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All Journal Media Statistika Jurnal Pendidikan Sains Jurnal Inovasi Pendidikan Kimia Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Tadris Kimiya Orbital: Jurnal Pendidikan Kimia Journal of Natural Science and Integration Tarbawi : Jurnal Pendidikan Islam JURNAL EKSAKTA PENDIDIKAN (JEP) Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Pembelajaran Sains Pelita Eksakta Journal of Educational Chemistry (JEC) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Leibniz: Jurnal Matematika BIOCHEPHY: Journal of Science Education Indo-MathEdu Intellectuals Journal Journal of Mathematics UNP Arfak Chem: Chemistry Education Journal Jurnal Pendidikan, Sains dan Teknologi UNESA Journal of Chemical Education UNP Journal of Statistics and Data Science Journal of Chemistry Education and Integration Jurnal Akademika Kimia Indonesian Journal of Statistics and Its Applications Jurnal Inovasi Pendidikan Kimia JES-TM Social and Community Service
Yenni Kurniawati
Jurusan Matematika, FMIPA Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Other

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Pengelompokan Kabupaten/Kota Maluku dan Nusa Tenggara Barat Berdasarkan Faktor Kemiskinan Menggunakan Self Organizing Maps Aulia, Yuke; Sulistiowati, Dwi; Kurniawati, Yenni; Salma, Admi
Leibniz: Jurnal Matematika Vol. 5 No. 02 (2025): Leibniz: Jurnal Matematika
Publisher : Program Studi Matematika - Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/leibniz.v5i02.607

Abstract

Provinsi Maluku dan Nusa Tenggara Barat masih menghadapi tantangan serius dalam upaya pengentasan kemiskinan. Kedua provinsi ini tidak hanya mengalami peningkatan persentase penduduk miskin, tetapi juga termasuk sebagai wilayah dengan persentase penduduk miskin tertinggi di Indonesia. Persentase penduduk miskin di Provinsi Maluku pada tahun 2023 mencapai 16,42%, naik sebesar 0,45%. Sementara itu, persentase penduduk miskin di Provinsi Nusa Tenggara Barat mencapai 13,85%, naik sebesar 0,17%. Angka-angka ini masih jauh dari target pemerintah yang menetapkan 6%-7% untuk persentase kemiskinan nasional. Penelitian ini bertujuan untuk mengelompokkan kabupaten/kota di Provinsi Maluku dan Nusa Tenggara Barat berdasarkan faktor yang memengaruhi kemiskinan serta mengidentifikasi karakteristik hasil klaster yang terbentuk. Penelitian ini menggunakan metode Self Organizing Maps (SOM). Data penelitian ini bersumber dari publikasi Badan Pusat Statistik (BPS), yaitu Maluku dalam Angka 2024 dan Nusa Tenggara Barat dalam Angka 2024. Hasil analisis menunjukkan terbentuknya 3 klaster wilayah yang divalidasi menggunakan pendekatan validasi internal (Connectivity, Dunn, dan Silhouette). Klaster 1 terdiri dari 2 kota ditandai oleh keunggulan dalam indikator pendidikan, kesehatan, dan ekonomi. Klaster 2 terdiri dari 15 kabupaten/kota yang dicirikan dengan potensi tenaga kerja yang tinggi, namun mengahadapi tantangan jumlah penduduk yang besar. Sementara itu, klaster 3 terdiri dari 4 kabupaten memiliki keterbatasan dalam berbagai aspek, termasuk pendidikan, kesehatan, ekonomi, dan infrastruktur.
Process Capability Analysis of OPC Cement Production Using Statistical Process Control and IMR Method: Blaine Test Evaluation Alya Aufa, Wafiq; Yenni Kurniawati; Admi Salma; Darwas
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/379

