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INDONESIA
EIGEN MATHEMATICS JOURNAL
Published by Universitas Mataram
ISSN : 26153599     EISSN : 26153270     DOI : -
Core Subject : Education,
Mathematics
Eigen Mathematics Journal mempublikasikan artikel yang berkontribusi pada informasi baru atau pengetahuan baru terkait Matematika, Statistika, dan Aplikasinya. Selain itu, jurnal ini juga mempublikasikan artikel berbentuk survey dalam rangka memperkenalkan perkembangan terbaru dan memotivasi penelitian selanjutnya dalam bidang matematika, statistika, dan aplikasinya.
Arjuna Subject : -
Articles 118 Documents
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Determination of The Best Koperasi Using SAW (Simple Additive Weighting) Ines Saraswati Machfiroh; Widiya Astuti Alam Sur; Jaka Permadi; Winda Aprianti; Herfia Rhomadhona
Eigen Mathematics Journal Vol. 6 No. 1 Juni 2023
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v6i1.158

Abstract

Office of Koperasi, UKM, and Trade of Tanah Laut Regency, South Kalimantan conducts the health of Koperasi by manually checking the financial report data of each Koperasi. This study aims to determine the best Koperasi performance using a decision-making system with the Simple Additive Weighting (SAW) method. Performance evaluation is based on the criteria in the Technical Instructions for the Deputy for Koperasi Number 15 of 2021 concerning Guidelines for Working Papers on Cooperative Health Examination. The criteria to determine the best Koperasi performance were based on the attributes of the governance, risk profile, financial performance, and capital of Koperasi. The SAW method was used to select the best Koperasi by adding up each attribute, then multiplying by the weight of the related attributes. Based on the calculations using the SAW method, Koperasi 33 was selected, with the highest Vector value (V(i)) of 0.944719. Koperasi 33 can be categorized as the best of 100 Koperasi in Tanah Laut Regency, South Kalimantan.
Modifikasi Algoritma Edmonds Karp untuk Menentukan Aliran Maksimum Pada Jaringan Distribusi Air PDAM (Studi Kasus Jaringan Telaga Sari PDAM Giri Menang Mataram) Hotimah, Husnul; Bahri, Syamsul; Awalushaumi, Lailia
Eigen Mathematics Journal Vol 6 No 2 (2023): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v6i2.134

Abstract

Clean water is the main and basic need for humans which is of concern to the government. Distribution network system is a very important part to delivering water to all consumers. The lack of water discharge distribution in several areas, especially at the end of the pipeline service, is cause by not optimal water distribution, the flow rate of sorce and leak in pipeline effect. This research has to analyze the optimal network model and determine the maximum flow rate from the PDAM pipeline using modified Edmonds Karp algorithm. Modified Edmonds Karp algorithm is a method for calculating maximum flow of a network. Based on analysis of modified Edmonds Karp algorithm there is a less efficient us of pipe in PDAM network and result of maximum flow from the network is 202,30 liter/second. This means it can be adding flow discharge to the water distribution pipe by PDAM for expedite the flow to consumer with the addition of flow should not exceed 202,30 liter/second.
Co-Existing Point of Equilibrium in Discretization of Fractional-Order Prey and Predator Model Rio Satriyantara; Dara Puspita Anggraeni; Irma Risvana Dewi; Alfian Eka Utama
Eigen Mathematics Journal Vol. 6 No. 1 Juni 2023
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v6i1.169

Abstract

In this work, a discretization process of a fractional-order prey and predator model is discussed. The aim of this work is to describe the population phenomenon which contains prey and predator. In this research, the prey and predator model by Ghosh et al. (2017) is used. The model has an unique form because it contains prey refuge and additional food to predator. In order to give more details on prey and predator population, the model then modified into fractional order and then discretized. The discretization model has three points of equilibrium and one of them named co-existing point of equilibrium. The numerical simulation is used to perform the stability. The numerical simulation is controlled by using mathematical programming language. It resulted that the co-existing point of equilibrium tends to be stable or converge if a small value of  (time step) is selected. Otherwise, if a larger value of  is selected, then oscillatory is appeared which means the point of equilibrium become unstable or diverge.
Model Regresi Cox Untuk Data Masa Studi (Studi Kasus: Data Masa Studi Mahasiswa Fakultas Teknik Universitas Bangka Belitung) Sulistiana, Ineu; Kustiawan, Elyas; Amelia, Ririn
Eigen Mathematics Journal Vol 6 No 2 (2023): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v6i2.170

