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Kiswara Agung Santoso
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Majalah Ilmiah Matematika dan Statistika (MIMS)
Published by Universitas Jember
ISSN : 14116669     EISSN : 27229866     DOI : https://doi.org/10.19184
Core Subject : Education,
Mathematics
The aim of this publication is to disseminate the conceptual thoughts or ideas and research results that have been achieved in the area of mathematics and statistics. MIMS, focuses on the development areas sciences of mathematics and statistics as follows: 1. Algebra and Geometry; 2. Analysis and Modelling; 3. Graph Theory and Combinatorics; 4. Computer Science and Big Data; 5. Application of Mathematics and Statistics.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 120 Documents
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Pemodelan kasus tingkat kemiskinan di Indonesia periode 2015-2021 dengan model regresi panel terboboti geografis Kurnia, Hafsah; Fauziah, Irma; Wijaya, Madona Yunita
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 2 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i2.39392

Abstract

Poverty is a major concern of the Indonesian government and the government's efforts to reduce poverty are a national development priority. Therefore, it is interesting to identify the factors that influence poverty in Indonesia. Considering a spatial perspective, Geographically Weighted Panel Regression (GWPR) method is applied to the panel data set of 34 Indonesia provinces over the period 2016-2021. The best fitted model is found when using the adaptive kernel weighting function with poverty rate, length of schooling, provincial minimum wave, human development index, literacy rate, and unemployment rate as the predictor variables. The result suggests that provinces in Indonesia can be divided into seven groups based on significant predictors on poverty rate. The fixed effect GWPR model is the final model selected for the data which can explain about 75.64% of the variability in poverty rate in Indonesia. Keywords: Fixed effect model, Geographically Weighted Panel Regression, Adaptive kernel. MSC2020: 62P25.
Peramalan dan dekomposisi untuk mata uang kripto dengan model facebook prophet Rahman, Dany; Rachmatin, Dewi; Marwati, Rini
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 1 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i1.39159

Abstract

Cryptocurrencies are becoming one of the hottest topics in Indonesia's society. One of those issues concerns investors who incur financial losses as a result of investing in crypto. The facebook Prophet model, one of the forecast models, can offer a solution to this problem. The Prophet model is built using four function. These variables are trend, seasonality, holidays, and additional regressions. The Prophet model benefits from a number of advantages, one of which is its ability to generate decomposition graphs. The decomposition may give analysts more insight into the data they are analyzing. The Prophet model is used to forecast and decompose the price of a cryptocurrenciy called Solana in this study. A multiplicative model with linear function as trend function, weekly seasonality, and daily seasonality as seasonality function is the best model for Solana price forecasting and decomposition. Additionally, hyperparameters in the model are tuned so the model won’t suffer underfitting or overfitting indications. The fitted Prophet model is good at forecasting as a result of the evaluation process. As a result of the forecast and decomposition, the forecasted value and the decomposition graph of the Solana exchange rate for one hour later show that the price of Solana will remain constant. Keywords: Cryptocurrency, time series, forecasting, decomposition, facebook prophetMSC2020: 62M10
Hubungan antara latis distributif dan aljabar median Dahoklory, Novita; Patty, Henry Willyam Michel
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 2 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i2.45887

Abstract

Let M be a non-empty set equipped by a ternary operation m:M×M×M→M. The set M is called a median algebra if (M,m) satisfies these properties (1) majority: m(a,a,b)=a, associativity: m(a,b,m(c,b,d) = m(m(a,b,c),b,d), and commutativity: m(a,b,c) = m(a,c,b) = m(b,a,c) for every a,b,c,d∈M. In this paper, we will relate a median algebra and a distributive lattice; every distributive lattice is a median algebra. Moreover, we will study an interval [a,b] in a median algebra (M,m) motivated by closed intervals in R. We will also investigate the basic properties of the interval [a,b] in a median algebra. Furthermore, using these properties, we will show that every interval in a median algebra is conversely a distributive lattice. Keywords: median algebra, distributive lattices, interval.MSC2020: 06D99.
Penyelesaian khusus persamaan diferensial biasa ordo dua linier tak homogen dengan koefisien konstan untuk fungsi bagian demi bagian Gunawan, Gani
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 1 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i1.38240

