Congratulation! Sugiyarto Surono has published his research paper in International Journal of Fuzzy System
Congratulation, Mr Sugiyarto has published her research result on International Journal of Fuzzy System. He is lecturer from Mathematics Department Universitas Ahmad Dahlan. His research was published on November 22, 2020 on International Journal of Fuzzy System (SJR: 0.730, Impact Factor: 4.406) with titled “Optimization of Fuzzy C-Means Clustering Algorithm with Combination of Minkowski and Chebyshev Distance Using Principal Component Analysis”.
In this research, he uses a new method, which combines the Minkowski distance with the Chebyshev distance which is used as a measure of similarity in the clustering process on FCM. FCM is an effective algorithm for grouping data, but it is often trapped in local optimum solutions.
Hopefully, this achievement can trigger the enthusiasm of the other lecturers and through this, they can give a good contribution to many people. All of them are full of blessings and benefits as always. Aamiin ..
Selamat, Bapak Sugiyarto Surono berhasil mempublikasikan hasil risetnya di International Journal of Fuzzy System
Selamat kepada Bapak Sugiyarto yang telah berhasil mempublikasikan hasil risetnya di di International Journal of Fuzzy System. Beliau merupakan dosen dari Program Studi Matematika, Universitas Ahmad Dahlan. Hasil riset beliau dipublikasikan pada 22 Novermber 2020 di International Journal of Fuzzy System (SJR: 0.730, Impact Factor: 4.406) dengan judul “Optimization of Fuzzy C-Means Clustering Algorithm with Combination of Minkowski and Chebyshev Distance Using Principal Component Analysis”.
Pada riset tersebut, beliau menggunakan metode baru, yaitu dengan mengkombinasikan Minkowski distance dengan Chebyshev distance, yang mana digunakan untuk mengukur persamaan dalam proses pengelompokkan FCM. FCM sendiri merupakan alogaritma yang efektif untuk mengelompokkan data.
Harapan nya, prestasi ini dapat memicu semangat para dosen di lingkungan UAD sehingga memberikan kontribusi yang baik untuk banyak orang. Semoga semuanya penuh berkah dan manfaat. Aamiin..
Analysis”.
In this research, he uses a new method, which combines the Minkowski distance with the Chebyshev distance which is used as a measure of similarity in the clustering process on FCM. FCM is an effective algorithm for grouping data, but it is often trapped in local optimum solutions.
Hopefully, this achievement can trigger the enthusiasm of the other lecturers and through this, they can give a good contribution to many people. All of them are full of blessings and benefits as always. Aamiin ..