Email this article 
Hide
Show all
Sistem Pendukung Keputusan Menggunakan Metode FUCOM-MOORA untuk Penentuan Maskapai Favorit
Abstract
Abstrak
Sejak dikeluarkannya berupa serangkaian langkah deregulasi pada tahun 1999, perkembangan industri jasa udara Indonesia semakin berkembang. Namun masih terdapat fakta bahwa banyak maskapai mengalami berbagai kendala sebelum dan selama penerbangan. Pada tahun 2021 saja, terdapat berbagai permasalahan pada pesawat maskapai mulai dari masalah mesin, kendala teknis, kerusakan ban, gangguan cockpit, hingga masalah tekanan udara. Pelanggan maskapai memiliki pertimbangan serta preferensi pribadi untuk memilih maskapai perjalanannya. Banyaknya pilihan maskapai serta banyaknya pertimbangan seringkali membingungkan pelanggan. Untuk menanggulangi hal tersebut, sistem pendukung keputusan (SPK) dapat dipergunakan untuk memberikan rekomendasi dalam memilih maskapai yang sesuai dengan pilihan pelanggan. Penelitian ini telah berhasil mengimplementasikan FUCOM-MOORA dalam penentuan maskapai favorit di Indonesia berdasarkan narasumber yang dilakukan sampling, dengan menggunakan 8 kriteria dan 6 alternatif yang diujikan. Pada perhitungan pembobotan kriteria menggunakan FUCOM menunjukkan bahwa faktor harga (C5) merupakan faktor yang paling diperhitungkan. Perhitungan menggunakan FUCOM-MOORA menunjukkan bahwa Garuda Indonesia menjadi maskapai favorit di Indonesia dengan nilai preferensi sebesar 0,30204, disusul dengan Citilink menjadi maskapai favorit kedua, Batik Air menempati peringkat ketiga. Pengujian menggunakan analisis konsistensi menunjukkan bahwa Garuda Indonesia tetap stabil menjadi pilihan pertama dengan menempati 15 kali peringkat teratas dari 17 pengujian dengan rata-rata sebaran peringkat sebesar 1,23466.
Kata kunci: FUCOM, MOORA, SPK, Maskapai, Indonesia
Abstract
Since the issuance of a series of deregulation steps in 1999, the development of Indonesia's air services industry has continued to develop. However, there is still the fact that many airlines experience various problems before and during the flight. In 2021 alone, there will be various problems with airline aircraft ranging from engine problems, technical problems, tire damage, cockpit problems, to air pressure problems. Airline customers have personal considerations and preferences in choosing their travel carrier. The many choices of airlines and many considerations often confuse customers. To overcome this, a decision support system (DSS) can be used to provide recommendations in selecting airlines that are in accordance with customer preferences. This research has successfully implemented FUCOM-MOORA in determining the favorite airlines in Indonesia based on resource persons who were sampled, using 8 criteria and 6 tested alternatives. In calculating the weighting of the criteria using FUCOM, it shows that the price factor (C5) is the most calculated factor. Calculations using FUCOM-MOORA show that Garuda Indonesia is the favorite airline in Indonesia with a preference value of 0.30204, followed by Citilink being the second favorite airline, Batik Air in third place. Testing using consistency analysis shows that Garuda Indonesia remains stable as the first choice by occupying the top 15 out of 17 tests with an average ranking distribution of 1.23466.
