Design Development of Detection System and Ro-Ro Ship Notification based on Fuzzy Inference System

mochammad Jafar Tri Febriansyah(1*), Sri Wahjuni(2), Indra Jaya(3),

(1) Institut Pertanian Bogor
(2) Institut Pertanian Bogor
(3) Institut Pertanian Bogor
(*) Corresponding Author
DOI: https://doi.org/10.23917/khif.v9i1.16759

Abstract

Ship stability is very important for the safety of ship motion. There are many factors that affect the stability of a ship. One of the causes of accidents on ships is the problem of ship stability, including the ship cannot be controlled, and loses balance due to improper placement of cargo loads. This study combines gyroscopes, accelerometers, compasses, and GPS sensors, so that more accurate ship tilt information is obtained through an Android smartphone application. This study uses the fuzzy inference system (FIS) method with a trapezoidal membership function where there are 2 inputs and 1 output. Ship tilt input uses 3 linguistic variables very tilted, tilted, and stable. The slope duration input uses 5 very fast, fast, fairly fast, slow, and very slow linguistic variables. Ship status output is divided into 3 linguistic variables safe, alert, and dangerous. Testing and implementation with an input slope of 4.8 and a slope duration of 10 seconds using the Sugeno fuzzy method, the ship's crips value of 0.65 with an alert status was obtained. Calculation of the accuracy of the gyroscope sensor error using the MAPE method, the result is an error percentage of 6.55% (very good). The system accuracy error of 39 trials (36 correct and 3 incorrect) is 92.30% (very good). This research is expected to make it easier for the captain to monitor the stability of the ship and can provide notification of the status of the ship to the captain of the ship if there is a condition of the ship that needs to be watched out for. In addition, the notification will also be received by Port officers on land.

Keywords

Smartphone, FIS, notification system, ship tilt, ship stability

Full Text:

Accepted PDF

References

Indonesia. 1992. Undang-Undang republik Indonesia nomor 21 tahun 1992 tentang pelayaran. Bina Dharma Pemuda.

Pangalila FP. 2010. Stabilitas statis kapal ikan tipe lambut tersanjung yang berpangkalan di pelabuhan perikanan samudera aertembaga kota Bitung Provinsi Sulawesi Utara. Jurnal Perikanan dan Kelautan Tropis. 6(3):149-155.

Paroka D. 2018. Karakteristik geometri dan pengaruhnya terhadap stabilitas kapal ferry ro-ro Indonesia. Kapal. 15(1):1-8.

[BPTD] Balai Pengelola Transportasi Darat. 2018. Satuan pelayanan lembar. Indonesia.

[KNKT] Komite Nasional Keselamatan Transportasi.2018. Data kecelakan kapal di Indonesia pada tahun 2010 – 2016. Indonesia.

Sarena ST, Adhitya RY, Handoko CR, Rinanto N. 2016. Aplikasi sistem peringatan tabrakan pada kapal berbasis data GPS menggunakan logika fuzzy. Jurnal IPTEK. 20(2): 93-104.

Kafila WK, Syauqy D. 2018. Sistem notifikasi kondisi angin menggunakan metode fuzzy untuk keselamatan pelayaran. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer (JPTIIK). 2(5): 2070-2077.

Guevara J, Hirata R, Canu S. 2013. Kernel functions in takagi-sugeno-kang fuzzy system with non singleton fuzzy input. Di dalam: 2013 IEEE International Conference on fuzzy Systems (FUZZ-IEEE). 1-8.

Ariany Z, Hendra A, Febriary S. 2018. Standar Pelayanan Minimal (SPM) dan sistem lasing pada kapal ro-ro untuk keselamatan transportasi penyeberangan laut (Studi kasus Kmp. Legundi). Gema Teknologi. 20(1):26-31.

Algifanri M, Sestri NR. 2018. Sistem pengambilan keputusan dalam penerimaan proyek pembuatan kapal menggunakan metode fuzzy. Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer. 9(2): 723-730

Saelan A. 2009. Logika fuzzy. Program Studi Teknik Informatika, Sekolah Teknik Elektro dan Informatika. Institut teknologi Bandung.

Passarella R, Exaudi K, Fatimah S. 2018. Perancangan sistem navigasi robot kapal katamaran untuk menghindari rintangan menggunakan logika fuzzy. Jurnal Nasional Teknik Elektro. 7(1):53-59.

Harys H, Suprayogi I, Rinaldi R. 2014. Aplikasi logika fuzzy untuk prediksi kejadian hujan (studi kasus: Sub das Siak Hulu). Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains. 1(1):1-14.

Siler W, Buckley JJ. 2005. Fuzzy Expert System and Fuzzy Reasoning. Birmingham (US): Wiley-Interscience.

Nayak GK, Naranayan SJ, Paramasivam I. 2013. Development and Comparative Analysis of fuzzy Inference Systems for Predicting Customer Buying Behavior. International Journal of Engineering and Technology (IJET).5(5):4093-4108.

Takagi T, Sugeno M. 1985. Fuzzy identification of systems and its applications to modeling and control. IEEE transactions on systems, man, and cybernetics. (1):116-132.

Agustin AH, Gandhiadi GK, Oka TB. 2016. Penerapan Metode Fuzzy Sugeno Untuk Menentukan Harga Jual Sepeda Motor Bekas. E-Jurnal Matematika, 5(4), pp.2303-1751.

Farid, Yunus Y. 2017. Analisa Algoritma Haversine Formula Untuk Pencarian Lokasi Terdekat Rumah Sakit Dan Puskesmas Provinsi Gorontalo. ILKOM Jurnal Ilmiah, 9(3), 353-355

Kim, S. and Kim, H., 2016. A new metric of absolute percentage error for intermittent demand forecasts. International Journal of Forecasting.32(3):669-679.

Article Metrics

Abstract view(s): 352 time(s)
Accepted PDF: 368 time(s)

Refbacks

  • There are currently no refbacks.