Abstract

The main challenge in cement production at PT Semen Padang is maintaining consistent product quality, particularly the fineness of cement particles measured by the Blaine test. Variations in raw materials and the production process can cause fluctuations in quality, which affect the performance of the final product. Therefore, it is crucial to monitor and control process stability and capability to consistently meet product specifications. Based on the Statistical Process Control (SPC) analysis using Individuals and Moving Range (I-MR) control charts on 28 observations of Ordinary Portland Cement (OPC) Blaine values from February 2025, one out-of-control point was detected on the Moving Range chart between observations 16 and 17, indicating a significant variation. However, all points on the Individuals chart remained within control limits, suggesting that the individual process values were still under control. After revising the outlier data, the process was confirmed stable. Process capability analysis showed a Cp value of 2.17 and a Cpk value of 1.98, indicating that the production process is not only statistically stable but also highly capable of meeting quality specifications. Therefore, despite some variation between data points, the cement production process at PT Semen Padang can be considered stable and capable. Nevertheless, periodic evaluations are recommended to maintain consistent product quality and provide strategic recommendations for the Quality Assurance division in implementing data-driven quality control.
Comparison of Kernel and Spline Nonparametric Regression (Case Study: Food Security Index of Jambi Province 2023) Rosa Salsabila Azarine; Septrina Kiki Arisandi; Fadhilah Fitri; Yenni Kurniawati
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/397

Abstract

Food security is one of the issues that plays an important role in national development, especially in regions with varying levels of economic welfare such as Jambi Province. One of the main factors affecting food security is food expenditure, which reflects the economic capacity of households to access food. The complex and non-linear relationship between Food Security Index (FSI) and Food Expenditure requires a flexible modeling approach in the analysis. This study aims to compare the performance of nonparametric regression Kernel ans Spline regression methods, namely the Nadaraya-Watson Estimator (NWE) and Local Polynomial Estimator (LPE) for Kernel Regression as well as Smoothing Spline and B-Spline for Spline Regression. The analysis was conducted using secondary data obtained from the Food Security and Vulnerability Map (FSVA) of 2023, with a total of 141 subdistricts in Jambi Province. The response variable is the Food Security Index (FSI), while the predictor variable is Food Expenditure. Model evaluation was conducted using the Mean Squared Error (MSE) and the coefficient of determination (R²). The results showed that the NWE method had the best performance with the smallest MSE value of 24.47690 and the highest R² value of 0.3332, meaning that approximately 33.32% of the variation in FSI could be explained by Food Expenditure. The LPE method showed nearly comparable performance, while Smoothing Spline and B-Spline exhibited higher prediction error rates. Therefore, the NWE method can be recommended as an effective nonparametric regression approach for modeling the relationship between food expenditure and food security.
Applying Robust Spatial Autoregressive Model to Analyze the Determinants of Open Unemployment in West Java Berliana Nofriadi; Suci Rahmadani; Sepniza Nasywa; Tessy Octavia Mukhti; Yenni Kurniawati
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/402

Abstract

Open unemployment is a critical macroeconomic challenge in developing regions like West Java, Indonesia, where spatial disparities and data anomalies complicate traditional analysis. This study addresses these limitations by employing a Robust Spatial Autoregressive (RSAR) model with M-Estimator, integrating spatial dependence and outlier resilience to enhance estimation accuracy. Using 2024 district-level data from Indonesia’s Central Bureau of Statistics (BPS) and Open Data Jabar, the research examines determinants such as labor force participation, education, and regional GDP. The methodology begins with Ordinary Least Squares (OLS) to identify initial predictors, followed by spatial diagnostics (Moran’s I, Lagrange Multiplier tests) to confirm spatial autocorrelation. A customized Queen contiguity weight matrix captures neighborhood effects, while robust M-Estimation mitigates outlier distortions. Results reveal that the RSAR model achieves superior explanatory power (R² = 0.8626) compared to OLS and standard Spatial Autoregressive (SAR) models, with labor force participation (X₄) emerging as a significant negative predictor of unemployment. Spatial effects (ρ = 0.337) though modest, underscore the importance of inter-regional dynamics. The study concludes that RSAR offers a more reliable framework for regional labor analysis, combining spatial rigor with robustness against data irregularities. Policy-wise, the findings advocate targeted interventions to boost labor participation and address localized disparities, emphasizing the need for spatially informed, outlier-resistant methodologies in economic planning.
Factors Affecting Households Program Keluarga Harapan Recipients in West Sumatra: Binary Logistic Regression Analysis Ardhi, Sonia; Dodi Vionanda; Yenni Kurniawati; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/406

