Article Per Year (5 Year)
p-Index From 2021 - 2026
4.923
P-Index
This Author published in this journals
All Journal Jurnal Statistika Universitas Muhammadiyah Semarang PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Indonesian Journal of Applied Statistics BAREKENG: Jurnal Ilmu Matematika dan Terapan Jambura Journal of Mathematics METIK JURNAL Jurnal Matematika UNAND Variance : Journal of Statistics and Its Applications ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal Statistika dan Aplikasinya JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Research in the Mathematical and Natural Sciences Prosiding Seminar Nasional Pendidikan Matematika, Universitas Mulawarman Pattimura International Journal of Mathematics (PIJMath) Jurnal Riset Mahasiswa Matematika The Indonesian Journal of Computer Science Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Computational and Applied Mathematics
Isran K Hasan
Universitas Negeri Gorontalo
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 38 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 38 Documents
Search

 1   2   3   4 
Model Matematika Penyebaran Penyakit Demam Berdarah Dengue dengan Faktor Kesadaran Sosial: Analisis dan Simulasi Djuma, Clara Anggriani; Achmad, Novianita; Nuha, Agusyarif Rezka; Hasan, Isran K.; Arsal, Armayani
Jambura Journal of Mathematics Vol 7, No 2: August 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v7i2.33921

Abstract

Dengue haemorrhagic fever (DHF) is a serious health problem in many tropical regions, including Indonesia. The spread of this disease is influenced by various factors, one of which is the level of social awareness in the prevention and control of infection. This study developed a mathematical model of DHF spread by integrating social awareness as an additional compartment. The model was analysed by determining the equilibrium points and the basic reproduction number (R0), as well as stability analysis using the Routh–Hurwitz criterion. The analysis results show the existence of two types of equilibrium points: the disease-free equilibrium point (T1) and the endemic equilibrium point (T2). Point T1 is locally asymptotically stable when R0 1 and unstable when R0 1, while point T2 is locally asymptotically stable when R0 1. Sensitivity analysis shows that the social awareness parameter significantly influences the value of R0. Additionally, numerical simulations indicate that increasing social awareness can effectively reduce disease spread and drive the system toward a disease-free state. These findings underscore the importance of community-based awareness interventions in dengue control strategies.
APPLICATION OF BINARY LOGISTICS REGRESSION AND RANDOM FOREST TO CIGARETTE CONSUMPTION EXPENDITURE IN GORONTALO REGENCY 2022 Hamani, Mohamad Taufik; Isa, Dewi Rahmawaty; Nasib, Salmun K.; Panigoro, Hasan S.; Hasan, Isran K.; Yahya, Nisky Imansyah
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 13, No 1 (2025): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.13.1.2025.14-22

Abstract

The goal of this research is to predict or identify an object's class using its available attributes through classification. The aim of this research is to use the random forest method to develop a classification model and the binary logistic regression method to discover significant determinants in cigarette consumption expenditure in Gorontalo Regency. The findings indicated that the size of the home, the number of family members, and the head of the household's educational attainment all had a considerable impact. Only the household head's educational attainment, however, consistently influences the model and satisfies the goodness of fit requirements. In contrast, the random forest model outperformed binary logistic regression in the classification analysis when classification characteristics including accuracy, precision, recall, and f1-score were assessed. Consequently, random forest was found to be the most effective classification model in this investigation.
PENERAPAN MODEL SPASIAL DURBIN DENGAN UJI LANJUTAN LOCAL INDICATOR OF SPATIAL AUTOCORRELATION UNTUK MELIHAT PENYEBARAN STUNTING DI KABUPATEN BONE BOLANGO HASIRU, LISA SYAHRIA; DJAKARIA, ISMAIL; HASAN, ISRAN K
Jambura Journal of Probability and Statistics Vol 3, No 1 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i1.13083

