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Journal : EIGEN MATHEMATICS JOURNAL

Analisis Faktor Untuk Pemetaan Karakteristik pada Percobaan Dekafeinasi Kopi Robusta Zulhan Widya Baskara; Zulhan Widya Baskara; Lisa Harsyiah; Dewa Nyoman Adi Paramartha; Qabul Dinanta Utama
Eigen Mathematics Journal Vol. 5 No. 1 Juni 2022
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v5i1.139

Abstract

In recent years, there has been a positive trend in coffee consumption in Indonesia. Coffee that was initially identical to older man's drinks is starting to be liked by teenagers and children because coffee contains caffeine which can have an addictive effect. Coffee has various benefits, such as preventing drowsiness, antioxidants, improving brain performance, and reducing fatigue. However, drinking a lot of coffee than your body can tolerate will cause symptoms of insomnia, excessive anxiety, and increased blood pressure. Various experiments have been made to reduce the caffeine content in coffee (decaffeination), one of which is mixing coffee with chayote juice (Sechium edule). Furthermore, this article classified the characteristics of decaffeinated products, caffeine content, moisture content, total acid titration, ash content, hue color, and L value. Using factor analysis, it is known that the characteristics can be mapped into three principal components. The first principal component consists of variables of caffeine content, water content, and hue color value. The second principal component consists of ash content and total acid content titration variables, and the third principal component, this factor, consists only of the characteristic L. It is also known that these three main components can explain 74.2% of the diversity of origin.
Analysis of Factors that Influence Poverty in West Nusa Tenggara Using Principal Component Regression Zulhan Widya Baskara; Harsyiah, Lisa; Baskara, Zulhan Widya; Putri, Dina Eka; Fadhilah, Rifdah
Eigen Mathematics Journal Vol 8 No 1 (2025): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i1.229

Abstract

West Nusa Tenggara (NTB) is one of the provinces in Indonesia with a percentage of poor people according to the March-September period in 2019, namely 14.56% -13.88%, while in 2020 it was 13.97% -14.23% and in 2021 the percentage was 14.14% -13.83%. The factors suspected of influencing poverty in each province have different conditions each year, so repeated observations are needed on poverty data and the factors that influence it. If the data contains multicollinearity, then one of the classic assumptions of multiple linear regression is not met so that the problem of multicollinearity needs to be addressed. The Principal Component Regression (PCR) method is the most consistent compared to the ridge and least square regression methods in solving multicollinearity problems. This study aims to analyze poverty in NTB using the PCR method. The data used in this study are the number of poor people and factors influencing poverty based on districts in NTB in 2020-2022. Based on the calculation results, it was obtained that Component 1 with an eigenvalue of 4.008 explained 57.2% of the variance, while Component 2 with an eigenvalue of 1.740 explained 82.1% of the variance. Both components significantly affect poverty according to the results of simultaneous and partial tests. This model has an R^2 value of 0.302 or 30.2% and the remaining 69.8% is influenced by external factors (error). The R^2 value is classified as a weak category and it is recommended to add other factors that affect poverty including access to electricity, access to sanitation, access to clean drinking water, and government spending.
Integrative Bioinformatics and Statistical Approaches for Identifying Prognostic Biomarkers and Therapeutic Targets in Breast Cancer Zulhan Widya Baskara; Anuraga, Gangga; Anurogo, Dito; Fitriani, Fenny; Rochmanto, Hani Brilianti; Baskara, Zulhan Widya
Eigen Mathematics Journal Vol 8 No 1 (2025): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i1.277

Abstract

Breast cancer is a leading cause of cancer-related mortality worldwide, necessitating the identification of reliable biomarkers for prognosis and targeted therapy. This study employed an integrative bioinformatics and statistical approach to analyze differentially expressed genes (DEGs) in breast cancer using datasets GSE70947 and GSE22820 from the gene expression omnibus (GEO). A protein-protein interaction (PPI) network was constructed to identify hub genes, followed by functional enrichment analysis to determine their biological significance. Survival analysis using the KMplot database revealed that CDC45, KIF2C, CCNB1, KIF4A, CENPE, CHEK1, KIF15, AURKB, NCAPG, and HJURP were significantly associated with poor prognosis. These genes were primarily enriched in cell cycle regulation, mitotic spindle organization, and DNA damage response, highlighting their role in tumor progression. Among them, CCNB1, CHEK1, and AURKB were strongly linked to cell cycle progression and checkpoint regulation, while KIF2C and CENPE played essential roles in mitotic division. High expression levels of these genes correlated with reduced overall survival, suggesting their potential as prognostic biomarkers and therapeutic targets in breast cancer.These discoveries help us better understand how breast cancer develops and point to potential targets for tailored treatments.
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.
Modeling of Economic Growth Rate in West Nusa Tenggara Province with Longitudinal Kernel Nonparametric Regression Zulhan Widya Baskara; Rizaldi, Muhammad; Fitriyani, Nurul; 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.v7i1.188

