FACTOR ANALYSIS ON WEATHER ELEMENTS THAT AFFECT MARINE TRANSPORTATION ACTIVITIES AT TANJUNG PERAK PORT WITH THE PRINCIPAL COMPONENT ANALYSIS METHOD

Nani Sunarmi, Weika Muchlis Aisyah, Uswatin Hasanah, Ayu Setiorini, Nur Lailatul Fitria, Frisca Karisma Wati

Abstract


This research’s aim is to analyze weather elements that affect marine transportation activities at Tanjung Perak Port. The data used in this study is secondary data obtained from Meteorology, Climatology and Geophysics Agency of the Republic of Indonesia. The data used is weather element record from the meteorological station in Perak II Surabaya for the 2017-2021 period which includes variables of sunlight exposure, precipitation, humidity, wind direction, air pressure, wind speed, and  air temperature. The method used is the Principal Component Analysis method. Based on the test, it is found that all weather variables can be analyzed using the Principal Component Analysis Method. The weather element variables formed 2 components which have Initial Eigenvalues > 1. The first component consists of Air humidity, Precipitation, Sunlight exposure, and Air Pressure. The second component consists of Air Temperature, Wind Direction, and Wind Speed. Based on the two components formed, the first component is the most dominant component element that affects marine transportation activities at Tanjung Perak Port for the 2017-2021 period with Initial Eigenvalues of 3,681. And air pressure is the most dominant weather element with the loading value based on the Principal Component Analysis method is 0,867.


Keywords


Weather Elements; The Principal Component Analysis Method; Marine transportation activities

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References


Saputra AD. Studi Kecelakaan Kapal di Indonesia dari Tahun 2003-2019 Berdasarkan Data Investigasi Komite Nasional Keselamatan Transportasi. War Penelit Perhub. 2021;33(2):87–94.

Hidayat AS, Soemantri AI, Poernomo H. Implementasi Strategi Pengendalian Alur Laut Kepulauan Indonesia ( ALKI ) II Dalam Mendukung Ketahanan Nasional. J Ketahanan Nas. 2019;25(3):313–30.

Kementerian Perhubungan Republik Indonesia. Profil Unit Kerja Kementerian Perhubungan Menteri Perhubungan [Internet]. [dikutip 15 Juni 2022]. Tersedia pada: http://dephub.go.id/ppid/kementerian/58

Sumarsono S, Nurhadi N, Yuana BR. Studi Kecelakaan Kapal Pada Alur Pelayaran Barat Selat Madura, Tanjung Perak, Surabaya. Info Tek [Internet]. 2018;18(2):215–34. Tersedia pada: http://ppjp.unlam.ac.id/journal/index.php/infoteknik/article/view/4348/3858

Tjahyono EB, Umasangaji F, Prakarsa L. Upaya Menghadapi Cuaca Buruk (Typhoon) Guna Mencegah Terjadinya Kecelakaan Pelayaran di Kapal MV. Pan Kristine. In: Prosiding Seminar Pelayaran dan Teknologi Terapan. Jakarta: Pusat Penelitian dan Pengabdian Kepada Masyarakat (P3M) Sekolah Tinggi Ilmu Pelayaran (STIP) Jakarta; 2020: hal. 56–63.

Lutfiana R, Tirono M. Pengenalan Pola Cuaca Maritim (Curah Hujan, Tinggi Gelombang dan Kecepatan Arus) dengan Metode Adaptive Neuro Fuzzy Inference System (ANFIS) pada Jalur Pelayaran Surabaya Makasar. J Neutrino. 2013;6(1):47–52.

Perawiska E, Adriat R. Analisis Unsur Cuaca Pada Saat Kejadian Siklon Tropis Haiyan Menggunakan Model Wrf (Weather Research And Forecasting). Prism Fis. 2018;VI(2):129–36.

Kementerian Perhubungan Republik Indonesia. Pastikan Cuaca Mendukung Untuk Kapal Berlayar Agar Terwujud Keselamatan Dan Keamanan Pelayaran [Internet]. Tersedia pada: https://hubla.dephub.go.id/

Wu SX, Wai HT, Li L, Scaglione A. A Review of Distributed Algorithms for Principal Component Analysis. Proc IEEE. 2018;106(8):1321–40.

Mahmoudi MR, Heydari MH, Qasem SN, Mosavi A, Band SS. Principal component analysis to study the relations between the spread rates of COVID-19 in high risks countries. Alexandria Eng J. 1 Februari 2021;60(1):457–64.

Purnama SA, Rikumahu B. Analisis Faktor Yang Mempengaruhi Harga Saham Menggunakan Metode Principal Component Analysis ( Studi Pada Sub Sektor Perbankan Saham LQ45 Yang Terdaftar Di Bursa Efek Indonesia Periode 2015-2019 ). 2020;7(2):5240–7.

Ayu DC, Rikumahu B, Akuntansi PS, Ekonomi F, Telkom U. Analisis Faktor-Faktor Penentu Financial Distress Dengan Metode Principal Component Analysis (Studi pada Perusahaan Telekomunikasi yang Terdaftar di Bursa Efek Indonesia Periode 2013-2017). 2019;6(3):5663–9.

Saepurohman T, Putro BE. Analisis Principal Component Analysis ( PCA ) Untuk Mereduksi Faktor-Faktor yang Mempengaruhi Kualitas Kulit Kikil Sapi. In: Seminar dan Koferensi Nasional IDEC. Surakarta; 2019: hal. C01.1-C01.10.

Ilmaniati A, Putro BE. Analisis Komponen Utama Faktor-Faktor Pendahulu (Antecedents) Berbagi Pengetahuan Pada Usaha Mikro , Kecil , Dan Menengah ( Umkm ) Di Indonesia. J Teknol. 2019;11(1):67–78.

BMKG RI. Badan Meteorologi, Klimatologi, dan Geofisika (BMKG) Republik Indonesia [Internet]. 2022 [dikutip 2 Juni 2022]. Tersedia pada: https://dataonline.bmkg.go.id/

Delsen MSN Van, Wattimena AZ, Saputri S. Penggunaan Metode Analisis Komponen Utama Untuk Mereduksi Faktor-Faktor Inflasi Di Kota Ambon. Barekeng J Ilmu Mat dan Terap. 2017;11(2):109–18.




DOI: https://doi.org/10.18860/neu.v15i1.17006

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