Keywords: FUCOM, MOORA, DSS, Airlines, Indonesia
Full Text:
PDFReferences
T. Santia, “Rentetan Kejadian Pesawat Maskapai Nasional di Awal 2021, Masalah Mesin hingga Pecah Ban,” Liputan 6, Mar. 12, 2021. https://www.liputan6.com/bisnis/read/4504854/rentetan-kejadian-pesawat-maskapai-nasional-di-awal-2021-masalah-mesin-hingga-pecah-ban
W. S. Widodo, “Airbus Umumkan Rugi Rp 18,8 Triliun Gegara Pandemi Corona,” Detik.com, Feb. 23, 2021. https://travel.detik.com/travel-news/d-5401132/airbus-umumkan-rugi-rp-188-triliun-gegara-pandemi-corona
J. Dalle, “Pandemi Corona dan Drama ‘Terra Incognita,’” Detik.com, Nov. 16, 2020. https://news.detik.com/kolom/d-5256888/pandemi-corona-dan-drama-terra-incognita
D. Kuswaraharja, “Cara Dapatkan Rapid Test Antigen Gratis di 5 Maskapai,” Detik.com, Mar. 08, 2021. https://travel.detik.com/travel-news/d-5485219/cara-dapatkan-rapid-test-antigen-gratis-di-5-maskapai
N. Indriyani, E. Ali, U. Rio, and R. Rahmaddeni, “Menentukan Kualitas Pelayanan Maskapai Penerbangan Domestik Dengan Menggunakan Metode Naïve Bayes:,” SATIN, vol. 6, no. 1, pp. 37–44, Jun. 2020, doi: 10.33372/stn.v6i1.605.
S. Seimahuira, “Implementasi Datamining dalam Menentukan Destinasi Unggulan Berdasarkan Online Reviews TripAdvisor Menggunakan Alogoritma K-Means,” Jurnal Technologia, vol. 12, no. 1, pp. 53–58, 2021.
N. K. A. P. Sari, “Implementation of the AHP-SAW Method in the Decision Support System for Selecting the Best Tourism Village,” Jurnal Teknik Informatika C.I.T Medicom, vol. 13, no. 1, pp. 22–31, Mar. 2021.
G. S. Mahendra and P. G. S. C. Nugraha, “Komparasi Metode AHP-SAW dan AHP-WP pada SPK Penentuan E-Commerce Terbaik di Indonesia Comparison of AHP-SAW and AHP-WP Methods on DSS to Determine the Best E-Commerce in Indonesia,” Jurnal Sistem dan Teknologi Informasi (JUSTIN), vol. 08, no. 4, pp. 346–356, 2020, doi: 10.26418/justin.v8i4.42611.
G. S. Mahendra and E. Hartono, “Komparasi Analisis Konsistensi Metode AHP-MAUT dan AHP-PM pada SPK Penempatan Siswa OJT,” Jurnal Teknologi Informasi Informasi dan Komputer, vol. 7, no. 2, 2021.
I. Badi and A. Abdulshahed, “Ranking the Libyan airlines by using Full Consistency Method (FUCOM) and Analytical Hierarchy Process (AHP),” Operational Research in Engineering Sciences: Theory and Applications, vol. 2, no. 1, pp. 1–14, 2019, doi: 10.31181/oresta1901001b.
D. Pamučar, Ž. Stević, and S. Sremac, “A new model for determiningweight coefficients of criteria in MCDM models: Full Consistency Method (FUCOM),” Symmetry, vol. 10, no. 9, pp. 1–22, 2018, doi: 10.3390/sym10090393.
B. Matić et al., “A New Hybrid MCDM Model : Sustainable Supplier Selection in a Construction Company,” Symmetry, vol. 11, no. March, pp. 1–24, 2019, doi: 10.3390/sym11030353.
D. Assrani, N. Huda, R. Sidabutar, I. Saputra, and O. K. Sulaiman, “Penentuan Penerima Bantuan Siswa Miskin Menerapkan Metode Multi Objective Optimization on The Basis of Ratio Analysis (MOORA),” Jurnal Riset Komputer (JURIKOM), vol. 5, no. 1, pp. 1–5, 2018.
A. S. R. A. Binjori, H. R. B. Hutapea, M. Syahrizal, and N. Kurniasih, “Sistem Pendukung Keputusan Penentuan Handphone Bekas Terbaik Menggunakan Metode Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA),” Jurnal Riset Komputer (JURIKOM), vol. 5, no. 1, pp. 61–65, 2018.
W. Brauers, “Location Theory and Multi-Criteria Decision Making : An Application of the MOORA Method,” IDEAS, vol. 12, no. 3, pp. 241–252, 2018, doi: 10.5709/ce.1897-9254.275.