Abstract

Student study time is the time needed by students to complete their education, which starts from the time they enter college until they are declared graduated or have completed their study period. In the study period data, survival time observations were only carried out partially or not until the failure event. In other words, termination occurs until the observation deadline. This termination occurred due to several factors that allegedly influenced the student's study period. This study intends to determine what variables influence the study period of students of the Faculty of Engineering, University of Bangka Belitung through survival analysis. Using study period data for students of the Faculty of Engineering, University of Bangka Belitung, class of 2015/2016, this study used the Kaplan Meier Estimation to see the survival function of each factor causing the length of the study period graphically and the Log Rank Test statistically. Meanwhile, to look at the factors that determine the length of a student's study period, researchers used the Cox Regression and Maximum Likelihood Estimation (MLE) models to find the best model. The results of the data analysis show that there are differences in the survival function in each category for all variables graphically, while the statistical comparison of the results of the estimation of the survival function curve based on gender and organizational status is not significantly different. The results of the analysis also show that the proportional hazard assumption is fulfilled through the cumulative hazard log so that categorical variables can be used in the Cox Regression model. Based on the results of the likelihood estimation, the variables that have a significant effect on the study period of Engineering Faculty students are majors and GPA variables. Furthermore, from the interpretation of the model parameters, it is obtained that the Hazard Ratio (HR) value for the study period of Mechanical, Mining and Electrical Engineering students is faster than that of Civil Engineering students, while students with GPA ≥ 3.00 have a shorter study period than students with GPA < 3.00.
Forecasting Non-Metal and Rock Mineral (MBLB) Tax Revenue Using the Fuzzy Time Series Markov Chain Method in East Lombok Regency Zulhan Widya Baskara; Zohrah, Baiq Siti Patimah; Bahri, Syamsul; Baskara, Zulhan Widya
Eigen Mathematics Journal Vol 7 No 1 (2024): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i1.171

Abstract

Indonesia is one of the countries that is included in a developing countries. Therefore, the Indonesian Goverment is trying to carry out various developments in various regions. Regional development is one of the Indonesian government’s ways of achieving national goals. In carrying out regional development, of course funds are needed as the main source to support the achievement of national development. The main source of funds obtained by the Government comes from Regional Oroginal Income. One source of Regional Oroginal Income is tax. There are various types of taxes managed by the government in East Lombok Regency. One of them is the Non-Metal Minerals and Rocks, which is a tax on the extraction of non-metallic minerals and rock Tax, which is a tax on the extraction of of non-metallic minerals and rocks from natural sources within or on the surface of the earth for use. This Non-Metal and Rock Mineral tax provides quite large revenues for East Lombok district regional taxes. Non-Metal and Rock Mineral tax income is often not constant, meaning that there is an increases and there is a decreases in the amount of income. For this reason, it is necessary to forecast Non-Metal and Rock Mineral tax revenue to predict income in the future. The method used in this study is the FTS Markov Chain order 1 and order 2. Based on the MAPE indicator, the results of forecasting using the FTS Markov Chain method of order 1 amounted to Rp. 1.117.069.497 with an accuracy of 48,55% with a just good forecasting classification. While the results of forecasting using the FTS Markov Chain method of order 2 amounted to Rp.1.761.652.173 with an accuracy of 39,12% with a just good forecasting classification. If seen from the MAPE value obtained, the forecasting results using the 2nd order FTS Markov Chain are more accurate than using the 1st order Markov Chain FTS method.
Modelling the Recovery of Malaria Patients in West Lombok District Using Cox Regression Usman, Siti Dwi Khairun Rahmatin; Hadijati, Mustika; Fitriyani, Nurul
Eigen Mathematics Journal Vol 6 No 2 (2023): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v6i2.173

Abstract

Malaria is one of the health problems in West Lombok Regency. There are 413 positive malaria cases, so it is necessary to research the models and factors affecting malaria sufferers' recovery. The analysis used is survival analysis using the Cox Proportional Hazard Regression method. The data used in this study is in the form of secondary data obtained from medical record data from all patients with malaria disease in West Lombok Regency from 2019 to 2020, with dependent variables in the form of recovery time of malaria patients and nine independent variables that are suspected of affecting the recovery of malaria sufferers. This study aims to determine a recovery model for malaria sufferers based on Cox regression and determine the factors that influence the recovery of malaria sufferers in West Lombok Regency. Based on the survival analysis results with the Cox Proportional hazard Regression method, the best model was obtained with two significant variables affecting the recovery time of malaria patients: the parasite type variable and the incidence of pregnancy or not getting pregnant. The model can be interpreted based on hazard ratio values that the variable type of parasite category Plasmodium vivax has a probability of being able to recover within one month of treatment by 2,542 times faster than Plasmodium falciparum. In comparison, the type of parasite in the Plasmodium mix category has a probability of being able to recover within one month of treatment 1.108 times faster than Plasmodium vivax,  and for the pregnant or non-pregnant variables for the category of pregnant patients had a 2,307 times faster probability of recovery within one month of treatment compared to non-pregnant patients.
The ARIMA-GARCH Method in Case Study Forecasting the Daily Stock Price Index of PT. Jasa Marga (Persero) Amri, Ihsan Fathoni; Wulan Sari; Widyasari, Velia Arni; Nurohmah, Nufita; Haris, M. Al
Eigen Mathematics Journal Vol 7 No 1 (2024): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i1.174