Abstract

Poverty is still a complex issues in Indonesia. Poverty rate in West Sumatra province has increased over the past 3 years. One of the government's initiatives to address poverty is the Program Keluarga Harapan (PKH), which is a social protection program that provides conditional cash transfers to poor and vulnerable Keluarga Penerima Manfaat (KPM) on condition that they are registered in the Data Terpadu Kesejahteraan Sosial (DTKS). Although PKH has a positive impact on poverty alleviation and enhanced access to health, education, and social welfare, the implementation still faces major challenges such as data inaccuracies, particularly in targeting accuracy. Therefore, an analysis is needed to determine the factors that significantly affects PKH recipient households in West Sumatra Province. This research used variables from the DTKS variable group contained in SUSENAS 2024 using two stages one phase stratified sampling method with 11,600 observations consisting of 1,790 receiving PKH and 9,810 not receiving PKH. The dependent variable is PKH recipient status (Yes = 1, no = 0). Data were analyzed using binary logistic regression with a significance level of 5%. Based on the results of the analysis, it can be concluded that floor area of ​​the house, age of the household head, household size, education level of the household head, and floor material of the house have a significantly effect on PKH recipient households. Household size has the most influence on PKH receipt with a 40,3% probability of receiving PKH.
Grouping Regencies/Cities in West Sumatra Province Based on People’s Welfare Indicator Using Biplot Analysis Maya Ifra Shobia; Yenni Kurniawati
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/407

Abstract

The level of community welfare is a crucial reflection of the success of development in a region. Welfare is assessed based on eight aspects: poverty, employment, education, housing, consumption patterns, health, population, and other social factors. In West Sumatra Province, the level of community welfare still requires improvement across all indicators. The determination of community welfare levels can be achieved by reviewing all dimensions based on the linear relationships between districts/cities, thereby providing insights into the indicators that still need enhancement. This effort can assist the West Sumatra Provincial Government in formulating regional policies and programs for equitable distribution and improvement of community welfare across all districts/cities. The data used in this study are secondary data obtained from the West Sumatra Provincial BPS website in 2024. The grouping of districts/cities was conducted using Principal Component Analysis based on singular value decomposition biplot analysis. The analysis results formed four groups with distinct characteristics of community welfare indicators. The groups that need to be prioritized for improvement are groups 1 and 3, which exhibit low levels of community welfare. Group 2 consists of districts/cities with high community welfare characteristics in terms of population, education, and housing. Meanwhile, group 4 includes districts/cities with high community welfare characteristics regarding consumption patterns, poverty, and labor indicators.
Aplication Algorithm Learning Vector Quantization for Classification of Hypertention in Padang Laweh Health Center Harpidna, Riska Harpidna; Chairina Wirdiastuti; Yenni Kurniawati
UNP Journal of Statistics and Data Science Vol. 3 No. 3 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss3/408

Abstract

Hypertension is a health condition characterized by blood vessel disorders, in which there is a chronic increase in blood plessure of 140/90 mmHg. There are several factors that influence hypertension, including unhealthy eating patterns, lack of physical activity, smoking, stress and excess weight. Hypertension does not show clear symptoms, but it has the potential to cause other diseases such as heart failure, stroke, and premature death. Therefore, a study was conducted to classify the risk of hypertension based on hypertension diagnoses at the Padang Laweh Health Center, Dharmasraya Regency, using the Learning Vector Quantiazation (LVQ) Algorithm. The advantage of LVQ is its ability to achieve high accuracy in processing data with numerous numerical and categorical features. The analysis results show that the use of the Learning Vector Quantization Algorithm on the test data produces very good accuracy, namely 95.17% correct classification of hypertensive patients
Design of Innovative Non-Routine Learning Strategies in Chemistry Learning Mujakir, Mujakir; Kurniawati, Yenni; Djamaluddin, Safrijal; Ahmad, Nur Jahan
Jurnal Tadris Kimiya Vol 9 No 2 (2024)
Publisher : Department of Chemistry Education, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/jtk.v9i2.38029