Abstract

Spring mechanical vibration motion system with a damped degree of freedom and influenced by external forces, is mathematically expressed as an ordinary differential equation of order of two linear constant coefficients that are not homogeneous. If an external force acts on a stationary system expressed as a continuous function f(t) for any time t, then the system will experience mechanical vibrational motion which mathematically the equation of motion can be expressed as a superposition. The equation consists of as a solution to a homogeneous form with mechanical vibrations as a solution to a particular form. In terms of the particular solution this article will show a mathematical way when f(t) is a continuous function section by part which is defined at an interval, such that the mechanical vibration motion equation is at the same time a special solution of the equation the mechanical vibration system. Keywords: Vibration, Impulse Functions, ConvolutionMSC2020: 34A37
Penerapan geographically weighted regression (GWR) dalam menganalisis kemiskinan di Pulau Jawa tahun 2022 Novaldi, Jeremia; Pusponegoro, Novi Hidayat
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 1 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i1.42717

Abstract

Poverty is a priority issue for Indonesia. However, efforts to eradicate poverty in Indonesia have always failed to fulfill the targets set out in the RPJMN. Java Island, which is known as the center of the economy, has not yet solved this poverty problem. In 2022, the majority of provinces on Java Island still have a higher poverty rate than the target in the 2020-2024 RPJMN, which is 6.5-7 percent. Therefore, the objective of this study is to analyze the relationship between the socio-economic conditions of the society, represented by aspects of education, health, and income, and poverty in 119 regencies or cities on Java Island. Geographically weighted regression (GWR) with a fixed bi-square kernel is applied to fulfill the study objective. The results showed that poverty is affected by RLS in 84 districts/cities, influenced by AHH in 15 regencies or cities, and influenced by AHH and income per capita in 8 regencies or cities. However, these three variables do not affect the poverty rate in the 12 regencies or cities. Keywords: Poverty, GWR, Spatial Analysis, SocioeconomicMSC2020: 91B72
Optimizing banana production in aroma Lumajang business using goal programming method and sensitivity analysis Bramastary, Aurelly Meidy; Kharis, Selly Anastassia Amellia
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 2 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i2.46732

Abstract

Lumajang regency, located in the East Java Province, Indonesia, is renowned for its extensive banana cultivation. Aroma Business, situated in Kalibendo Village, Pasirian District, Lumajang Regency, specializes in banana processing. The company faces challenges including suboptimal production levels, underutilization of resources, raw material shortages, and escalating production costs. These issues contribute to financial instability and unmet market demand. This study aims to establish optimal production planning strategies to address these critical challenges. The research employs the Goal Programming method, which is selected for its suitability in addressing multi-objective problems. Optimization of production is essential for achieving desirable outcomes, ensuring both quantity and quality of products. Research conducted with the aid of LINDO software reveals that production costs can be reduced from IDR 6,647,400 to IDR 6,417,000. Additionally, raw material availability can be increased by 1,512 pieces and the production of banana stem chips can be increased from 240 pieces to 372 pieces, resulting in an increase in company profits from IDR 10,506,000 to IDR 11,727,000. Sensitivity analysis indicates that variations in the right-hand side ranges value do not impact the obtained optimal results. Keywords: Banana production, goal programming, optimization, sensitivity analysis, LINDO software. MSC2020: 90B30.
Regularisasi model pembelajaran mesin dengan regresi terpenalti pada data yang mengandung multikolinearitas (Studi kasus prediksi Indeks Pembangunan Manusia di 34 provinsi di Indonesia) Khamidah, Nur; Sadik, Kusman; M Soleh, Agus; Dito, Gerry Alfa
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 1 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i1.40360

Abstract

This research intends to model high-dimensional data that contains multicollinearity in four machine-learning algorithms: Random Forest, K-Nearest Neighbor, XGBoost, and Regression Tree. Previously, regularization was carried out with penalized ridge regression, least absolute shrinkage and selection operator (LASSO) regression, and Elastic Net regression. A total of 100 predictor variables and 1 response variable which are the Development Index 2022 data of 34 provinces in Indonesia from BPS were used and standardized. The simulation is also applied to highly correlated data on two distributions, uniform and normal with parameter values taken from existing empirical data. The results showed that the ridge regularization method is the best for producing accurate and stable predictions. Furthermore, there was no difference in the root mean square error (RMSE) results between the data with standardization and without standardization, wherein all the data analyzed it was found that the kNN model was better than other models on simulation data, and the Random Forest and XGBoost models were better than other models on empirical data. In addition, the Regression Tree model is not recommended according to the results of this study. Keywords: regularization, multicollinearity, ridge, LASSO, elastic netMSC2020: 62J07
Indeks Padmakar-Ivan dan indeks Randic pada graf non-koprima dari grup bilangan bulat modulo Ghoffari, Lalu Hasan; Wardhana, I Gede Adhitya Wisnu; Abdurahim, Abdurahim
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 1 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i1.45367

