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All Journal JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat JTAM (Jurnal Teori dan Aplikasi Matematika) Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jambura Journal of Mathematics Jurnal Matematika UNAND Variance : Journal of Statistics and Its Applications Jurnal Statistika dan Aplikasinya Indonesian Journal of Applied Research (IJAR) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Jurnal Diferensial Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Griya Journal of Mathematics Education and Application Journal of Science and Technology Journal of Mathematics: Theory and Applications Pattimura International Journal of Mathematics (PIJMath) Jurnal Riset Mahasiswa Matematika Indonesian Journal of Computational and Applied Mathematics
La Ode Nashar
Prodi Statistika, Fakultas Matematika Dan IPA, Universitas Negeri Gorontalo
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Pemodelan Regresi Robust dengan Estimasi Generalized-M untuk Penanganan Outlier pada Kasus Kusta di Indonesia Loleh, Linda Purnama Sari; Wungguli, Djihad; Rezky Friesta Payu, Muhammad; Nashar, La Ode
Griya Journal of Mathematics Education and Application Vol. 5 No. 3 (2025): September 2025
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v5i3.811

Abstract

which attacks the skin, peripheral nerves, and other body organs except the central nervous system. New leprosy cases with visible disabilities are classified as Grade 2 disabled leprosy. The number of Grade 2 disabled leprosy cases is an indicator used to show success in early detection of new leprosy cases. However, the leprosy data in Indonesia for 2023 contains outliers that can affect the results of linear regression analysis. To address this issue, this study utilizes the robust regression method of generalized-M estimation, which is an extension of M-estimation. The objectives of this study are to obtain a robust regression model using generalized-M estimation and to identify significantly influential variables. The research findings indicate that these factors have a significant simultaneous impact on the number of leprosy cases with grade 2 disability, and partially, the factor of access to basic sanitation facilities has an influence on the number of leprosy cases with grade 2 disability with an R^2 value of 73%, which can be explained by the predictor variables in this study. Meanwhile, 27% is explained by other predictor variables not included in this study. From these results, it is hoped that the efforts of the government and relevant agencies can improve access to basic sanitation facilities for the prevention and control of leprosy cases in Indonesia.
Dynamical Analysis of a Predator-Prey Model Involving Intraspecific Competition in Predator and Prey Protection Resmawan, Resmawan; Nuha, Agusyarif Rezka; Nasib, Salmun K.; Nashar, La Ode
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 3 (2024): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i3.22154

Abstract

This article explains the interaction of the prey-predator model in the presence of wild harvesting and competition intra-specific predator populations and prey protection zones.  Model construction is based on literature studies related to the basic theory of the model and the biological properties between predator and prey populations. This study aims to look at the dynamic conditions of the predator-prey model in the form of the existence of prey and predator populations and the impact that occurs in the long term for both populations due to changes in parameter values. The model analysis begins with the formulation of the solution conditions and boundaries model, and next with the determination of the equilibrium point. Every equilibrium point is analyzed by the characteristic of its stability is neither local or global. The model owns three equilibrium points, namely the equilibrium point of population extinction (E_0), the equilibrium point of predator extinction (E_1), and the equilibrium point of persistence of the two populations (E_2). These equilibrium points are stable locally or globally if certain conditions are met. Next, it is shown that bifurcation proceeds Which describes the changing of characteristic stability point equilibrium Which depends on the threshold parameter values h_1, Ω^*, and ρ^*. In the end, numerical simulations are presented in the form of phase, time-series, and bifurcation diagrams to support the analytical results of the model, as well as to visually show the dynamic behaviour of the interaction between the two populations based on changes in predation levels, illegal harvesting, prey refuge zones, and intra-specific competition.
Prediksi Permintaan Produksi dan Strategi Pemasaran UMKM Pia Aldista Menggunakan Analisis Markov dan SWOT Suleman, Alis; Djakaria, Ismail; Nashar, La Ode
Jurnal Riset Mahasiswa Matematika Vol 5, No 1 (2025): Jurnal Riset Mahasiswa Matematika
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/jrmm.v5i1.35717

