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All Journal Media Statistika Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Journal of Natural Science and Integration JURNAL EKSAKTA PENDIDIKAN (JEP) Eksakta : Berkala Ilmiah Bidang MIPA Imajiner: Jurnal Matematika dan Pendidikan Matematika Pelita Eksakta Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Leibniz: Jurnal Matematika Journal of Mathematics UNP UNP Journal of Statistics and Data Science Indonesian Journal of Statistics and Its Applications
Yenni Kurniawati
Jurusan Matematika, FMIPA Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Astronomy 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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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
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.
Penanganan Ketidakseimbangan Multikelas pada Dataset Survei Kerangka Sampel Area menggunakan Metode SCUT Sondriva, Wilia; Kurniawati, Yenni; Amalita, Nonong; Salma, Admi
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (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-iss2/163

Abstract

Area Sampling Frame (ASF) is a survey used by the Indonesian government to measure rice productivity in Indonesia. ASF survey is important data because accurate and high-quality rice productivity data is highly needed. There is extreme imbalance in the ASF survey data, thus requiring handling of this imbalance. SMOTE and Cluster-based Undersampling Technique (SCUT) is a method that can be used to address the dataset imbalance. SCUT combines oversampling using SMOTE and undersampling using CUT. The results from SCUT show that the number of data points in each class becomes balanced. Subsequently, a two-sample mean test is conducted to observe the mean differences between the original dataset and the dataset after handling. The results show that in the early vegetative, late vegetative, and harvest phases, the means are significantly similar between the original dataset and the dataset after handling, but in the generative phase, the means are not significantly similar. Therefore, synthetically generated data using the SCUT method generally exhibit similar mean characteristics.
Application of Area Sampling Frame for Digitizing Household Data in Talawi Mudiak to Support Sustainable Development Goals Syafriandi, Syafriandi; Fitria, Dina; Amalita, Nonong; Kurniawati, Yenni; Permana, Dony; Fitri, Fadhilah; Martha, Zamahsary; Mukhti, Tessy Octavia
Pelita Eksakta Vol 8 No 2 (2025): Pelita Eksakta, Vol. 8, No. 2
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol8-iss2/293

Abstract

Desa Talawi Mudiak menghadapi tantangan dalam pengelolaan data kependudukan. Meskipun mereka telah menyusun RPJMD 2022-2027 yang mengacu pada SDG's, pendataan yang dilakukan masih terbatas pada aspek kependudukan dan demografi. Padahal, pemutkhiran data harus mencakup 17 pilar SDg's agar dapat digunakan sebagai dasar dalam perencanaan pembangunan desa. Selain itu, keterbatasan akses internet dan kurangnya pemanfaatan teknologi informasi juga menjadi kendala pengembangan sistem informasi desa yang lebih komprehensif. Program Studi S1 Statistika hadir dalam menjembatani pencapaian beberapa pilar itu melalui pemutakhiran data hingga dilitalisasinya. Kegiatan diawali dengan pengumpulan data awal, perhitungan kerangka sampling, pelaksanaan survei, dan pemrosesan data pasca survei hingga diperoleh suatu kesimpulan yang dapat digunakan untuk pembangunan desa. Kegiatan melibatkan banyak pihak, mulai dari dosen program studi, perangkat desa, mahasiswa, dan masyarakat. Hasil yang diperoleh berupa data yang mutakhir dan sebuah buku berisikan kondisi Desa Talawi Mudiak tahun 2025.
Analisis Pengaruh Penggunaan ChatGPT Terhadap Prestasi Akademik Mahasiswa Dengan Motivasi Sebagai Variabel Intervening Menggunakan Metode SEM-PLS Salsabilla Khairani; Yenni Kurniawati; Dony Permana; Fadhilah Fitri
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (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-iss4/430

Abstract

This study aims to analyze the factors that influence student academic achievement through the use of ChatGPT using the Structural Equation Modeling (SEM) method based on the Partial Least Square (PLS) approach. In this study, three main factors were identified as elements that can influence the use of ChatGPT, namely knowledge about ChatGPT (PTC), willingness to use the technology (KUMT), and concerns that may arise (KYDT), as well as learning motivation as an intervening variable. The total sampling method was used in this study, where the entire population that met the criteria was designated as respondents. The research population included students in the Statistics Study Program at Padang State University in semesters 4–8 who had used ChatGPT for at least six months, with a total of 216 student respondents. Data were collected through a survey using an online questionnaire. Based on the analysis that has been carried out, the results of the study show that the variables of knowledge about ChatGPT (PTC) and willingness to use the technology (KUMT) have a significant positive effect on learning motivation, while concerns that may arise (KYDT) have no significant effect. Furthermore, only the variable of concerns that may arise (KYDT) had a significant direct effect on academic achievement, while the results of the mediation effect test showed that only the variable of willingness to use the technology (KUMT) had a significant indirect effect on academic achievement through learning motivation.
Comparison Performance of SARIMA and Exponential Smoothing Holt-Winter’s models for Forecasting turnover PT. Indah Logistik Cargo Padang Silvia Triana; Dina Fitria; Yenni Kurniawati; Admi Salma
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (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-iss4/432

