Garuda - Garba Rujukan Digital

Studi Kecepatan Pembakaran Laminar dan Tinggi Api Premix Avgas 100 LL dengan Variasi Ekuivalen Rasio Nasrullah, Muhammad Nur Cahyo Hidayat; Kustanto, Muh Nurkoyim; Darsin, Mahros; Ilminnafik, Nasrul; Syuhri, Skriptyan Noor Hidayatullah
TURBO [Tulisan Riset Berbasis Online] Vol 12, No 2 (2023): TURBO: Jurnal Program Studi Teknik Mesin
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/trb.v12i2.2952

Aviation gasoline atau yang umum disebut dengan avgas merupakan bahan bakar bagi pesawat dengan mesin piston. Pesawat tipe ini pada umumnya banyak digunakan untuk pelatihan terbang hingga untuk penyemprotan tanaman. Banyak peneliti yang telah membahas mengenai bahan bakar ini. Namun, masih belum ditemukan mengenai pengujian kecepatan pembakaran (SL) dan tinggi api laminar premix menggunakan metode bunsen burner. Oleh karena itu penelitian ini membahas mengenai studi kecepatan pembakaran laminar dan tinggi api premix avgas 100 LL dengan memvariasikan ekuivalen rasio dari 0,8; 1,0 dan 1,2. Pada penelitian ini ditemukan bahwa kecepatan pembakaran tertinggi didapatkan pada ekuivalen rasio 1,0 yakni 49,31 cm/detik. Namun pada pengujian tinggi api, ekuivalen rasio 1,0 menghasilkan nilai tingi api terendah yakni 6,303 mm. Hal ini disebabkan karena nilai maksimum kecepatan pembakaran umumnya tercapai pada rasio stoikiometrik, yang menandakan saat bahan bakar dan udara dicampur dalam proporsi yang tepat untuk pembakaran sempurna. Dengan pembakaran campuran bahan bakar-udara yang mendekati stokiometri ini maka menyebabkan nilai tinggi api semakin rendah. Fenomena ini terjadi karena tinggi api terkait erat dengan konsumsi penuh uap bahan bakar, Sehingga, tinggi api mencapai titik akhir ketika semua bahan bakar yang menguap telah terbakar habis.

Unraveling the Research Trends of Artificial Intelligence in Aviation: A Bibliometric Analysis Sulung, Sabam Danny; Nasrullah, Muhammad Nur Cahyo Hidayat; Wibowo, Untung Lestari Nur
Journal of Science Technology (JoSTec) Vol. 5 No. 1 (2023): Journal of Science Technology (JoSTec)
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/jostec.v5i1.696

This study employs bibliometric methods utilizing VOSviewer analysis of Scopus data from 2013 to 2023 to investigate trends in artificial intelligence (AI) research within the aviation industry. The analysis reveals a substantial increase in publication volume over time, peaking at 406 articles in 2022, signifying a heightened interest in AI implementation within the aviation sector. Key publication sources notably include conferences such as AIAA IEEE Digital Avionics Systems Conference Proceedings and ACM International Conference Proceeding Series. Leading contributions in publications emerge from countries such as the United States, China, India, Germany, the United Kingdom, and France, reflecting global involvement in AI research within the aviation industry. Citation analysis identifies highly cited articles addressing topics such as Digital Twin (DT) optimization processes in aviation, AI application in aircraft navigation, and machine learning for weather forecasting. These findings underscore researchers' interest in fundamental topics such as aviation, aircraft-related artificial intelligence, flight delay, and deep learning. Furthermore, co-citation analysis delineates research clusters, illustrating thematic similarities within AI research in the aviation industry. Overall, this bibliometric analysis provides comprehensive insights into the evolution of AI research in the aviation industry, potentially guiding researchers, practitioners, and stakeholders in directing research efforts, formulating policies, and understanding current trends in the application of artificial intelligence within the aviation sector.

Penggunaan Flight Data Logger untuk Menganalisis Dampak Modifikasi Seaplane pada Kinerja Take Off Cessna PK-APH: Studi Komparasi Nasrullah, Muhammad Nur Cahyo Hidayat; Rubiono, Gatut; Sulung, Sabam Danny; Prayitno, Hadi
TEKNIK Vol. 45, No. 1 (2024): May 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/teknik.v45i1.57634

Penelitian ini dilakukan untuk membandingkan take off performance antara pesawat yang telah dimodifikasi menjadi pesawat seaplane (amfibi) dan pesawat Cessna standar sebelum dimodifikasi. Komparasi dilakukan menggunakan data dari flight data recorder Garmin G1000 dengan flight data logger. Data yang dipilih adalah berdasarkan pada satu pesawat yang sama, yakni dengan registrasi PK-APH, namun data difilterisasi dengan berbagai kondisi. Tujuan penelitian ini adalah untuk mengetahui dampak yang ditimbulkan oleh modifikasi seaplane (amfibi) yang telah dilakukan dari segi fase climbing, perbandingan ground roll, maksimal ground speed serta maksimal airspeed. Analisis menunjukkan perbedaan signifikan antara pesawat sebelum dan setelah dimodifikasi menjadi pesawat seaplane. Sebelum modifikasi, pesawat mencapai ketinggian 478,4 kaki diatas permukaan laut dalam 60 detik setelah lepas landas, sedangkan setelah modifikasi hanya mencapai 355,7 kaki di atas permukaan laut. Ground speed pada detik ke-20 juga berbeda, dengan pesawat sebelum modifikasi mencapai 60,69 knots dan pesawat seaplane hanya mencapai 48,65 knots. Perbedaan terlihat pada airspeed awal saat take-off, di mana pesawat sebelum modifikasi memiliki angka 71 knots pada detik ke-24, sedangkan pesawat seaplane memiliki angka 66 knots.