Abstract

Economic growth can indicate the success of economic development in people's lives, so it is essential to study the relationship between economic growth and factors that affect economic growth. Regression analysis is one of the most widely used statistical data analysis methods to determine the relationship pattern between the independent and dependent variables. Three methods can be used to estimate the regression curve, one of which is nonparametric regression. Economic growth data is one form of longitudinal data, with observations of independent subjects, with each subject being observed repeatedly over different periods. Kernel nonparametric regression model applications can be used for longitudinal data. This research aims to estimate the curve and get the best regression model. In this research, the smoothing technique chosen to estimate the nonparametric regression model for longitudinal data is the kernel triangle estimator, which can be obtained by minimizing the square of error using Weighted Least Squares (WLS) and selecting the optimum bandwidth using the Generalized Cross Validation (GCV) method. This study uses the economic growth rate in West Nusa Tenggara as the dependent variable and the human development index, population density, general allocation funds, local revenue, and labor force participation as independent variables. The result showed that the model is less accurate because of the low value of the coefficient for determination and the high value of the mean absolute percentage error (MAPE). This can be caused by the selection of bandwidth intervals that are too small.
Co-Authors Abdul Muiz Abdurahim, Abdurahim Aisya, Hakiki Latifa Amanda, Humami Syifa Amini, Elsa Angriani, Baiq Milla Anindita SHM Kusuma Apriliana, Baiq Nurul Arbyati, Asri Mustika Asih Priyati Asmawati, Ismi Choirunnisa, Fajarani Desy Komalasari Dewa Nyoman Adi Paramartha Dina Eka Putri Dina Eka Putri Dina Eka Putri Dito Anurogo, Dito Dwi Putra, Guyup Mahardian Eka Putri, Dina Era Pazira Fadhilah, Rifdah Fahrani, Indi Rizqy Fara Fid Fauzi, Meilinda Fitriani, Fenny Gangga Anuraga Graha, Syifa Salsabila Satya Hadijati, Mustika Halifatunnisa, Nur Hani Brilianti Rochmanto Harsyiah, Lisa Helmina Andriani Hidayat, Agriananta Fahmi Hidayatullah, Azka Farris Humami Syifa Amanda Ika Wulandari Ika Wulandari Indi Rizqy Fahrani Ismi Asmawati Istiqomah, Nisa Ul Jurnal Pepadu Jurniati, Jurniati Khairun Nisa Khoryanton, Ampala Kurniawan, Hary Lailia Awalushaumi, Lailia Lilik Hidayati, Lilik Maharani, Andika Ellena Saufika Hakim Marwan Marwan Muhamad Ikhsan Febriyanto Mbele Muhammad Rijal Alfian Muhammad Syahrul Musfita, Nurul Mustika Hadijati Nanang Apriandi Nisa Ul Istiqomah Nur Asmita Purnamasari Nurul Fitriyani Nurul Fitriyani Nurwahyuni Indah Nurwahyuni Pazira, Era PURNAMASARI, NUR ASMITA Putri, Devi Karina Qabul Dinanta Utama Qudsi, Jihadil Qurratul Aini Qurratul Aini Ramadhan, Hikmal Maulana Ramdhani, Triana Putri Rani Raharjanti Rio Satriyantara Rizaldi, Muhammad Rizka Okta Dini Robbaniyyah, Nuzla Af'idatur Robbaniyyah, Nuzla Af’idatur Rucitra Widyasari Rucitra Widyasari Salwa Salwa Sari, Kurnia Mahraini Kartika Sirajuddin Haji Abdullah Surya Abdul Muttalib, Surya Abdul Suryatin, Evatia syahrul, muhammad Syamsul Bahri Syechah, Bulqis Nabula Syifa Salsabila Satya Graha Tajalli, Halawatun Tri Isti Rahayu Tri Maryono Rusadi Ulfaturrahmi, Ulfaturrahmi Wardana, I Gede Adhitya Wisnu Widhiantari, Ida Ayu Wiharyani Werdiningsih Yanuar Mahfudz Safarudin Yasmin Yasmin Yasmin Yasmin Yeni Sulastri Yusuf Dewantoro Herlambang Zohrah, Baiq Siti Patimah Zulfikar, Wahyudi