Abstract

One of the spatial regression analysis used is the spatial durbin model (SDM). This model can be applied to obtain the relationship between X and Y variables and their spatial effects. This research was continued by testing the local spatial autocorrelation, namely the local indicator of spatial autocorrelation (LISA) which aims to provide information on the pattern of spatial relationships of each observation area in Bone Bolango regency. Stunting cases in Gorontalo province, especially in Bone Bolango regency, are in a status that needs to be addressed immediately due to the prevalence rate in Bone Bolango regency in 2019 above 20% based on the WHO standard. The results showed that the factors that significantly affected stunting in 2019 in Bone Bolango regency were exclusive breastfeeding, the  proper sanitation and poverty. Meanwhile, based on the spatial effect, the factors that significantly affected stunting in 2019 in Bone Bolango regency were the percentage of exclusive breastfeeding, the percentage of LBW, the number of children with CBI and poverty. Based on result from the LISA, the observation areas of stunting cases showed that the percentage of exclusive breastfeeding, the number of children with CBI and povertu had a spatial autocorrelation or forming a grouping on the distribution of the stunting cases, the number of children with IDL and poverty, there are sub-districts that have spatial autocorrelation.
Implementasi Deep Learning dalam Pengklasifikasian Wajah Menggunakan Library Tensorflow pada Algoritma Convolutional Neural Network (CNN) Usman, Rahmat Setiawan; Hasan, Isran K.; Isa, Dewi Rahmawaty
Jambura Journal of Probability and Statistics Vol 4, No 2 (2023): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v4i2.18264

Abstract

The convolutional neural network is a deep learning method that functions to recognize and classify objects in an image. An example of its application is a facial recognition system which consists of a detection and classification process. Facial recognition by computers can be influenced by many things such as lighting, expressions, and the amount of dataset provided. This study aims to find out how to implement CNN to identify faces using Tensorflow with the Python programming language. The number of datasets used is 120 data and 10 respondents in total with different lighting conditions and shooting angles. Apart from the dataset, this study also uses several different scenarios in the training process, namely the difference in the number of epochs and the difference in the number of learning rates. Based on the results of the discussion, two models were obtained. In the first model, the results obtained an accuracy of 100% in the training process and 65% in the testing process. In the second model, the results obtained are 100% accuracy in the training process and 75% in the testing process. performance of the model made in this study can be said to be optimal in recognizing objects in several lighting conditions and image angles.
Wind Speed Category Characteristics in Bone Bolango Regency: A Markov Chain Approach Using the Beaufort Scale and Metropolis-Hastings Algorithm Pomahiya, Saiful; Nurwan, Nurwan; Yahya, Nisky Imansyah; Nasib, Salmun K.; Hasan, Isran K.; Asriadi, Asriadi
Pattimura International Journal of Mathematics (PIJMath) Vol 3 No 2 (2024): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol3iss2pp63-68

Abstract

This study models daily wind speed transitions in the Bone Bolango Regency using the Markov Chain Monte Carlo (MCMC) method and the Metropolis-Hastings algorithm, employing the Beaufort scale for wind speed classification. The research aims to predict the steady-state distribution of wind speeds and evaluate their temporal stability. Daily wind speed data from 2023, provided by the Meteorology, Climatology, and Geophysics Agency (BMKG), were categorized into three levels: calm, light breeze, and fresh breeze, based on the Beaufort scale. Transition probabilities were estimated using the Beta distribution, and simulations via the Metropolis-Hastings algorithm yielded the steady-state distribution. Results show a significant tendency for transitions from calm and light breeze categories to fresh breezes, with varying probabilities. Notably, calm conditions exhibit a 69% likelihood of transitioning to a light breeze. This research contributes to improving wind speed prediction models by integrating statistical algorithms with meteorological classifications. The findings have implications for enhancing short-term weather forecasts and developing predictive systems for regions with similar weather patterns.
Implementation of Fuzzy Time Series Markov Chain Method using Kernel Smoothing in forecasting the Stock Price of PT. Elnusa Tbk. Mokodompit, Marcela; Nasib, Salmun K; Djakaria, Ismail; Yahya, Nisky Imansyah; Hasan, Isran K.
Indonesian Journal of Computational and Applied Mathematics Vol. 1 No. 1: February 2025
Publisher : Gammarise Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64182/indocam.v1i1.9

