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Study Program of Mathematics, Department of Mathematics, Faculty of Science and Technology, Universitas Airlangga, Indonesia Kampus C UNAIR Jl. Mulyorejo Surabaya, Jawa Timur 60115
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Contemporary Mathematics and Applications (ConMathA)
Published by Universitas Airlangga
ISSN : -     EISSN : 26865564     DOI : https://doi.org/10.20473/conmatha
Core Subject : Science, Education,
Materials Science & Nanotechnology Mathematics
Contemporary Mathematics and Applications welcome research articles in the area of mathematical analysis, algebra, optimization, mathematical modeling and its applications include but are not limited to the following topics: general mathematics, mathematical physics, numerical analysis, combinatorics, optimization and control, operation research, statistical modeling, mathematical finance and computational mathematics.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 3 No. 1 (2021)" : 5 Documents clear
The Dynamics of a Discrete Fractional-Order Logistic Growth Model with Infectious Disease Hasan S Panigoro; Emli Rahmi
Contemporary Mathematics and Applications (ConMathA) Vol. 3 No. 1 (2021)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v3i1.26938

Abstract

In this paper, we study the dynamics of a discrete fractional-order logistic growth model with infectious disease. We obtain the discrete model by applying the piecewise constant arguments to the fractional-order model. This model contains three fixed points namely the origin point, the disease-free point, and the endemic point. We confirm that the origin point is always exists and unstable, the disease-free point is always exists and conditionally stable, and the endemic point is conditionally exists and stable. We also investigate the existence of forward, period-doubling, and Neimark-Sacker bifurcation. The numerical simulations are also presented to confirm the analytical results. We also show numerically the existence of period-3 solution which leads to the occurrence of chaotic behavior.
Analisis Kestabilan dan Kontrol Optimal Model Matematika Partisipasi Pemilih pada Pemilihan Umum dengan Saturated Incidence Rate Dinda Ariska Putri; Windarto Windarto; Cicik Alfiniyah
Contemporary Mathematics and Applications (ConMathA) Vol. 3 No. 1 (2021)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v3i1.26939

Abstract

Voter participation in general elections is an important aspect of a democratic state structure. Participation is determined by the level of public political awareness, if the level of public political awareness is low, voter participation tends to be passive (Abstinence). A mathematical model approach to voter participation in elections that has been modified to a saturated incidence rate is needed to predict voter participation in future elections. This thesis aims to analyze the stability of the equilibrium point and apply the optimal control variable in the form of an awareness campaign. In the model without control variables, we obtain two equilibriums, namely, the non-endemic equilibrium and the endemic equilibrium. Local stability and the existence of endemic equilibrium depend on the basic reproduction number (R0), where R0=bL/(g+m)m. There is voter participation in elections when R0 < 1 and the absence of voter participation in elections when R0 > 1. We also analyze the sensitivity of parameters to determine which parameters are the most influential in this mathematical model. Furthermore, the application of control variables in the mathematical model of voter participation in elections with saturated incidence rate is determined through the Pontryagin Maximum Principle method. Numerical simulation results show that providing control variables in the form of awareness campaign it is quite effective in minimize the number of the voting population who abstained from election.
Penerapan Metode Learning Vector Quantization (LVQ) untuk Mendeteksi Penyalahgunaan Narkoba Berny Pebo Tomasouw; Salmon Notje Aulele; Monalisa E. Rijoly
Contemporary Mathematics and Applications (ConMathA) Vol. 3 No. 1 (2021)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v3i1.26940

Abstract

Dalam penelitian ini, metode LVQ akan diterapkan untuk mendeteksi penyalahgunaan narkoba berdasarkan gejala-gejala yang dialami seseorang. Untuk mendapatkan tingkat akurasi terbaik, maka data pelatihan dan data pengujian dibagi ke dalam tiga skema pembagian data yakni 60/40, 70/30 dan 80/20. Setelah dilakukan proses pelatihan dan pengujian menggunakan metode LVQ dengan berbagai variasi nilai laju pembelajaran dan jumlah epoch, maka diperoleh tingkat akurasi terbaik sebesar 86.7 % pada skema pembagian data 70/30 dengan laju pembelajaran  = 0.001 dan  = 0.005.
Detection of Heart Abnormalities Based On ECG Signal Characteristics using Multilayer Perceptron with Firefly Algorithm-Simulated Annealing Sofiah Ishlakhul Abda; Auli Damayanti; Edi Winarko
Contemporary Mathematics and Applications (ConMathA) Vol. 3 No. 1 (2021)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v3i1.26941