G. S. Mahendra, I. W. W. Karsana, and A. A. I. I. Paramitha, “DSS for best e-commerce selection using AHP-WASPAS and AHP-MOORA methods,” MATRIX, vol. 11, no. 2, pp. 81–94, Jul. 2021, doi: 10.31940/matrix.v11i2.2306.
B. Setiani, “Tanggung Jawab Maskapai Penerbangan Sebagai Penyedia Jasa Penerbangan Kepada Penumpang Akibat Keterlambatan Penerbangan,” JHN, vol. 7, no. 3, Feb. 2016, doi: 10.26555/novelty.v7i3.a3930.
I. Setiawan, D. Nusraningrum, and Y. Pahala, “Deregulasi Penerbangan dan Kinerja Perusahaan Penerbangan Niaga Berjadwal di Indonesia,” Jurnal Manajemen Transportasi dan Logistik, vol. 2, no. 1, p. 1, Jul. 2017, doi: 10.25292/j.mtl.v2i1.130.
D. Pamučar, Ž. Stević, and S. Sremac, “A new model for determiningweight coefficients of criteria in MCDM models: Full Consistency Method (FUCOM),” Symmetry, vol. 10, no. 9, pp. 1–22, 2018, doi: 10.3390/sym10090393.
Ž. Stević and N. Brković, “A Novel Integrated FUCOM-MARCOS Model for Evaluation of Human Resources in a Transport Company,” Symmetry, vol. 4, no. 1, p. 4, 2020, doi: 10.3390/logistics4010004.
Ž. Stević, B. Miĉić, D. Lukić, M. Tomašević, and S. Sremac, “Supplier Selection for Distribution of Finished Products: Combined FUCOM-MABAC Model,” in The Seventh International Confrence Transport and Logistics, 2019, no. December, pp. 35–40.
Y. Sa’adati, S. Fadli, and K. Imtihan, “Analisis Penggunaan Metode AHP dan MOORA untuk Menentukan Guru Berprestasi sebagai Ajang Promosi Jabatan,” Publikasi Jurnal & Penelitian Teknik Informatika, vol. 3, no. 1, pp. 82–90, 2018.
U. K. Mandal and B. Sarkar, “Selection of Best Intelligent Manufacturing System (IMS) Under Fuzzy MOORA Conflicting MCDM Environment,” IJETAE (International Journal of Emerging Technology and Advanced Engineering), vol. 2, no. 9, pp. 301–310, 2012.
I. G. Hendrayana and G. S. Mahendra, “Perancangan Metode AHP-MOORA Pada Sistem Pendukung Keputusan Pemilihan Paket Wisata,” Prosiding Seminar Nasional Pendidikan Teknik Informatika (SENAPATI) Ke-10, vol. 1, no. 1, pp. 143–149, 2019.
R. Wirth and J. Hipp, “CRISP-DM : Towards a Standard Process Model for Data Mining,” Semantic Scholar, vol. 1, no. 24959, pp. 1–11, 2000.
G. S. Mahendra and I. P. Y. Indrawan, “Metode AHP-TOPSIS Pada Sistem Pendukung Keputusan Penentuan Penempatan Atm,” JST (Jurnal Sains dan Teknologi), vol. 9, no. 2, pp. 130–142, 2020, doi: 10.23887/jst-undiksha.v9i2.24592.
E. Exenberger and J. Bucko, “Analysis of Online Consumer Behavior - Design of CRISP-DM Process Model,” AOL, vol. 12, no. 3, pp. 13–22, Sep. 2020, doi: 10.7160/aol.2020.120302.
M. A. Rivai, “Analysis of Corona Virus spread uses the CRISP-DM as a Framework : Predictive Modelling,” International Journal of Advanced Trends in Computer Science and Engineering, vol. 9, no. 3, pp. 2987–2994, 2020, doi: 10.30534/ijatcse/2020/76932020.
DOI: https://doi.org/10.32520/stmsi.v10i3.1386
Article Metrics
Abstract view : 1791 timesPDF - 370 times
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.