Abstract

This research aims to apply the Fuzzy Time Series Markov Chain combined with Kernel Smoothing in forecasting stock prices. The Kernel Smoothing technique is used to smooth stock data before the fuzzification process, resulting in more accurate predictions. The research stages include Data Smoothing, Fuzzy interval formation, Fuzzy Logical Relationship and Fuzzy Logical Relationship Group formation, and forecasting using Markov Chain Transition Matrix. Evaluation using MAPE shows a low prediction error rate, with a value of 0.005974257%, so this method is effective for volatile stock data. The implementation of this model is expected to be a reference for investors and analysts in understanding and predicting future stock price movements.
A Mathematical Model of the Mud Crab (Scylla Sp.) Involving Cannibalism and Refuge Abubakar, Agung Sucipto; Panigoro, Hasan S.; Djakaria, Ismail; Nuha, Agusyarif Rezka; Hasan, Isran K.; Asriadi, Asriadi
Indonesian Journal of Computational and Applied Mathematics Vol. 1 No. 1: February 2025
Publisher : Gammarise Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64182/indocam.v1i1.12

Abstract

Cannibalism, a common ecological phenomenon in various species, significantly impacts the population dynamics of mud crabs (Scylla sp.). This study develops a mathematical model to analyze the effects of cannibalism and protective refuges on the population sustainability of juvenile and adult mud crabs. The model identifies two equilibrium points: the extinction equilibrium and the coexistence equilibrium. Stability analysis using the Jacobian matrix reveals that the extinction equilibrium is locally asymptotically stable under specific conditions. In contrast, the coexistence equilibrium depends on the transition rate from juvenile to adult crabs and the effectiveness of protective measures. Numerical simulations demonstrate that increasing the transition rate and implementing higher levels of refuge protection mitigate the adverse effects of cannibalism, enhancing population stability. These findings provide a quantitative foundation for sustainable fisheries management and conservation strategies for mud crab populations in mangrove ecosystems.
Developing a Python-Based Application for a Discrete-Time Population Dynamics Model Nadhilah, Farhah; Panigoro, Hasan S.; Arsal, Armayani; Nurwan, Nurwan; Wungguli, Djihad; Hasan, Isran K.
Indonesian Journal of Computational and Applied Mathematics Vol. 1 No. 2: June 2025
Publisher : Gammarise Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64182/indocam.v1i2.20

Abstract

Difference equation is a type of equation in mathematics that is widely used to describe certain phenomena as time changes, one of which is in the field of population dynamics. In various studies, it is explained that solving complex population dynamics models is by using numerical simulations. Along with the development of technology, computational science is used to help solve mathematical problems that are difficult to solve analytically. One of them is to use a programming language, such as Python, to help present data in a graphical form. This research aims to develop an application that presents a computational solution to a difference equation using Python. The numerical results begin by entering the equation and variable values into the application, which then automatically generates a figure according to the entered equation. The figures generated in the application include one-dimensional and two-dimensional time series, as well as a Bifurcation diagram.
Co-Authors Abubakar, Agung Sucipto Agusyarif Rezka Nuha Alaina, Silvana Rahmayanti Alvitha Habibie Armayani Arsal Asriadi Asriadi Asriadi Asriadi Buhungo, Rayhanul Jannah Demas Novaleda Abdul Karim Dewi Rahmawaty Isa Djihad Wungguli Djuma, Clara Anggriani Doholio, Nadya Pratiwi Emiro, Awalia Hamani, Mohamad Taufik Harmain, Ismail Saputra R. Harun, Trieke Nurfadilah Hasan S. Panigoro HASIRU, LISA SYAHRIA Hinelo, Ikrar Prasetyo I Wayan Can Aryasandi Indrawati Lihawa Ismail Djakaria Ivan Novri Jefriyanto Ibrahim Karim, Finansiya S. Abd. Kasim, Afrianto Pratama Khairun Nisa Humolungo Kilo, Nur Ain Kurniawan Kurniawan La Ode Nashar Lailany Yahya Lapitung, Putri Mokodompit, Marcela Nadhilah, Farhah Nanda Arista Rizki NISKY IMANSYAH YAHYA Novianita Achmad Nur Falaq Nurdin, Sri Ayu Nurul Afifah Nurwan Nurwan Nurwan, Nurwan Pakaya, Desya Neydi Putri Pomahiya, Saiful Rahmi, Emli Resmawan Resmawan Salmun K. Nasib Sampe, Nofia Sigar, Tesya Siti Nurmardia Abdussamad Suharmin, Wandayana Nur'Amanah Sumarno Ismail Thesalonica Graina Barung Ulopo, Asrul S Usman, Rahmat Setiawan Wewengkang, Hanz Franklyn Bachruddin Winni A. Pakaya wolah, Meitasya