Abstract

Traditional teaching methods in chemistry have been insufficient in helping students master problem-solving and conceptual understanding across the three levels of chemical representation: macroscopic, submicroscopic, and symbolic. Innovative strategies are needed to address these challenges and improve learning outcomes. This study evaluates the feasibility, practicality, and effectiveness of a non-routine learning strategy as an innovative approach to teaching chemistry. The research adopts the Gall and Gall Research and Development (R&D) model with a 3D design framework (Define, Design, Develop). The study involved chemistry education students from UIN Ar-Raniry Banda Aceh and UIN Sultan Syarif Kasim Riau. Data collection instruments included validation sheets to assess feasibility, observation sheets for practicality and effectiveness, as well as tests and related documents. The findings demonstrate that the non-routine learning strategy is valid, practical, and effective. It significantly enhances students' ability to solve problems and explain chemical concepts using the macroscopic, submicroscopic, and symbolic levels of representation. This non-routine learning strategy represents a feasible and effective innovation in chemistry education, providing a practical tool for improving students’ problem-solving skills and conceptual understanding. Its implementation offers valuable insights for advancing chemistry teaching practices.
Penerapan Vector Error Correction Model dalam Menganalisis Dampak Faktor Makroekonomi terhadap Inflasi di Indonesia Anjelisni, Nining; Amalita, Nonong; Kurniawati, Yenni; Martha, Zamahsary
Leibniz: Jurnal Matematika Vol. 5 No. 02 (2025): Leibniz: Jurnal Matematika
Publisher : Program Studi Matematika - Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/leibniz.v5i02.654

Abstract

Penelitian ini bertujuan menganalisis dampak faktor makroekonomi terhadap inflasi di Indonesia pada periode Januari 2020–Maret 2025 dengan menggunakan pendekatan matematis melalui metode Vector Error Correction Model (VECM). Data diperoleh dari situs resmi Badan Pusat Statistik (BPS) dan Bank Indonesia (BI), yang meliputi variabel inflasi, jumlah uang beredar, BI Rate, kurs, ekspor, dan impor. Hasil analisis menunjukkan terdapat empat hubungan kointegrasi signifikan, dengan pengaruh positif dari jumlah uang beredar, kurs, dan ekspor terhadap inflasi, serta pengaruh negatif dari BI Rate dan impor. Dalam jangka pendek, ekspor (lag 1) secara statistik signifikan memengaruhi inflasi, sedangkan variabel lainnya belum signifikan. Model VECM yang dibangun terbukti stabil dan valid melalui berbagai uji kelayakan, serta menunjukkan akurasi tinggi dalam peramalan dengan nilai MAPE sebesar 9,23%. Prediksi inflasi untuk enam bulan ke depan memperlihatkan tren kenaikan bertahap, sehingga diperlukan penguatan ekspor dan pengendalian kebijakan moneter untuk menjaga stabilitas harga. Kontribusi utama penelitian ini adalah penerapan model matematis VECM sebagai alat analisis kuantitatif yang komprehensif dalam studi dinamika inflasi.
Karakteristik Kondisi Air Minum Menurut Wilayah Perkotaan dan Perdesaan di Indonesia Menggunakan Metode CHAID Aulia Wanda; Kurniawati, Yenni
UNP Journal of Statistics and Data Science Vol. 2 No. 1 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss1/152

