Pengembangan Sistem Pendukung Keputusan Menggunakan Metode Tsukamoto

• Graha Prakarsa Universitas Informatika dan Bisnis Indonesia
• Vani Maharani Nasution Universitas Informatika dan Bisnis Indonesia
Keywords: Fuzzy, Tsukamoto, Hanger, Maintenance, System.

Abstract

Hanger maintenance process this time based on the circulation from hanger give to the production side. No standard calculation, looking for risk percentage for hanger go into maintenance, become a problem. The hanger must have a standard calculation for percentage value, where the value can provide a clear decision. There is a method in Fuzzy Logic, that the Tsukamoto method, can be utilized in making a decision. This research is based on the problem of how to make a standard calculation, to looking for the risk percentage level for hanger go into maintenance, by applying Fuzzy Logic Tsukamoto method, so that the calculation becomes faster, accurate, and precise. The result from the application of the Tsukamoto method, to find the risk percentage level for hanger enter maintenance, for example at hanger Back Caesar, the resulting level of percentage hanger requirement is 91%, and hanger maintenance risk level 70,375%. The final result shows hanger Back Caesar has a high maintenance risk level (range between 54,6-100%) and well plan maintenance action. Application of Tsukamoto method that has been done shows that to find the risk level percentage for hanger go into maintenance, the first must be looking for output crisp from the percentage level of hanger that needed with the Tsukamoto method.

References

Rusli, M., 2017. Dasar Perancangan Kendali Logika Fuzzy. Ke1 ed. Malang: UB Press.

Rohayani, H., 2015. Fuzzy Inference System Dengan Metode Tsukamoto Sebagai Penunjang Keputusan Produksi. Jurnal Sistem Informasi, 7(1), pp. 753-764.

Sari, N. R. & Mahmudy, W. F., 2015. Fuzzy Inference System Tsukamoto Untuk Menentukan Kelayakan Calon Pegawai. Seminar Nasional Sistem Informasi Indonesia, 2-3 November.pp. 245-252.

Hadi, H. N. & Mahmudy, W. F., 2015. Penilaian Prestasi Kinerja Pegawai Menggunakan Fuzzy Tsukamoto. Jurnal Teknologi Informasi dan Ilmu Komputer, 1(2), pp. 41-48.

Permatasari, H. S., Kridalaksana, A. H. & Suryatno, A., 2015. Sistem Pendukung Keputusan Pemilihan Program Studi di Universitas Mulawarman Menggunakan Metode Tsukamoto. Jurnal Informatika Mulawarna, 1(10), pp. 32-37.

Caraka, A. A., Haryanto, H., Kusumaningrum, D. P. & Astuti, S., 2015. Logika Fuzzy Menggunakan Metode Tsukamoto Untuk Prediksi Perilaku Konsumen di Toko Bangunan. Techno.COM, 14(4), pp. 255-265.

Murti, T., Abdillah, L. A. & Sobri, M., 2015. Sistem Penunjang Keputusan Kelayakan Pemberian Pinjaman dengan Metode Fuzzy Tsukamoto. Seminar Nasional Inovasi dan Tren (SNIT), pp. 252-256.

Ayuningtias, L. P., Irfan, M. & Jumadi, 2017. Analisa Perbandingan Logic Fuzzy Metode Tsukamoto, Sugeno, dan Mamdani (Studi Kasus: Prediksi Jumlah Pendaftar Mahasiswa Baru Fakultas Sains Dan Teknologi Universitas Islam Negeri Sunan Gunung Djati Bandung). Jurnal Teknik Informatika, 10(1), pp. 9-16.

Putra, O. E. & Febrianti, E. L., 2016. Analisa Jumlah Produksi Pada Industri Rumah Tangga Dengan Menggunakan Logika Fuzzy. Journal Of Sainstek, 8(2), pp. 173-179.

Rohayani, H., 2015. Fuzzy Inference System Dengan Metode Tsukamoto Sebagai Penunjang Keputusan. Jurnal Sistem Informasi (JSI), 7(1), pp. 753-764.

Sukmarani, N. P. Y., 2016. Penerapan Metode Exponential Smoothing Pada Peramalan Penjualan Dalam Penentuan Kuantitas Produksi Roti (Studi Kasus Perusahaan Roti Dhiba Kendari), Kendari: Fakultas Teknik Universitas Halu OLeo.

Triwahyuni, A. & Saputra, N., 2015. Architecture E-Mall Using RUP (Rational Unifed Process) Methods. Cogito Smart Journal, 1(1), pp. 1-12.

Published
2019-12-09
How to Cite
Graha Prakarsa, & Nasution, V. M. (2019). Pengembangan Sistem Pendukung Keputusan Menggunakan Metode Tsukamoto. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 3(3), 414 - 421. https://doi.org/10.29207/resti.v3i3.1224
Section
Information Technology Articles