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All Journal INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Mandala Pengabdian Masyarakat El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Pesona Pariwisata Bhinneka Multidisiplin Journal Journal of Humanities Education Management Accounting and Transportation Journal of Ekonomics, Finance, and Management Studies
Kusuma, Nur Makkie Perdana
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Dampak Penerapan Fuel Surcharge pada Maskapai Wing Air Layanan No Frills terhadap Load Factor Rute Surabaya – Yogyakarta Kinarya, Dani Eka; Kusuma, Nur Makkie Perdana
El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Vol. 5 No. 3 (2024): El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmal.v5i3.620

Abstract

There was an increase in world oil due to geopolitical conflicts, this increase in fuel prices had an impact on the aviation industry, namely an increase in the price of avtur or aircraft fuel. One of them is Wing Airlines with a propeller-engined aircraft, namely ATR-72, expressed a complaint in the conditions experienced to ask for an adjustment in the price of airplane tickets for assistance from the government due to the avtur cost component which eats up operational costs. This study aims to determine the impact factors of the increase in aircraft fuel prices in the application of a new component called Fuel Surcharge. In addition, this study also aims to find solutions to overcome the impact of rising fuel prices by Wing Airlines on the Surabaya - Yogyakarta route. This research is descriptive using qualitative methods with data collection methods in the form of interviews, observation, and documentation. The data obtained is in the form of interviews with Wing Air Airline officers at Juanda International Airport as well as documents used to carry out daily activities. The results of this study indicate that the factors that increase passenger ticket fares in fuel operational costs are due to rising world oil prices, so that government regulations are imposed, namely applying a fuel surcharge component of 25% of the base price rate charged to service passengers. air freight. In the results the data obtained does not show a drastic change in the number of passengers (Load Factor) so that the increase in ticket prices does not have an effect on the number of passengers (Load Factor) to adjust fuel operational costs but additional costs (Fuel Surcharge) have been determined and determined by the government to parties airline to apply to the specified route. Keywords: Avtur increase, Fuel Surcharge, Load Factor
Perbedaan penemuan Foreign Object Debris (FOD) Sebelum dan Selama Haji Tahun 2022 untuk Menunjang Keamanan Penerbangan di Bandar Udara Internasional Adi Soemarmo Boyolali Jawa Tengah Suci, Dinny Purnama; Kusuma, Nur Makkie Perdana
El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Vol. 5 No. 4 (2024): El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmal.v5i4.868

Abstract

Every airport always has Foreign Object Debris (FOD), be it on the apron, runway or taxiway. Adi Soemarmo International Airport is one of the airports that serves regular flights and Hajj flights. Each flight takes off and lands on the runway and parks on the apron. Adi Soemarmo International Airport has routine daily work carried out by the engineering unit and supervised by the Apron Movement Control (AMC) unit, namely sweeping Foreign Object Debris (FOD). This study aims to determine the difference in Foreign Object Debris (FOD) in May (before Hajj) and in June (during Hajj). In addition, this study also aims to obtain the results of differences in the number and type in May-June. This study used a quantitative descriptive method with a documentation study data collection method and secondary data from the number of daily sweeps of Foreign Object Debris (FOD) in May-June 2022, namely before and during Hajj at Adi Soemarmo International Airport. The method used to analyze the data in this study was to use a two-sample t-test in pairs. The results of this study show that there are significant differences in the types of Foreign Object Debris (FOD) and show that there are no significant differences between Foreign Object Debris (FOD) in May and June 2022 with H0 not being accepted because there are no significant results from the two differences with a ratio of 1:1.015 and for the difference from May and June of 15. Keywords: Foreign Object Debris (FOD), Difference, Before and during Hajj.
Comparing Data Mining Classification for Online Fraud Victim Profile in Indonesia Sunardi, Sunardi; Fadlil, Abdul; Kusuma, Nur Makkie Perdana
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 7 No 1 (2023): February 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v7i1.18283

Abstract

Classification is one of the most often employed data mining techniques. It focuses on developing a classification model or function, also known as a classifier, and predicting the class of objects whose class label is unknown. Categorizing applications include pattern recognition, medical diagnosis, identifying weaknesses in organizational systems, and classifying changes in the financial markets. The objectives of this study are to develop a profile of a victim of online fraud and to contrast the approaches frequently used in data mining for classification based on Accuracy, Classification Error, Precision, and Recall. The survey was conducted using Google Forms, which is an online platform. Naive Bayes, Decision Tree, and Random Forest algorithms are popular models for classification in data mining. Based on the sociodemographics of Indonesia's online crime victims, these models are used to classify and predict. The result shows that Naïve Bayes and Decision Tree are slightly superior to the Random Forest Model. Naive Bayes and Decision Tree have an accuracy value of 77.3%, while Random Forest values 76.8%.
Co-Authors Abdul Fadlil Defitasari, Defitasari Frisnawati, Elnia Habibah, Ina Wahyu Eva Kinarya, Dani Eka Pratiwi, Sulfiana Ridho, Nofah Sari, Nanik Rianandita Suci, Dinny Purnama Sunardi Sunardi