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All Journal Agrointek Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Jurnal Pengabdian Magister Pendidikan IPA EIGEN MATHEMATICS JOURNAL Variance : Journal of Statistics and Its Applications Jurnal Pengabdian Masyarakat Sains Indonesia (Indonesian Journal Of Science Community Services) Jurnal Ilmiah Profesi Pendidikan Jurnal Abdi Insani Mandalika Mathematics and Educations Journal ESTIMASI: Journal of Statistics and Its Application Jurnal Ilmiah Abdi Mas TPB Unram Jurnal Diferensial Eksergi: Jurnal Teknik Energi Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Jurnal Pepadu Bakti Sekawan : Jurnal Pengabdian Masyarakat Semeton Mathematics Journal IJASDS: Indonesian Journal of Applied Statistics and Data Science
Zulhan Widya Baskara
Program Studi Statistika, Universitas Mataram, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Other

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Peranan Statistika di Era Transformasi Digital untuk Agen Perubahan di SMAN 1 Gunungsari Lombok Barat Zulhan Widya Baskara; Purnamasari, Nur Asmita; Mustika Hadijati; Lilik Hidayati; Desy Komalasari; Zulhan Widya Baskara; Lisa Harsyiah; Jihadil Qudsi; Helmina Andriani; Dina Eka Putri; Fara Fid
Jurnal Pengabdian Magister Pendidikan IPA Vol 8 No 1 (2025): Januari-Maret 2025
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpmpi.v8i1.10423

Abstract

The digital transformation era and technological advancements demand rapid adaptability from human resources, including the increasingly important utilization of data science across various industries. Statistics, as a core component of data science, plays a crucial role in transforming data into valuable information for decision-making. Considering the significance of statistical analysis, this skill has become one of the most sought-after in today's industrial world, especially for the younger generation, such as high school students, who will become agents of change in the future. Community service activities at SMA Negeri 1 Gunungsari, Lombok Barat, aim to enhance students understanding of the role of statistics in the digital transformation era. These activities include raising awareness about the importance of statistics in career choices and the application of statistical tools in digital contexts. Furthermore, the material delivered also covers how statistics can be used as a tool to address future industrial challenges. The evaluation of this activity shows an increase in students understanding, as evidenced by the post-test results, which show significant improvement compared to the pre-test. This demonstrates that raising awareness about statistics is effective in equipping students with relevant skills in the digital era. Therefore, similar activities are expected to be implemented in other schools to strengthen students readiness to utilize statistics as agents of change in the digital transformation era.
Perbandingan Regresi Nonparametrik Kernel dan Spline pada Pemodelan Hubungan antara Rata-Rata Lama Sekolah dan Pengeluaran per Kapita di Indonesia Zulhan Widya Baskara; Muhammad Syahrul; Humami Syifa Amanda; Indi Rizqy Fahrani; Yasmin Yasmin; Nur Asmita Purnamasari; Zulhan Widya Baskara
Indonesian Journal of Applied Statistics and Data Science Vol. 1 No. 1 (2024): November
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v1i1.5725

Abstract

Poverty remains a major issue in developing countries, including Indonesia. In 2021, Indonesia’s poverty rate reached 10.14%, or approximately 27.5 million people (BPS). Poverty alleviation is a primary goal within the Sustainable Development Goals (SDGs). Two important indicators for measuring poverty are per capita expenditure and average years of schooling, which can aid in formulating policies to reduce poverty. This study analyzes the relationship between average years of schooling and per capita expenditure in 2023 using nonparametric regression methods, specifically kernel and spline regression. The kernel regression analysis yielded an optimal bandwidth of 0.860 and a minimum GCV of 0.574. However, the truncated spline method, with one optimal knot, a minimum GCV of 0.5263514 at the 3rd order, and the smallest MSE of 0.4097892, proved to be more accurate in describing the relationship between the two variables. The study concludes that the truncated spline method is superior in modeling the relationship between per capita expenditure and average years of schooling, providing valuable insights for policy formulation aimed at poverty alleviation in Indonesia.
Perbandingan Peramalan Jumlah Produksi Air Bersih PT. Air Minum Giri Menang dengan Metode Double Exponential Smoothing dari Holt dan Brown menggunakan Optimasi Algoritma Kuadratik Zulhan Widya Baskara; Era Pazira; Zulhan Widya Baskara; Qurratul Aini
Indonesian Journal of Applied Statistics and Data Science Vol. 1 No. 1 (2024): November
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v1i1.5793