Abstract

Heart disease is one of the causes of death worldwide. Therefore, detecting heart disease is very important to reduce the increased mortality rate. One of the methods used to detect the abnormalities or disorders of the heart is to use computer assistance to determine the characteristics of an electrocardiogram. Electrocardiogram (ECG) is a test that detects and records the activity of the heart through small metal electrodes attached to the skin of one's chest, arms and legs. This test shows how fast the heart beats and whether the rhythm is stable or not. The purpose of this thesis is to apply a multi-layer perceptron model with firefly algorithm and simulated annealing in detecting cardiac abnormalities based on the ECG signal characteristics. The initial step of this research is image processing. The stages of ECG image processing are grayscale, thresholding, edge detection, segmentation and normalization processes. The results of this image processing are used as input matrices in the perceptron multilayer network training using firefly algorithm and simulated annealing. In the training process, we will get optimal weights and biases for validation tests on test data. The training data in this thesis uses 20 ECG images and in the validation test process uses 10 ECG images. The validation results in the validation test show that the accuracy in detecting heart abnormalities based on the characteristics of ECG signals using multi- layer perceptron with firefly algorithm and simulated annealing is 100%.
Hybrid Jaringan Saraf Tiruan Backpropagation dengan Firefly Algorithm dan Simulated Annealing untuk Peramalan Curah Hujan di Surabaya Dicky Zulfikar Zurkarnain; Auli Damayanti; Edi Winarko
Contemporary Mathematics and Applications (ConMathA) Vol. 3 No. 1 (2021)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v3i1.26942

Abstract

Indonesia mempunyai berbagai jenis iklim. Salah satu parameter iklim adalah curah hujan. Curah hujan yang dapat menjadi sumber bencana adalah curah hujan ekstrem, yaitu kondisi curah hujan yang cukup tinggi/rendah dari rata-rata kondisi normalnya. Informasi tentang peramalan curah hujan sangat berguna khususnya bagi pemerintah kota Surabaya dalam mengantisipasi kemungkinan kejadian-kejadian atau bencana yang diakibatkan oleh curah hujan ekstrem seperti, kekeringan, banjir, pohon tumbang, rusaknya fasilitas umum, dll. Tujuan dari penulisan skripsi ini adalah untuk mendapatkan nilai peramalan curah hujan di Surabaya pada bulan yang akan datang menggunakan Hybrid Jaringan Saraf Tiruan Backpropagation dengan Firefly Algorithm dan Simulated Annealing. Proses diawali dengan input dan normalisasi data, kemudian dilanjutkan dengan proses pelatihan untuk mencari bobot dan bias yang optimal. Setelah diperoleh bobot dan bias yang optimal, kemudian melakukan uji validasi, dan dilanjutkan dengan proses peramalan. Pada proses peramalan curah hujan, data yang digunakan sebanyak 120 data curah hujan bulanan dari bulan Januari 2008 hingga bulan Desember 2017 dengan ketentuan 80% data untuk pelatihan dan 20% data untuk uji validasi. Data yang digunakan, selanjutnya dilatih kemudian dicari nilai Mean Square Error (MSE) dan bobot yang optimal. Bobot optimal yang diperoleh, selanjutnya diuji dengan uji validasi untuk mengetahui seberapa baik pola yang dikenali. Berdasarkan implementasi pada data curah hujan tersebut, diperoleh nilai MSE hasil pelatihan sebesar 0.0395384228 dan nilai selisih rata-rata sebesar 3,75382. Sedangkan hasil peramalan untuk 3 bulan berikutnya yaitu bulan Januari hingga Maret 2018 berturut-turut adalah 6.1451, 8.5459, dan 7.7391.

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