Abstract

PT Jasa Marga is a large company in Indonesia that develop and operation the toll roads and is known as one of the blue chip companies with LQ45 shares. However, share prices have high volatility or rise and fall quickly so their value is always changing. Therefore, forecasting is needed to predict the share price of PT Jasa Marga in the future in order to know the movement of its share price. The Autoregressive Integrated Moving Average (ARIMA) method is a method that can predict data with high volatility, but has the disadvantage of residuals containing heteroscedasticity. So, the addition of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model was carried out to overcome the heteroscedasticity problem that was initially caused by the ARIMA model so it could predict data with high volatility more optimally. Therefore, this research applies the ARIMA-GARCH method to find the best model for forecasting the daily share price index of PT Jasa Marga. The data used comes from the daily closing stock price index of PT Jasa Marga (Persero) for the period January 2015 to May 2023. The measurement of forecasting accuracy uses the Mean Absolute Percentage Error (MAPE). The forecasting results show that the best model uses ARIMA (2,1,1) - GARCH (1,3) with a MAPE value of 6.825728%, which indicates very good forecasting results because the MAPE value is <10%.
Comparison Analysis of Clustering Methods for Clustering of Indonesian’s Gender Empowerment Conditions in 2022 Nur Rahmah, Aisyah 'Azizah; Wijayanto, Arie Wahyu
Eigen Mathematics Journal Vol 6 No 2 (2023): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v6i2.176

Abstract

Gender empowerment is one of the components of gender development achievement measures that is an important agenda at the global level in realizing the Sustainable Development Goals. The Gender Empowerment Index (GEI) of Indonesia has been continuously improving since 2010, indicating an increasing involvement of women in various areas of life. However, behind this upward trend in GEI, there is still inequality at the provincial level. Therefore, there is a need to formulate development strategies, one of which is gender-based. One possible step is to categorize regions in Indonesia based on their gender empowerment characteristics so that government interventions can be targeted effectively. This research utilizes two clustering approaches, namely Hierarchical Methods and Partitioning Methods, with data consisting of three variables representing the components of GEI for 34 provinces in Indonesia in 2022. The selection of the best method and number of clusters is based on internal and stability validity, followed by the determination of the smallest within and between standard deviation ratios. From the cluster analysis results, the best method is found to be K-means with a total of 5 clusters.
Pemodelan Tingkat Pengangguran Terbuka di Indonesia Menggunakan Analisis Regresi Data Panel Setiawana, Ena; Fitriyani, Nurul; Harsyiah, Lisa
Eigen Mathematics Journal Vol 7 No 1 (2024): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i1.184

Abstract

Indonesia has entered the peak of the demographic bonus which can provide positive and negative impacts for various fields. One of them is in the economic field, namely the increasing number of productive population who are unabsorbed in the world of work and is referred to as an open unemployment. This research was conducted to build a model and to analyze the Open Unemployment Rate, Economic Growth, Provincial Minimum Wage, Level of education, Population growth, Labor Force Participation Rate, Employment, Human Development Index, Poor Residents, Illiterate Population, Average Length of School, Domestic Investment, Foreign Investment, and School Participation Rate, that influence the open unemployment rate in Indonesia using panel data regression analysis with data 2015-2021 from 34 provinces. A fixed effect model with different intercept values for every participant is the best panel data regression model (Fixed Effect Model) that could be found. Based on simultaneously research, it was discovered that every component of the model significantly effect the open unemployment rate. Partially, it was discovered that the following factors significantly effect the open unemployment rate in Indonesia: Employment, Labor Force Participation Rate, Economic Growth, Population Growth, Human Development Index, Poor Population, and Average years of Schooling.
Nowcasting of Indonesia's Gross Domestic Product Using Mixed Sampling Data Regression and Google Trends Data Yuliana, Niken; Ramadanty, Shashella Zelicha; Syifa, Umu Arifatul; Kartiasih, Fitri
Eigen Mathematics Journal Vol 7 No 2 (2024): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i2.187

Abstract

This study aims to compare the results of the GDP nowcasting of the accommodation and food service activities sector without and with the pandemic time using the MIDAS method. The MIDAS method is an econometric approach used to predict economic development using real-time available high-level and low-frequency data. In this study, Google Trend acts as a predictor variable consisting of 16 search categories which are then reduced by Principal Component Analysis, resulting in several principal components. For GDP data, the data period collected is Quarter I 2010 to Quarter I 2023. This period will later be partitioned into the period before the COVID-19 pandemic, namely Quarter I 2010 to Quarter IV 2019 and a combined period, namely Quarter I 2010 to Quarter I of 2023. This partition was carried out to see the performance and sensitivity of the model before and after the shock due to the COVID-19 pandemic. From the models that have been made, nowcasting is carried out and it is found that the RMSE and MAE values for the pre-pandemic model are smaller than the combined model. The RMSE values for each of the pre-pandemic and combined models were 0.005753 and 0.056032 and the MAE values were 0.00359 and 0.048976 for the pre-pandemic and combined models. However, from this study it is not advisable to make predictions on the nominal GDP of the accommodation and food service activities sector because the results of the nowcasting predictions are still far from the actual value, but can be a reference if you want to predict the growth direction of the accommodation and food service activities sector.

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