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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Math Educa Journal Jurnal Saintika Unpam : Jurnal Sains dan Matematika Unpam Mandalika Mathematics and Educations Journal Limits: Journal of Mathematics and Its Applications
Syafrizal Sy
Universitas Andalas
Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Physics

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BILANGAN RAMSEY MULTIPARTIT UKURAN UNTUK GRAF POHON DAN GRAF LINTASAN Yerti Syahraini Putri; Effendi Effendi; Syafrizal Sy
JURNAL SAINTIKA UNPAM Vol 3, No 2 (2021)
Publisher : Program Studi Matematika FMIPA Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jsmu.v3i2.6675

Abstract

Misalkan j,l,n,s dan t adalah bilangan-bilangan asli dengan n,s≥2 dan j,l,t≥1 maka bilangan Ramsey multipartit ukuran m_j (K_(n×l),K_(s×t) )  adalah bilangan asli terkecil ξ sedemikian sehingga sebarang pewarnaan dari semua sisi K_(j×ξ)  menggunakan dua warna merah dan biru, akan selalu berlaku bahwa K_(j×ξ) memuat K_(n×l)  merah atau K_(s×t) biru sebagai subgraf. Untuk sebarang graf G dan H, j≥2 adalah bilangan bulat, bilangan Ramsey multipartit ukuran m_j (G,H)  adalah bilangan asli terkecil ξ sedemikian sehingga setiap faktorisasi dari graf K_(j×ξ)≔F_1⊕F_2 memenuhi kondisi berikut:  F_1 memuat subgraf G atau F_2 memuat subgraf H. Dalam makalah ini, akan ditentukan nilai-nilai dari bilangan Ramsey multipartit ukuran m_j (T_n,P_3 )  untuk j≥3. Hasil pada penelitian ini menunjukkan bahwa bilangan Ramsey multipartit ukuran untuk graf pohon dan graf lintasan, untuk sebarang bilangan bulat positif n dan j≥3, yaitu m_3 (T_n,P_3 )=⌈n/3⌉, m_4 (T_n,P_3 )=⌈n/4⌉, dan m_3 (T_j,P_3 )=⌈n/j⌉.
Bilangan Kromatik Lokasi Graf Tentakel Azizah Riana Putri; Syafrizal Sy; Monika Rianti Helmi
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 2 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i2.3462

Abstract

The locating-chromatic number of a graph was introduced by Chartrand et al. in 2002, which is a combined concept between the vertex coloring and partition dimension of a graph. The locating-chromatic number of a graph is a grouping of vertices on a graph based on color, which is called a color class, provided that each vertex on the graph has a different color code. Determining the locating-chromatic number of a graph is done by constructing the lower and upper bound of the locating-chromatic number of the graph. In this paper, we determine the locating-chromatic number of the tentacle graph, which is denoted by T_(k,m,n). Tentacle Graph is a graph constructed from a triangular book graph Bt_n whose common edge is amalgamated with C_k. Then two vertices in C_k that are adjacent to the vertex associated with the terminal edge are amalgamated with the star graphs S_(n_1) and S_(n_2). By determining the lower and upper bounds of the location chromatic number, it is obtained that the location chromatic number of Tentacle Graph is 4, m=1,n=2, n+1, for m>=1, n>= m + 2, and m + 2, for m > 1, n < m + 2.
RAINBOW CONNECTION NUMBERS IN GRAPHS: A COMPREHENSIVE STUDY Gema Hista Medika; Syafrizal Sy; Muhafzan Muhafzan; Zulfaneti Zulfaneti
Math Educa Journal Vol 10, No 1 (2026)
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/mej.v10i1.13681