Abstract

MSMEs play a vital role in national economic growth, but fluctuations in production demand pose a challenge in maintaining operational stability. The study on the Pia Lumer Aldista MSME aims to predict production demand and formulate marketing strategies through Markov Chain Analysis and SWOT. Markov Chain is used to model demand transition patterns based on the last three years of data and determine steady-state conditions, while SWOT identifies internal and external factors that influence marketing strategies. The Chi-Square Test results indicate that the data meets the Markov assumptions. Furthermore, the analysis results indicate that the original chocolate variant will stabilize in the 10th period with a decrease of 38.4\%, while pandan chocolate is stable in the first period but experiences a drastic decrease of 29.4\%. The SWOT analysis produces an IFAS score of 3.195 and an EFAS score of 3.148, placing the MSME in Quadrant I. Therefore, aggressive strategies are recommended, such as strengthening product uniqueness, lowering prices, expanding markets, and optimizing distribution. The approach of these two methods helps anticipate market changes and increase business competitiveness.
Implementation of K-Nearest Neighbor Algorithm on Density-Based Spatial Clustering Application with Noise Method on Stunting Clustering Gani, Friansyah; Panigoro, Hasan S.; Mahmud, Sri Lestari; Rahmi, Emli; Nasib, Salmun K.; Nashar, La Ode
JURNAL DIFERENSIAL Vol 6 No 2 (2024): November 2024
Publisher : Program Studi Matematika, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jd.v6i2.16278

Abstract

This paper studies the implementation of the K-Nearest Neighbor (KNN) algorithm on Density-Based Spatial Clustering Application with Noise (DBSCAN) method on stunting Clustering in the eastern region of Indonesia in 2022. The DBSCAN method is used because it is more efficient to perform the Clustering process for irregular Clustering shapes. The main objective of this study is to apply the KNN algorithm to the DBSCAN Clustering technique in 161 Districts/Cities in 11 provinces in eastern Indonesia. A comparison of the performance evaluation of the DBSCAN Clustering technique is done by considering the value of the Silhouette score, BetaCV score, and Davies-Bouldin score indicating the quality of the Clusters formed with the lowest results scores of 0.67 and 1.84 with epsilon value = 3.4 and minimum point value = 2 resulting in 4 Clusters. The results of Clustering 161 Districts and Cities based on the factors that cause stunting formed 4 Clusters where Cluster 0 consists of 119 Districts and Cities with very high stunting characteristics, Cluster 1 consists of 3 Districts and Cities with high stunting characteristics, the results of Cluster 2 consist of 2 Districts and Cities with low stunting characteristics, then the results of Cluster 2 consist of 2 Districts and Cities with low stunting characteristics and Cluster 3 consists of 2 Cities with very low stunting characteristics.
Analisis Sensitivitas Model Goal Programming Pada Optimasi Produksi Roti Menggunakan Metode Branch and Bound Ahmad, Rindawati; Katili, Muhammad Rifai; Mahmud, Sri Lestari; Wungguli, Djihad; Nashar, La Ode
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 11 Issue 2 December 2023
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v11i2.22299

Abstract

Sya'qila Bakery is a manufacturing industry that produces bread in five flavor variants. The planning carried out by Sya'qila Bakery in the bread production process is considered suboptimal due to the limitation in the quantity of production for each flavor variant, resulting in occasional shortages of raw materials. Additionally, the order production process requires a long total completion time (makespan), resulting in delays in production completion (meaning tardiness). This research aims to optimize the total completion time, the average lateness, the use of raw materials, and production revenue. In this research, the Goal Programming model is utilized with the Branch and Bound method. The analysis results with the Goal Programming model using the Branch and Bound method obtain an optimal solution, which includes an excess of 36 minutes in total completion time (makespan), an excess of 6 minutes in average lateness (mean tardiness), no excess in the availability of raw materials, and zero sales revenue shortfall. Sensitivity analysis results indicate that bread production at Sya'qila Bakery will remain optimal if changes occur in the production completion time, production delay time, and raw material availability, as long as these changes remain within their tolerance limits.
DISTRIBUTED LAG MODEL PENGARUH JUMLAH UANG BEREDAR TERHADAP NILAI TUKAR RUPIAH MENGGUNAKAN METODE KOYCK DAN ALMON LIHAWA, SRIRAPI H; RESMAWAN, RESMAWAN; ISA, DEWI RAHMAWATY; NASHAR, LA ODE
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.v3i1.11805

Abstract

A regression model that contains the dependent variable which is influenced by the current independent variable, and is also influenced by the independent variable at the previous time is called a distributed lag model. Distributed lag model is a dynamic model in econometrics that is useful in empirical econometrics because it makes a static economic theory dynamic by taking into account the role of time explicitly. There are two distributed lag models, namely the infinite lag model and the finite lag model using the Koyck method and the Almon method in determining the estimated Distributed lag model. This study aims to determine the Distributed lag model for the effect of the money supply on the rupiah exchange rate and determine the best model based on the Koyck method and the Almon method. From the results of selecting the best model based on the SIC value and judging by the more precise R2 of the Koyck method, the resulting model ist  = 7958 + 0.0002Xt + 0.000177Xt-1+ 0.000157Xt-2+ 0.000139Xt-3 + 0.0000123Xt-4
Determination of Premium Price for Rice Crop Insurance in Gorontalo Province Based on Rainfall Index with Black Scholes Method Nadiyyah, Ana; Rahmi, Emli; Nasib, Salmun K.; Nuha, Agusyarif Rezka; Yahya, Nisky Imansyah; Nashar, La Ode
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/pijmathvol3iss2pp51-62