Abstract

Graph theory, introduced by the Swiss mathematician Leonhard Euler in 1736, has played a pivotal role in solving real-world problems since its inception, notably exemplified by Euler's solution to the Konigsberg Bridge problem. Its applications extend to various domains, including scheduling, shortest path routing, and chemical structure representation. In chemistry, graphs are extensively used to depict molecular structures and chemical compounds, aiding in visualizing atomic connections and overall compound configurations. Topology indices, such as the Padmakar-Ivan (PI) and Randic indices, provide numerical values capturing chemical bonding relationships. Beyond chemical structures, these indices find applications in abstract algebraic graph representations. Recent research, exemplified by Husni et al.'s work on the harmonic and Gutman indices, explores these indices in coprime graphs of integer groups modulo prime power orders. Additionally, studies on non-coprime graphs of integer groups modulo reveal unique characteristics and invariants, shedding light on their structure. The non-coprime graph is a graph with two vertices said to be adjacent if the greatest common divisor (GCD) of their orders is not equal to one. This paper aims to investigate the topological indices, specifically the Padmakar-Ivan and Randic indices, in non-coprime graphs of integer groups modulo, adding depth to our understanding of their applicability and significance in abstract algebraic representations. Keywords: Graph theory, padmakar-ivan index, randic index, non-coprime graphsMSC2020: 05C09
Klasifikasi kepuasan mahasiswa matematika UNP terhadap kualitas pelayanan Go-Food pada Gojek dengan metode naïve Bayes Mirnawati, Mirnawati; Sari, Devni Prima
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 2 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i2.42827

Abstract

The development of Go-Food services in the surrounding community, including UNP Mathematics students, has caused various reactions, namely satisfaction and dissatisfaction with the services provided. Several factors are thought to result in Go-Food services being less than optimal based on the opinions of several experts, namely reviews of prices, payments, promotions, driver performance and suitability of specifications. Based on the results of distributing research questionnaires, there are several factors that cause students to be satisfied using Go-Food services and some are dissatisfied. The field of data mining science that will help companies to overcome this problem is classification techniques. Classification techniques in data mining will produce a classification model obtained from input in the form of training data, which has class variables. The classification model will map data object X to one of the previously defined classes Y. The classification method used is Naïve Bayes, which is defined as a combination of naïve and Bayes' theorem and produces the assumption that one independent variable is independent of each other. This research uses 44 training data and 44 test data. This classification presents the data into 50% training data and 50% testing data. The results of the classification of UNP Mathematics students' satisfaction with the quality of Go-Food services at Gojek using the naïve Bayes method obtained an accuracy of 86.3% and an APER value of 13.3%. This means that the naïve Bayes classification results are in the good classification range, which is concluded as good classification results. Keywords: Classification, go-food, service quality, naïve bayes, APER.MSC2020: 62C10
Analisis pengelompokan jumlah tanaman kehutanan yang diusahakan menurut jenis tanaman di Indonesia Octavanny, Made Ayu Dwi
Majalah Ilmiah Matematika dan Statistika Vol. 24 No. 1 (2024): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v24i1.39575

Abstract

One of the problems of archipelagic countries is the lack of maximum utilization of natural resources which has resulted in some areas being left behind. Indonesia is one of those who experience the impact of the lack of utilization of natural resources in the forestry sector. The non-optimal use of forests for planting forestry plants has made most Indonesians use their land as artificial forests, namely to plant forestry plants. Cluster analysis in this case seeks to classify provinces in Indonesia based on the type of forestry plants cultivated. The method used is hierarchical and non-hierarchical. The hierarchical method uses single linkage and complete linkage methods while the non-hierarchical method uses the K-mean method. By making comparisons between methods, the results obtained are that the single linkage method with 8 clusters is the best method for grouping provinces in Indonesia according to the types of plants cultivated. Of the 34 provinces in Indonesia, cluster 1 consists of 27 provinces, while clusters 2 to 8 each consist of only 1 province. Keywords: Cluster analysis, single linkage, complete linkage, K-mean, forest plantsMSC2020: 62H30

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