Abstract

The rainbow connection number is a graph parameter that integrates edge colouring and graph connectivity. A connected graph is said to be rainbow connected if every pair of vertices is joined by a path whose edges have distinct colours, and the rainbow connection number represents the minimum number of colours required to satisfy this property. This study aims to provide a comprehensive and systematic analysis of research developments related to rainbow connection numbers in graphs. The method employed is a systematic literature review of reputable international journals and nationally accredited publications. The analysis covers fundamental definitions, known values for various classes of graphs, relationships with structural parameters such as diameter, minimum degree, and connectivity, as well as computational complexity and several important variants, including strong rainbow connection, rainbow vertex-connection, and total rainbow connection. The results indicate that the rainbow connection number is strongly influenced by graph structure, with diameter serving as a natural lower bound and connectivity contributing to tighter upper bounds. Furthermore, determining the exact value for general graphs is computationally intractable, motivating the use of approximation and heuristic approaches. This study also identifies research gaps, particularly in algorithmic development and the analysis of complex graph class, and highlights potential applications in communication networks and network security.
Eksistensi dan Keunikan dalam Pengendalian LQ Berhorison Tak Terbatas Melalui Analisis Riccati Berbasis Sontag Budi Rudianto; Muhafzan Muhafzan; Mahdhivan Syafwan; Syafrizal Sy
Mandalika Mathematics and Educations Journal Vol 8 No 1 (2026): Edisi Maret
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v8i1.10782

Abstract

This paper examines the existence and uniqueness of solutions to Linear Quadratic (LQ) optimal control problems with infinite time horizons in time-varying dynamic systems. By extending Sontag's Theorem to semi-infinite intervals, the properties of The Riccati Differential Equation’s solutions are analyzed under assumptions of essential boundedness and boundedness of the system matrix and cost weights. It is proven that the Riccati matrix solution P(t) exists globally, remains positive definite, and converges to the steady-state limit P∞. The uniqueness of the optimal control–state pair (x,u) is obtained through P(t)-based co-state analysis. Simulations on satellite attitude control systems demonstrate convergence and robustness towards periodic disturbances, supporting applications in adaptive control, robust estimation, and time-varying filtering.
Impact of Speckle Reduction Filters on Machine Learning-Based Detection of Polycystic Ovary Syndrome from Ovarian Ultrasound Images Fazrol Rozi; Syafrizal Sy; Adiwijaya; Admi Nazra; Primawati
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 4 (2026): August 2026 (in progress)
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/xwwsr649

Abstract

Polycystic Ovary Syndrome (PCOS) is commonly assessed with ovarian ultrasonography, but speckle can conceal follicular margins and reduce the robustness of automated interpretation. Although automated PCOS studies increasingly employ machine learning, the contribution of conventional despeckling to subsequent segmentation and classification has not been examined consistently. This study compares five classical filters - Mean, Median, Lee, Frost, and Kuan - within an interpretable machine-learning pipeline for ovarian ultrasound analysis. From a public collection of 12,680 images, a balanced sample of 300 scans (150 PCOS and 150 non-PCOS) was selected. Two radiologists produced follicle annotations, and disagreements were resolved with a third expert to obtain consensus masks. Each filtered image was segmented by adaptive thresholding with morphological refinement, after which geometric and intensity descriptors were extracted. Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbors (k-NN), and Logistic Regression (LR) were trained using a stratified 70/30 train-test split with cross-validated hyperparameter tuning. The Kuan-LR configuration yielded the strongest result, reaching 94.44% accuracy and an AUC of 0.98, together with the best edge-preservation score and segmentation agreement. The results indicate that preprocessing materially affects the reliability of an interpretable PCOS detection pipeline and provide quantitative guidance for selecting a speckle-reduction strategy before segmentation and classification.
Co-Authors - Primawati Adiwijaya Admi Nazra Azizah Riana Putri Budi Rudianto Effendi Effendi Fazrol Rozi, Fazrol Gema Hista Medika Helmi, Monika Rianti Muhafzan Muhafzan Syafwan, Mahdhivan Yerti Syahraini Putri Zulfaneti Zulfaneti