Abstract

Forecasting is an important part of corporate decision making. With forecasting, companies can predict future conditions and demand so that they can make appropriate and strategic decisions. PT. Indah Logistik Cargo Padang's turnover data contains trend and seasonal elements that are forecasted using a time series model. This study was conducted to determine the best model for forecasting PT. Indah Logistik Cargo Padang's revenue in the coming period. The methods used in this study are the SARIMA method and Holt-Winter's Exponential Smoothing. The best model was obtained from the results of a comparative analysis of the two methods, as seen in the forecasting error rate determined by the mean absolute percentage error value. For forecasting the revenue of PT. Indah Logistik Cargo Padang, the best model used was SARIMA with a MAPE value of 3.9%.
Penerapan Model Log Linear Tiga Dimensi dalam Analisis Faktor Risiko Riwayat Sakit Maag Wita, Wita Resfi Ananta; Eujenniatul Jannah; Siti Nurhaliza; Yenni Kurniawati; Syafriandi Syafriandi
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (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-iss4/433

Abstract

Gastritis, or commonly known as an ulcer, is an inflammatory condition caused by excess stomach acid that irritates the stomach lining. This disease is one of the most common in Indonesia and often disrupts daily activities, especially among students who face academic pressure, stress, and irregular diet. Based on Indonesia’s Health Profile Data, gastritis ranks sixth for inpatients with 330,580 cases, 60.86% of which occur in women, and seventh for outpatients with 201,083 cases, of which 77.74% occur in women. This study aims to examine the relationship between gastritis and demographic factors using a three-dimensional log-linear model. The method analyzes interactions between categorical variables to identify the best explanatory model. Results indicate that the most appropriate model involves the interaction between place of residence, gender, and history of stomach ulcers, showing that these factors collectively influence gastritis incidence. In conclusion, gastritis is not only related to physical health but also lifestyle and demographic factors. This study underlines the importance for students to manage stress, maintain healthy eating habits, and adopt preventive measures. The urgency of this research lies in raising awareness that untreated gastritis may reduce productivity and lead to more serious health problems.
Perbandingan Regresi Ridge dan LASSO dalam Pemilihan Variabel dan Prediksi Keluarga Berisiko Stunting di Sumatera Barat Nofriadi, Berliana; Syafriandi, Syafriandi; Kurniawati, Yenni
Imajiner: Jurnal Matematika dan Pendidikan Matematika Vol 8, No 1 (2026): Imajiner: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/imajiner.v8i1.26124

Abstract

Co-Authors Aditya, Muhammad Fadhil Aditya Admi Salma Afifa Lufti Insani 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 Baehaqi Berliana Nofriadi Bimbim Oktaviandi Celsy Aprotama Chairina Wirdiastuti Cindy Caterine Yolanda Darwas Deska Warita Devi Yopita Sipayung Dewi Murni Dina Fitria Dina Fitria Dina Fitria, Dina Disti Harlin Diva Aliyah Dodi Vionanda Dony Permana Dwi Sulistiowati, Dwi Elfiani Sarian Bur Elfin Innaka Hamidah Elza Vinora Eujenniatul Jannah Fadhil Irsyad, Muhammad Fadhilah Fitri Fahmi Amri, Fahmi Fashihullisan Fayyadh Ghaly Fayza Annisa Febrianti Febiola Putri, Febi Fitri, Fadhilah Fitri, Fitri Hayati fitri, silfia wisa Ghaly, Fayyadh Hadiyanti Riskha harelvi, dhea afrila Harpidna, Riska Harpidna Hary Merdeka Helma Helma Helma Helma Hendrawan, Muhammad Ihsan Dermawan Irwan Irwan Khairani, Putri Rahmatun Kusman Sadik Lutfian Almash M Fathoni Arnas Manja Danova Putri Marvero, Andre Maya Ifra Shobia Meira Parma Dewi Minora Longgom Nasution Muhammad Arief Rivano Mukhti, Tessy Octavia NA Mentacem Natasya Dwi Ovalingga, natasyalinggaa Nofriadi, Berliana Nonong Amalita Oktaviani, Bernadita Permana, Dony permana, yazid Prida Nova Sari Putra, Dio Afdal Putri Yeni, Dicha Putri, Fadhira Vitasha Rahma, Dzakyyah rahmad revi fadillah Revina Rahmadani Rizki Amalia, Annisa Rizkiah, Niswatul Ronald Rinaldo Rosa Salsabila Azarine Salma, Admi Salsabilla Khairani Sasmita, Riza Sepniza Nasywa Septrina Kiki Arisandi Silvia Triana Siskha Maulana Basrul Siti Nurhaliza Sondriva, Wilia SRI RAHAYU Sri Wahyuni Susrifalah, Amelia Syafriandi Syafriandi Syafriandi Syafriandi Tessy Octavia Mukhti Tsani, Nahda Maesya Wimmi Sartika Windi Dwi Saputra Wita, Wita Resfi Ananta Yunistika Ilanda Zahrani Asyati Zulika Zamahsary Martha Zilrahmi, Zilrahmi