Abstract

With its complex topography, Gorontalo Province experiences significant rainfall variations that impact the agricultural sector, particularly rice crops. These variations can cause substantial losses for farmers. One way to address uncertain probabilities caused by rainfall is through agricultural insurance. This research aims to calculate the value of agricultural insurance premiums based on the rainfall index. The Black- Scholes method is used to calculate the premiums, while the Burn Analysis method is employed to determine the rainfall index. The research results classify the rainfall index values in Gorontalo Province into 7 (seven) percentiles. The lowest is at the 20th percentile, with 17.37 mm and a premium value of IDR 1,574,190, while the highest is at the 80th percentile, with 17.65 mm and a premium value of IDR 2,154,574. This indicates that the higher the rainfall, the greater the premium to be paid.
Particle Swarm Optimization-Enhanced DBSCAN for Clustering Malnutrition Data on Java Island, Indonesia Nurafni, Firda; Nashar, La Ode; Panigoro, Hasan S.
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.v1i1.7

Abstract

This manuscript proposes an approach that uses the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) method in mapping the spatial pattern of malnutrition in Java. Results showed that with a Silhouette Coefficient value close to 1 (0.134) and the lowest Davies-Bouldin Index (1.80), PSO successfully determined the optimal epsilon (eps) value of 1.76 and the optimal minimum number of points of 3. Index validation showed that DBSCAN could map the study area into three clusters that reflected the level of malnutrition, where 82 districts/cities were included in Cluster 0, 5 districts/cities in Cluster 1, and 3 districts/cities in Cluster 2. In contrast, 29 districts/cities were identified as noise. This finding confirms that the PSO approach in optimizing DBSCAN parameters can improve the method's effectiveness in handling complex cases such as malnutrition in a geospatial context.
STRUCTURAL EQUATION MODELING-GENERALIZED STRUCTURED COMPONENT ANALYSIS TO ANALIZING STRUCTURE OF POVERTY IN INDONESIA IN 2022 Marukai, Nur Amalia; Wungguli, Djihad; Nashar, La Ode; Nasib, Salmun K.; Asriadi, Asriadi; Abdussamad, Siti Nurmardia
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 2 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol7iss2page167-174

Abstract

Structural Equation Modeling - Generalized Structured Component Analysis (SEM-GSCA) is a component-based method suitable for limited sample sizes. GSCA is appropriate for structural models that include variables with reflective and formative indicators. This study utilizes the Alternating Least Square (ALS) parameter estimation. Iterations in ALS are used to achieve minimal residuals. Additionally, this study employs jackknife resampling to obtain standard error estimates. This study aims to identify the poverty model structure in Indonesia and examine the relationships among poverty, human resources, economic, and health variables. The results of the structural model of poverty in Indonesia are explained as follows: the influence of human resources and economic variables on poverty is insignificant, while the health variable significantly negatively influences poverty. Furthermore, the health variable significantly influences human resources, and both human resources and health significantly influence the economy.
Co-Authors Agusyarif Rezka Nuha Ahmad, Rindawati Akor, Umar D. Asriadi Asriadi Asriadi Asriadi Brahim, Annisa Maharani Chasanah, Sri Istiyarti Uswatun Dewi Rahmawaty Isa Dina Fakhriyana Djihad Wungguli Fadilah Istiqomah Pammus Gani, Friansyah Hasan S. Panigoro Hasan, Riyanto Hasibuan, Lilis Harianti Herlina Jusuf Ismail Djakaria Isran K Hasan Iyohu, Lisa Rianti K. Hasan, Isran Karina Anselia Mamonto LA ODE SABRAN Ladjali, Sri Indriani Lailany Yahya Latif, Sintia Abdul LIHAWA, SRIRAPI H Lindrawati Abdjul Loleh, Linda Purnama Sari Mahmud, Sri Lestari Marukai, Nur Amalia Muhammad Rezky F. Payu Nadiyyah, Ana NISKY IMANSYAH YAHYA Novianita Achmad Nurafni, Firda Nurwan Nurwan Nurwan Nurwan Nurwan NURWAN NURWAN Nurwan Nurwan Rahman, Gusti Arviana Rahmi, Emli Rasyid, Kamelia Resmawan Resmawan Rianjaya, Ilham Dangu Sabran, La Ode Salmun K. Nasib Sartika Sari Dewi Siti Nurmardia Abdussamad Sugito Mahendra Imran Suleman, Alis Syarif Abdullah Tedy Machmud Ulopo, Asrul S Valentika, Nina Zian Bula