Abstract

Regional Water Supply Companies (PDAM) play a crucial role in ensuring the availability of clean and consumable water. This study aims to compare the Double Exponential Smoothing (DES) methods—Brown’s one-parameter and Holt’s two-parameter—for forecasting the clean water production of PT. Air Minum Giri Menang (Perseroda), emphasizing parameter optimization using a quadratic algorithm. The algorithm efficiently determines the optimal smoothing parameters to minimize forecasting errors measured by the Mean Absolute Percentage Error (MAPE). The results indicate that Brown’s DES method, with a MAPE of 3.29%, outperforms Holt’s DES method, which has a MAPE of 3.96%. While both methods are highly accurate for forecasting (MAPE ≤ 10%), the quadratic algorithm optimization makes Brown’s DES method the preferred choice for planning clean water production for the January–June 2023 period.
Faktor-Faktor yang Memengaruhi Minat Belanja Mahasiswa Kota Mataram pada Live Produk di Tiktok dan Shopee Zulhan Widya Baskara; Syifa Salsabila Satya Graha; Nisa Ul Istiqomah; Ika Wulandari; Ismi Asmawati; Zulhan Widya Baskara; Dina Eka Putri
Indonesian Journal of Applied Statistics and Data Science Vol. 2 No. 1 (2025): Mei
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v2i1.6913

Abstract

The development of live shopping on the Shopee and TikTok platforms has changed consumer shopping behavior, including students in Mataram City. This study has two main objectives. The first objective is to identify eight independent variables that influence college students' shopping interest when Live shopping on the two platforms, which are analyzed using multiple linear regression. The second objective was to examine the relationship between shopping decisions and shopping interest using correlation analysis, which focused specifically on these two variables due to their significant relationship in the context of consumer action. Data was collected through a questionnaire that was tested for validity and reliability, with a Cronbach's Alpha value of 0.95 which indicates a high level of consistency. The results of the classical assumption test show that the model meets the assumption of multicollinearity, but does not meet the assumptions of normality and homogeneity. Multiple linear regression shows an R value of 0.75, which indicates a strong relationship between the independent variables and the shopping interest of respondents. Substantial factors that influence shopping interest include interaction and engagement, product quality and variety, and shopping satisfaction when Live. Meanwhile, price, influencer participation, time constraints, gender, and platform did not show a substantial influence.
Analisis Minat Pemilih Mahasiswa Gen Z di Universitas Mataram Terhadap Pemilihan Gubernur Di NTB Tahun 2024 Zulhan Widya Baskara; Amini, Elsa; Fauzi, Meilinda; Ramdhani, Triana Putri; Ulfaturrahmi, Ulfaturrahmi; Putri, Dina Eka; Baskara, Zulhan Widya
Semeton Mathematics Journal Vol 2 No 1 (2025): April
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i1.295

Abstract

This study aims to analyze the determinants of voting behavior among Generation Z students in the context of the 2024 Gubernatorial Election in West Nusa Tenggara (NTB), Indonesia. Utilizing a quantitative approach, the research applies multiple linear regression to examine the influence of sociological, psychological, and rational factors on voting behavior. Primary data were collected through an online questionnaire distributed to 97 purposively selected active students at the University of Mataram. The instrument employed a 4-point Likert scale to minimize neutral responses. The findings reveal that psychological and rational factors significantly influence voting behavior, whereas sociological factors do not show a statistically significant effect. The regression model yielded an Adjusted R² value of 0.549, indicating that the three independent variables explain 54.9% of the variance in voting behavior.
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.
The Newton Model for Seaweed Drying: An Investigation of a Cabinet Dryer Using Biomass Energy Zulhan Widya Baskara; Apriandi, Nanang; Herlambang, Yusuf Dewantoro; Khoryanton, Ampala; Safarudin, Yanuar Mahfudz; Widya Baskara, Zulhan; Raharjanti, Rani
Eksergi Vol. 19 No. 01 (2023): JANUARY 2023
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/eksergi.v19i01.4211

Abstract

This study investigates the viability of employing a cabinet-type dryer with a heat energy source derived from biomass combustion to dry Eucheuma sp. using Newton's model. In this investigation, seaweed was dried with air at a temperature of 55 °C. A reduction in water content of 8.1% was attained after six hours of drying. To make the data fit the suggested drying mathematical model, the data were examined and recorded. The model feasibility test shows that, with a coefficient of determination (R2) that is close to one and corrected at 0.9502, the Newton model can be used to predict the moisture content of dried seaweed after the drying process using a cabinet-type dryer with a source of heat energy from biomass combustion.
Klasifikasi Status Penerima Bantuan Program Keluarga Harapan di Provinsi NTB Menggunakan Metode Regresi Probit Zulhan Widya Baskara; Harsyiah, Lisa; Widya Baskara, Zulhan; Eka Putri, Dina; Jurniati, Jurniati
Mandalika Mathematics and Educations Journal Vol 7 No 3 (2025): Edisi September
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i3.9776

Abstract

The Indonesian government's effort to accelerate the achievement of comprehensive social welfare involves adopting strategic policies in the form of distributing social assistance to economically vulnerable communities. One concrete example of this policy is the Family Hope Program (Program Keluarga Harapan/PKH). However, its implementation in the field still faces challenges, particularly in the form of unequal distribution, which has the potential to hinder the program’s effectiveness. To address this issue, a rigorous verification system is required to ensure that prospective beneficiaries truly meet the official criteria set by the government. Therefore, classifying households eligible for PKH is a crucial step. The probit regression approach is employed as a method to analyze and determine the household eligibility status. This method yields an accuracy rate of 76.25%, which is considered valid and reliable based on the Press’s Q statistic
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.
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