Abstract

Drinking water is the basic needs of society’s basic instead of food, clothing and shelter. The availability and quality of drinking water needs to be considered, both in terms of quantity and suitability which must meet the requirements. Having clean water as drinking water can reduce diseases such as diarrhea, cholera, dysentery, typhus, worms, skin diseases and poisoning. Decent and clean drinking water is protected drinking water, including tap water, public taps, public hydrants, water terminals, rainwater reservoirs, or protected springs and wells, drilled wells/pumps with the closest distance being 10 meters from the location of waste disposal, waste storage and rubbish disposal. Access to drinking water in urban areas is different compared to that in rural areas. To determine the characteristics of drinking water in urban and rural areas, Chi-Square Automatic Interaction Detection (CHAID) analysis is used. This analysis is used on categorical type variables. Before the analysis stage, there is a data mining process to obtain knowledge from the data cluster and handle missing data in the data cluster. Handling of missing data in categorical variables is done by imputation mode. Using CHAID analysis, drinking water characteristics for rural areas with the highest percentage were filtered using cloth and not boiled and the water source was elsewhere. Meanwhile, in urban areas, the highest percentage of households with drinking water characteristics are treated with bleach/chlorine, not filtered using cloth, and not boiled with a water source in their own yard.
Co-Authors Abdullah Herman Aditya, Muhammad Fadhil Aditya Admi Salma Afifa Lufti Insani Ahmad, Nur Jahan AL Rezki Ivansyah Alya Aufa, Wafiq Amelia Susrifalah Anang Kurnia Anggara, Rudi Anggi Adrian Danis Anita Fadila Anjelisni, Nining Annisa Ramadhani Aprotama, Celsy Ardhi, Sonia Ardiyatul Putri Arnellis Arnellis arrahmi, nailul Atus Amadi Putra Aulia Wanda Aulia, Yuke Aurumnisva Faturrahmi Berliana Nofriadi Bimbim Oktaviandi Celsy Aprotama Chairina Wirdiastuti Cindy Caterine Yolanda Darwas Deska Warita Devi Yopita Sipayung Dewi Murni Dewi, Sari Tirta Dina Fitria Dina Fitria Dina Fitria, Dina Disti Harlin Diva Diva Aliyah Diyanti, Wafika Rahma Djamaluddin, Safrijal Dodi Vionanda Dony Permana Dwi Sulistiowati, Dwi Elfiani Sarian Bur Elfin Innaka Hamidah Elza Vinora Eujenniatul Jannah Fachri Dermawan Fadhil Irsyad, Muhammad Fadhilah Fitri Fadzliana, Nanda Fahmi Amri, Fahmi Fashihullisan Fatimah Depi Susanty Harahap Fayyadh Ghaly Fayza Annisa Febrianti Febiola Putri, Febi Fitri, Fadhilah Fitri, Fitri Hayati fitri, silfia wisa Fitri, Tessa Zulenia Ghaly, Fayyadh Hadiyanti Riskha Handayani, Laras Dyaz harelvi, dhea afrila Harpidna, Riska Harpidna Hary Merdeka Helma Helma Helma Helma Hendrawan, Muhammad Hendri, Jhon Ihsan Dermawan Irwan Irwan Khairani, Putri Rahmatun Kristi, Elizabeth Kusman Sadik Lina, Ejma Rukma Lutfian Almash M Fathoni Arnas Manja Danova Putri Marvero, Andre Maya Ifra Shobia Meira Parma Dewi Minora Longgom Nasution Muhammad Arief Rivano Mujakir Mujakir Mukhti, Tessy Octavia Mulyani, Suci NA Mentacem Nabillah, Marwana Natasya Dwi Ovalingga, natasyalinggaa Nonong Amalita Nugroho, Handi Wilujeng Oktaviani, Bernadita Permana, Dony permana, yazid Prida Nova Sari Putra, Dio Afdal Putra, Rama Dani Eka Putri Amalia Azzahra Putri Yeni, Dicha Putri, Fadhira Vitasha Putri, Rihani Himtari Rahma, Dzakyyah rahmad revi fadillah Rahmah, Ati Rahmawati, Santri Ramadani, Dea refelita, fitri Revina Rahmadani Riady, AD Risnawati Risnawati Rizki Amalia, Annisa Rizkiah, Niswatul Ronald Rinaldo Rosa Salsabila Azarine Rosya, Aljeneri Safitri, Natasya S. Salma, Admi Salsabilla Khairani Sari, Ceria Purnama Sari, Nurhikmah Sasmita, Riza Sepniza Nasywa Septrina Kiki Arisandi Silvia Triana Siregar, Erlina Azmi Siskha Maulana Basrul Siti Nurhaliza Sondriva, Wilia SRI RAHAYU Sri Wahyuni Suprianingsih, Nelis Susrifalah, Amelia Syafriandi Syafriandi Syafriandi Syafriandi Syahidah, Izzati Tessy Octavia Mukhti Tsani, Nahda Maesya Wimmi Sartika Windi Dwi Saputra Wita, Wita Resfi Ananta yenti, elvi Yunistika Ilanda Zamahsary Martha Zilrahmi, Zilrahmi