Unraveling the Research Trends of Artificial Intelligence in Aviation: A Bibliometric Analysis Sulung, Sabam Danny; Nasrullah, Muhammad Nur Cahyo Hidayat; Wibowo, Untung Lestari Nur; Lubis, Julianto
Journal of Science Technology (JoSTec) Vol. 5 No. 1 (2023): Journal of Science Technology (JoSTec)
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/jostec.v5i1.696

This study employs bibliometric methods utilizing VOSviewer analysis of Scopus data from 2013 to 2023 to investigate trends in artificial intelligence (AI) research within the aviation industry. The analysis reveals a substantial increase in publication volume over time, peaking at 406 articles in 2022, signifying a heightened interest in AI implementation within the aviation sector. Key publication sources notably include conferences such as AIAA IEEE Digital Avionics Systems Conference Proceedings and ACM International Conference Proceeding Series. Leading contributions in publications emerge from countries such as the United States, China, India, Germany, the United Kingdom, and France, reflecting global involvement in AI research within the aviation industry. Citation analysis identifies highly cited articles addressing topics such as Digital Twin (DT) optimization processes in aviation, AI application in aircraft navigation, and machine learning for weather forecasting. These findings underscore researchers' interest in fundamental topics such as aviation, aircraft-related artificial intelligence, flight delay, and deep learning. Furthermore, co-citation analysis delineates research clusters, illustrating thematic similarities within AI research in the aviation industry. Overall, this bibliometric analysis provides comprehensive insights into the evolution of AI research in the aviation industry, potentially guiding researchers, practitioners, and stakeholders in directing research efforts, formulating policies, and understanding current trends in the application of artificial intelligence within the aviation sector.

Integrated and Sustainable Transit Development: A Case Study of Terminal Isimu and Djalaluddin Airport in Gorontalo Province Rahmawati, Aisyah; Nasrullah, Muhammad Nur Cahyo Hidayat; Mintje, Quirina Ariantji Patrisia
Logistica : Journal of Logistic and Transportation Vol. 3 No. 2 (2025): April 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/logistica.v3i2.698

This study examines the integration potential between Terminal Isimu and Djalaluddin Airport in Gorontalo Province, Indonesia, using the Green Transport Sustainability Model (GTSM). The research evaluates existing conditions of intermodal connectivity, identifies key barriers, and develops alternative development scenarios. A qualitative descriptive approach was applied, relying on secondary institutional data and GTSM indicators such as connectivity, modal share, emissions, and stakeholder alignment. The findings indicate that Terminal Isimu currently operates as an informal hub, while Djalaluddin Airport serves growing passenger and cargo traffic with limited coordination. Three scenarios are outlined, ranging from basic shuttle linkage to a full Transit Oriented Development (TOD) with electric vehicles and intelligent transport systems. The study contributes by contextualizing GTSM in a secondary city setting and highlighting practical pathways for phased integration. However, the exclusive use of secondary data and the absence of field validation limit the scope of findings. Future research should incorporate surveys or stakeholder engagement to strengthen empirical evidence and ensure policy relevance. The study concludes that Gorontalo holds significant promise as a model for sustainable transit integration in Indonesia's secondary urban areas. Through strategic investments and stakeholder collaboration, the region can enhance accessibility, reduce emissions, and support inclusive economic growth.

Human Capital Optimization in Logistics: A Quantitative Analysis of Motivational and Environmental Determinants of Performance Herdian, Rofik Sandra; Budiyanto, Albert; Nasrullah, Muhammad Nur Cahyo Hidayat; Hariri, Ahmad; Marini
Logistica : Journal of Logistic and Transportation Vol. 2 No. 1 (2024): January 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/logistica.v2i1.737

This study investigates the influence of work motivation and work environment on employee performance within PT Aerojasa Cargo's warehouse division. Recognizing the strategic importance of human capital in logistics, the research aims to evaluate how these two variables interact to affect operational outcomes.Using a quantitative methodology, the study surveyed 55 employees selected through Slovin’s formula. A structured Likert-scale questionnaire measured three core constructs: motivation, work environment, and performance. Data were analyzed using SPSS 26.0, employing descriptive statistics, multiple regression analysis, and validation metrics such as Cronbach’s alpha and R². Key results show that both motivation and work environment significantly impact employee performance (p < 0.05), with a combined explanatory power of 83.3% (R² = 0.833). The work environment demonstrated a slightly higher beta coefficient (β = 0.417) than motivation (β = 0.286), suggesting that physical and social workplace conditions are marginally more influential. Descriptive findings also revealed demographic patterns relevant to performance, including age distribution, education level, and gender roles. These findings align with existing literature and underscore the synergistic importance of fostering motivation and creating supportive work environments. The study concludes that HR managers in logistics should implement dual-focused strategies to enhance both motivational drivers and workplace quality. Such strategies may include high-performance work systems, ergonomic improvements, and continuous feedback mechanisms. This research contributes to the field of organizational behavior by offering empirical support for integrated HRM approaches in logistics, providing a framework for future policy and academic inquiry.

Title

Found 6 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 6 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 6 Documents
Search