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Journal : Unisda Journal of Mathematics and Computer Science (UJMC)

PENERPAN PETRI-NET PADA MODEL GERAKAN BERJALAN TROTTING ROBOT BERKAKI EMPAT (QUADRUPED) Tony Yulianto
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 1 No 01 (2015): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1662.022 KB) | DOI: 10.52166/ujmc.v1i01.440

Abstract

Nowadays many robots has produced not just on a few scale, but also on large for helping human on doing task everyday corresponding the function. By the way, the function can be good functionate if the components, which support to the robot, can be good functionate, too, like the other one is robot walked way movement. Here, we look on four legs of robot walked movement using trotting, because we can find this nowadays and the trouble is kind than robot walked movement with two legs. On this case, we will use max-plus algebra to solve this problem to get robot walked way model on trotting which is like what we want.
IMPLEMENTASI METODE LAGRANGE UNTUK OPTIMASI PENYAKIT KANKER HATI Tony Yulianto; Kuzairi Kuzairi; Riyatun Hasanah
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 2 No 1 (2016): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1070.282 KB) | DOI: 10.52166/ujmc.v2i1.451

Abstract

Modelling the math frequently encountered in everyday life , many things that can be modeled by mathematical modeling , one of which is the modeling of the disease. One of the diseases thoth can be modeled is liver cancer. Liver cancer is very much experienced by people, also cause a variety ranging from the spread of viruses and inveksi . Thus, in the mathematical modeling of the matter is that the modeling using Lagrange method not instant but through a few steps to get the optimal control of this modeling . Thus the optimization of liver cancer can be viewed from the optimal solution by applying the method of Lagrange. From the result of applying the method lagrange can be obtained results when tumor cells T = 0, immune cells I = 0, and addition of condition M = 0, that indicate a person is said to be normal N = 1.
Clustering Daerah Bencana Alam di Indonesia Menggunakan Metode Fuzzy C-Means Yulianto, Tony; Rahmah, Alfiana Faizzatur; Faisol, Faisol; Amalia, Rica
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 9 No 2 (2023): Unisda Journal of Mathematics and Computer science
Publisher : Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v9i2.4776

Abstract

Bencana alam merupakan kejadian luar biasa yang disebabkan oleh faktor alam ataupun faktor dari ulah manusia yang berdampak pada lingkungan dan manusia itu sendiri. Indonesia menjadi salah satu negara yang menjadi rawan bencana alam seperti tanah longsor, banjir, banjir bandang, gempa bumi, tsunami, kekeringan, kebakaran, gunung meletus, puting beliung dan gelombang pasang laut, Sehingga menimbulkan kerusakan lingkungan, kerugian harta benda, dampak psikologis, dan bahkan menimbulkan korban jiwa. Dalam penelitian ini dapat mengcluster bencana alam antara aman, cukup aman, rawan dan sangat rawan, sehingga dalam penyaluran bantuan bisa tepat sasaran. Dalam melakukan pengelompokan disini banyak metode yang bisa digunakan, namun dalam penelitian ini peneliti menggunakan metode Fuzzy C-Means. Dari hasil penelitian tersebut ada 11 provinsi yang masuk pada cluster 1, 4 provinsi yang masuk pada cluster 2, 13 provinsi yang masuk pada cluster 3 dan 6 provinsi yang masuk pada cluster 4. Berdasarkan hasil clustering terdapat beberapa provinsi yang paling rawan bencana adalah provinsi Aceh, Sumatera Utara, Riau, Sumatera Selatan, Lampung, Jawa Barat, Jawa Tengah, Jawa Timur, Nusa Tenggara Timur, Sulawesi Tenggara, Sulawesi Selatan, Papua, dan Papua Barat.
Pengelompokan Jumlah Wisatawan Nusantara Menggunakan Fuzzy Learning Vector Quantization Fauzan, Fauzan; Yulianto, Tony; Faisol, Faisol; Yudistira, Ira; ku, Kuzairi
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 10 No 1 (2024): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v10i1.7277

Abstract

Tourism is a variety of tourist activities and support from facilities and services provided by interested parties, such as the community, entrepreneurs and the goverment. Tourists are people who visit a destination outside of their daily activities within a certain period of time. There are several provinces that are classified as having minimal tourists, so they require government evaluation in providing good services in order to increase tourists in terenst in provinces that are classified as having minimal tourists. Therefore, to group the number of tourists, research will be carried out using a combination of data mining and fuzzy logic, namely the fuzzy learning vector quantization method. The research results obtained: For Euclidean Distance, there are 10 provinces in cluster 1 and there are 24 provinces in cluster 2. For squareeuclidean distance, there are 32 provinces in cluster 1 and there are 2 provinces in cluster 2. For city block distance there is 1 province which is included in cluster 1 and there are 33 provinces which are included in cluster 2. For the Chebychev distance there are 10 provinces which are included in cluster 1 and there are 24 provinces which are included in cluster 2. The final result which was chosen as the best is Euclidean however after checking the validity method it is in the formula squareeuclidean with value of PC= 8.32165E+26, CE=-8.94064E+14, and IFV= -1.4892E+13