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All Journal Media Statistika Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Mahasiswa Jurusan Arsitektur Jurnal Mahasiswa Statistik Journal of Natural A Natural B Jurnal Ekonomi & Studi Pembangunan BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Media Mahardhika ComTech: Computer, Mathematics and Engineering Applications Jurnal Ilmiah Aquinas Industri Inovatif : Jurnal Teknik Industri Inferensi JIHAD : Jurnal Ilmu Hukum dan Administrasi Jurnal Ilmiah Manajemen dan Bisnis (JIMBI) Jurnal Dimamu Pangripta Jurnal Ilmiah Kajian Perencanaan Pembangunan Jurnal Sosial Ekonomi Perikanan Economics Development Analysis Journal Indonesian Journal of Statistics and Its Applications
Rahma Fitriani
Department Of Mathematics, University Of Brawijaya, Malang
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : BAREKENG: Jurnal Ilmu Matematika dan Terapan

 1 
APPLICATION OF DBSCAN FOR CLUSTERING SOCIETY BASED ON WASTE MANAGEMENT BEHAVIOR Al Jauhar, Hafizh Syihabuddin; Solimun, Solimun; Fitriani, Rahma
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp961-972

Abstract

This research aims to answer the challenge of identifying the characteristics of the Batu City community in waste management, where traditional clustering techniques are often suboptimal due to the presence of noise or objects that do not fit the general pattern. As a solution, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is applied, which allows the clustering of objects based on local density and detects the presence of noise or outliers in the data. DBSCAN is considered more flexible than other clustering methods, especially in clustering data that is not linear or has a non-uniform distribution. This study successfully identified three clusters of waste management behavior with a silhouette index of 0.875, indicating good cluster quality. The first cluster consists of communities with good environmental quality, active participation in the use of waste banks, and a deep understanding of 3R-based waste management. The second cluster has adequate infrastructure quality and high awareness of the potential economic benefits of waste, while the third cluster displays a pretty good level of understanding of the 3Rs and relatively good environmental quality. The results of this study provide important insights into the differences in waste management characteristics between clusters, with environmental quality proving to be a significant factor in cluster formation.
ESTIMATION OF MAXIMUM LIKELIHOOD WEIGHTED LOGISTIC REGRESSION USING GENETIC ALGORITHM (CASE STUDY: INDIVIDUAL WORK STATUS IN MALANG CITY) Menufandu, Dahlia Gladiola Rurina; Fitriani, Rahma; Sumarminingsih, Eni
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (399.767 KB) | DOI: 10.30598/barekengvol17iss1pp0487-0494

Abstract

Weighted Logistic Regression (WLR) is a method used to overcome imbalanced data or rare events by using weighting and is part of the development of a simple logistic regression model. Parameter estimation of the WLR model uses Maximum Likelihood estimation. The maximum likelihood parameter estimator value is obtained using an optimization approach. The Genetic algorithm is an optimization computational algorithm that is used to optimize the estimation of model parameters. This study aims to estimate the Maximum Likelihood Weighted Logistic Regression with the applied genetic algorithm and determine the significant variables that affect the working status of individuals in Malang City. The data used is the result of data collection from the National Labor Force Survey of Malang City in 2020. The results of the analysis show that the variable education completed and the number of household members has a significant effect on individual work status in Malang City.
CLUSTER FAST DOUBLE BOOTSTRAP APPROACH WITH RANDOM EFFECT SPATIAL MODELING Ngabu, Wigbertus; Fitriani, Rahma; Pramoedyo, Henny; Astuti, Ani Budi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0945-0954

Abstract

Panel data is a combination of cross-sectional and time series data. Spatial panel analysis is an analysis to obtain information based on observations affected by the space or location effects. The effect of location effects on spatial analysis is presented in the form of weighting. The use of panel data in spatial regression provides a number of advantages, however, the spatial dependence test and parameter estimators generated in the spatial regression of data panel will be inaccurate when applied to areas with a small number of spatial units. One method to overcome the problem of small spatial unit size is the bootstrap method. This study used the fast double bootstrap (FDB) method by modeling the poverty rate in the Flores islands. The data used in the study was sourced from the BPS NTT Province website. The results of Hausman test show that the right model is Random effect. The spatial dependence test concludes that there is a spatial dependence and the poverty modeling in the Flores islands tends to use the SAR model. SAR random effect model R2 shows the value of 77.38 percent and it does not meet the assumption of normality. Spatial Autoregressive Random effect model with the Fast Double Bootstrap approach is able to explain the diversity of poverty rate in the Flores Island by 99.83 percent and fulfilling the assumption of residual normality. The results of the analysis using the FDB approach on the spatial panel show better results than the common spatial panel.
ENHANCING WEIGHTED FUZZY TIME SERIES FORECASTING THROUGH PARTICLE SWARM OPTIMIZATION Zamelina, Armando Jacquis Federal; Astutik, Suci; Fitriani, Rahma; Fernandes, Adji Achmad Rinaldo; Ramifidisoa, Lucius
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2675-2684

