS) Vol 7, No 2 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um032v7i2p176-195

Abstract

This research investigates the relationship between sea level height and various environmental factors in Pangpang Bay, Indonesia, using Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) modeling techniques. Daily data on sea level height, weather, and oceanography were collected from April 1 to April 15, 2024. An analysis was conducted on the factors affecting sea level height and the evaluation of predictive model performance. The findings reveal historical patterns of sea level height changes influenced by the variability of meteorological and oceanographic conditions. Although ANN and CNN models have varying degrees of accuracy, both show potential in predicting sea level height by considering environmental factors. Recommendations include the development of more advanced predictive models, deeper data observation, integration of multidisciplinary information, continuous environmental monitoring, and stakeholder collaboration. This research is expected to contribute to the understanding and management of environmental risks related to sea level height in Pangpang Bay.
Safety Risk Assessment on Aircraft Marshaling Case Study at Indonesian Civil Pilot Academy of Banyuwangi Wicaksono, Agung Wahyu; Patompo, Putri Annatasah; Globalisasi, Safitri Era
Langit Biru: Jurnal Ilmiah Aviasi Vol 18 No 2 (2025): Langit Biru: Jurnal Ilmiah Aviasi
Publisher : Politeknik Penerbangan Indonesia Curug

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54147/langitbiru.v18i2.1264

Abstract

Aviation is subject to risks that emerge from all activities correlated with flight operations. Indonesian Aviation Academy Banyuwangi as an educational institution that participating in such activities, it is susceptible to various risks, ranging from the minor to the major risks. The marshaling activity is one of the crucial flight activities conducted by cadets of the Indonesian Civil Pilot Academy of Banyuwangi. This activity can be hazardous if not conducted properly and in compliance with the procedures. This research aims to determine the risks of marshaling activities at the Indonesian Civil Pilot Academy of Banyuwangi and propose effective mitigation strategies. The qualitative methodology was chosen in this research utilizing three stages of data collection techniques: observation, literature study, and interviews. The research results show that three primary risks occur in marshaling activities at the Indonesian Civil Pilot Academy of Banyuwangi, in particular, not using earplugs, not using safety vests and unclear parking markings. These three risks attributed to a lack of accountability, the absence of standard operating procedures, and insufficient provision of necessary equipment by the organization.
PREDICTION OF SEA LEVEL MEASUREMENT IN PANGPANG BAY FOR SEAPLANE LANDING SEAPLANE LANDING USING ID CONVOLUTIONAL NEURAL NETWORK Setiawan, Ariyono; Islam, Fajar; Efendi, Efendi; Globalisasi, Safitri Era; Hammad, Jehad A.H
Jurnal Praksis dan Dedikasi Sosial Vol. 7 No. 2 (2024)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research investigates the relationship between sea level height and various environmental factors in Pangpang Bay, Indonesia, using Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) modeling techniques. Daily data on sea level height, weather, and oceanography were collected from April 1 to April 15, 2024. An analysis was conducted on the factors affecting sea level height and the evaluation of predictive model performance. The findings reveal historical patterns of sea level height changes influenced by the variability of meteorological and oceanographic conditions. Although ANN and CNN models have varying degrees of accuracy, both show potential in predicting sea level height by considering environmental factors. Recommendations include the development of more advanced predictive models, deeper data observation, integration of multidisciplinary information, continuous environmental monitoring, and stakeholder collaboration. This research is expected to contribute to the understanding and management of environmental risks related to sea level height in Pangpang Bay.
Co-Authors Agung Wahyu Wicaksono Efendi Efendi Fajar Islam Hammad, Jehad A. H Hammad, Jehad A.H Islam, Fajar Patompo, Putri Annatasah Setiawan, Ariyono