Abstract

Climate change is a complex process that has far-reaching consequences for daily living. Temperature is one of the climatic features. Knowing its future value through a forecasting model is critical, as it aids in earlier strategic decision-making. Without considering spatial factors, this study investigates an Air Temperature variable forecasting. Weighted Fuzzy Time Series (WFTS) is one of the forecasting techniques. Furthermore, the length of the interval and the extent to which previous values (Order length) are utilized in predicting the subsequent value are pivotal factors in WFTS modelization and its forecasting accuracy. Therefore, this research investigates the interval length and the Order length of the WFTS through the Particle Swarm Optimization (PSO) approach. The variable used is the air temperature in Malang, Indonesia. The dataset is taken from BMKG-Indonesia. The forecasting performance of classical WFTS is enhanced by setting an appropriate order level and employing Particle Swarm Optimization (PSO) to determine the optimal interval fuzzy length. As indicated by the Evaluation matrices in the result section, the proposed optimization overtaken the classical WFTS in term of accuracy. The evaluation indicates a Mean Absolute Percentage Error (MAPE) value of 1.25 and a Root Mean Square Error (RMSE) of 0.32 for the Proposed model. In contrast, the classical WFTS demonstrates a MAPE of 2.26 and RMSE of 0.58. The implementation of the PSO provides solid insights for Air temperature forecasting accuracy.
CLUSTERING WITH SKATER METHODS AND UTILIZATION OF LISA ON UNEMPLOYMENT RATE Abdila, Naufal Shela; Fitriani, Rahma; Pratama, Muhamad Liswansyah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2633-2646

Abstract

Spatial cluster analysis is an analysis used to identify a spatial pattern or geographical grouping of data. One method that can be used in spatial cluster analysis is Spatial Cluster Analysis by Tree Edge Removal (SKATER). This research aims to analyze the spatial pattern of the Unemployment Rate in East Java by utilizing the SKATER method. The clustering results are then used to create a weighting matrix, which is used to find local spatial autocorrelation values ​​using the Local Indicators of Spatial Association (LISA) index. The data is taken from BPS East Java with variables including unemployment rate, education level, minimum wage, Human Development Index, and population density. The results show that this approach is able to identify significant local spatial patterns. However, the selection of the number of clusters and input variables proved to be very influential on the results, so care needs to be taken.
Co-Authors Abdila, Naufal Shela Agung Murti Nugroho Agus Dwi Sulistyono, Agus Dwi Akhmad Mansyur, Akhmad Al Jauhar, Hafizh Syihabuddin Alfi Fadliana Ani Budi Astuti Antonius Totok Priyadi Atiek Iriani, Atiek Atiek Iriany Azizah, Amelia Nur Darmanto Darmanto Dianiati, Aldila Nur Eddi Basuki Kurniawan Encep Supriatna Eni Sumarminingsih Fernandes, Adji Achmad Rinaldo Firdausi, Rizka Firsa, Pocut Zahran Nada Gusganda Suria Manda Handoyo, Samingun Hapsari, Ulfalina Henny Pramoedyo Herman Cahyo Diartho Hermanto, Tutut Istiqomah, Nur Jaka Pratama Musashi Jannah, Friendtika Miftaqul Jannah, Friendtika Miftaqul Korniasari, Leli Dwi Kusdarwati, Heni La Onu, La Ola Lestari, Kartika Ayu Liduina Asih Primandari, Liduina Asih Loekito Adi Soehono Maharani, Kasih Mahendra, Di Aidil Menufandu, Dahlia Gladiola Rurina Mitakda, Maria Bernadetha Ni Wayan Surya Wardhani Ni Wayan Surya Wardhani Nofriadi Nofriadi Nugroho, Salma Fitri Nur Aisyah Nurachmad Sujudwijono Pasca, Paunfia Meiditha pramoedyo, henny Pratama, Muhamad Liswansyah Pribadi, Teddy Ramadhan, Apry Zakaria Ramifidisoa, Lucius Risfandi Ry, Mohd Dzaky Sarini Yusuf Septya Hadiningrum Sesilia Seli Sholihah, Suma Suci Solimun, Solimun Suci Astutik Sumarminingsih, Eni Sundyni, Reza Chyta Syukrilla, Wara Alfa Tampubolon, Risma Hartati Tri Pratiwi, Elly Andita Umami, Asri Rizza Vierkury Metyopandi Vivit Senja, Dinda Rinai Waego Hadi Nugroho Widya Reza Wigbertus Ngabu Yusrina Nur Dianati Zakaria Zamelina, Armando Jacquis Federal