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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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Analisis Pemilihan Model Regresi Konversi Metanol Berdasarkan Suhu, Waktu Tinggal, Konsentrasi, Rasio Oksigen, dan Sistem Reaktor Marvero, Andre; Amri, Fahmi; Fadhil Irsyad, Muhammad; Kurniawati, Yenni
UNP Journal of Statistics and Data Science Vol. 3 No. 1 (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-iss1/339

Abstract

This study aims to determine the best regression model that explains the effect of temperature, residence time, methanol concentration, oxygen to methanol ratio, and reactor system on methanol conversion in supercritical water. Preliminary analysis showed a violation of the multicollinearity assumption, which affected the validity of the multiple linear regression model. To overcome this and determine the optimal model, variable selection was performed using the stepwise selection method. This method was evaluated based on predictive power, model accuracy and statistical validity. The results showed that the stepwise method produced an optimal model in predicting conversion. Reactor system and temperature were the most significant variables affecting methanol conversion. The conclusion of this study shows that the variable selection approach with stepwise selection can be effectively used to identify the best regression model, when classical assumptions are met. These findings make an important contribution to the optimization of supercritical water-based chemical processes.
ANALISIS KEMISKINAN DI INDONESIA MENGGUNAKAN LOCAL INDICATOR OF SPATIAL ASSOCIATION DAN SPATIAL ERROR MODEL Khairani, Putri Rahmatun; Kurniawati, Yenni; Amalita, Nonong; Mukhti, Tessy Octavia
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 6 No. 1 (2025): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v6i1.966

Abstract

Poverty in Indonesia remains a significant socio-economic challenge with notable regional disparities. The eastern provinces, particularly Papua, Maluku, and East Nusa Tenggara, experience persistently high poverty rates, suggesting a strong spatial influence. This study examines the spatial distribution of poverty using the Local Indicators of Spatial Association and the Spatial Error Model with 2024 data from the Indonesian Central Statistics Agency (BPS) for 38 provinces. The analysis employs a K-Nearest Neighbors weighting matrix (k = 10) for spatial dependencies. The LISA results identify High-High poverty clusters in Papua, Maluku, and East Nusa Tenggara. In contrast, Low-Low clusters are concentrated in Java and Bali, indicating a strong spatial pattern (Moran’s I = 0.4448). SEM findings reveal that the Gini index (β = 29.97) and population density (β = 0.016) significantly influence poverty, whereas inflation and total population do not. The model explains 76.1% of poverty variance (R² = 0.760966), highlighting its superiority over traditional regression models. These findings underscore the need for spatially adaptive policies to address poverty effectively. Policymakers should prioritize equitable economic development, regional investment, and infrastructure improvements, particularly in high-poverty clusters. Integrating spatial econometric models with KNN provides deeper insights into interregional disparities, supporting more precise and inclusive development strategies
Mapping Area of Nagari Tanjung Gadang Sijunjung Regency Kurniawati, Yenni; Fitria, Dina; Salma, Admi
Pelita Eksakta Vol 8 No 01 (2025): Pelita Eksakta, Vol. 8, No. 1
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol8-iss01/281

Abstract

Developing a digital village as a government point of view supports Nagari Tanjung Gadang as one of Sicantik (a village loving statistics). The village and server got the up to date data about the village and its sub-village. The problem for the village is presenting and analysing the data to publish as it is used. They also found difficulties in writing it into a publication format. The server gave an assistance to write Lumbuang Data Nagari Tanjung Gadang. The result is a book which explains the demographic condition of the village.
Analysis Of Students' Critical Thinking Skills With The Learning Cycle 5e Learning Model On Stoichiometry Material Yenni Kurniawati
Jurnal Pendidikan, Sains Dan Teknologi Vol. 4 No. 1 (2025): Januari - Maret
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jpst.v4i1.2423

Abstract

This research aimed at analyzing and knowing the difference on critical thinking ability of the tenth-grade students of Science between before and after implementing Learning Cycle 5E learning model. It was conducted on the second semester in the Academic Year of 2017/2018 at the tenth grade of Science 2 of Islamic Senior High School of Darul Hikmah Pekanbaru, and the material was about Stoichiometry. This research was Descriptive, and the one group pretest-posttest design was used. Purposive sampling was used in this research and 21 students were the samples. The instrument was essay in the forms of pretest and posttest, and the instruments used to strengthen the data were observation sheet and interview. The data analysis result showed that student critical thinking ability taught by using Learning Cycle 5E learning model was on good category. The most dominant indicator of high, medium, and low student critical thinking ability was giving simple explanation with N-Gain that was 0.63, and the lowest indicator was making further explanation with N-Gain that was 0.39. The result of student interview showed that students were interested in Learning Cycle 5E learning.
Analysis of Differentiated Learning Implementation Using a 3D Chemistry Periodic Table Application to Improve Students' Cognitive Ability Safitri, Natasya S.; Kurniawati, Yenni
Jurnal Akademika Kimia Vol. 14 No. 1 (2025)
Publisher : Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/j24775185.2025.v14.i1.pp1-7

Abstract

The cognitive ability of each student is different. To improve it, it needs to be trained and optimized. The purpose of cognitive skills is the implementation of differentiated learning using a 3D Chemistry Periodic Table Application to improve the students’ cognitive ability. This research was implemented in the even semester academic year 2023 / 2024 at State Senior High School 1 Tambang. The method used in this research was mixed-method research with a research design Sequential Explanatory model, with research samples consisting of three classes of Grade X at State Senior High School 1 Tambang, namely two (2) experimental classes and one (1) control class. The post-test research result showed a significance of 0.000 < 0.05 until indicating a significant difference between the experimental and control classes. Besides, the average N-Gain of the experimental class namely 0.77, and the second experimental class was 0.71, with high category, and the control class was 0.60, with medium category. In other words, it is proven that differentiated learning with a 3D application increases cognitive ability. The students’ response after gaining the learning by using 3D was excellent, with a percentage of 81.41 %. The results of this research are expected to help teachers improve the students’ cognitive abilities.
Comparison of The Singular Spectrum Analysis and SARIMA for Forecasting Rainfall in Padang Panjang City Putri, Fadhira Vitasha; Fitri, Fadhilah; Kurniawati, Yenni; Zilrahmi, Zilrahmi
Indonesian Journal of Statistics and Applications Vol 9 No 1 (2025)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v9i1p61-74

Abstract

Indonesia is an area with a tropical climate, so it has two seasons, namely the rainy season and the dry season. The rainy season lasts from November to March and during this period rainfall tends to be high in several areas. Padang Panjang City is one of the cities with the smallest area in West Sumatra Province, which has the nickname Rain City. This is because the city of Padang Panjang has cool air with a maximum air temperature of 26.1 °C and a minimum of 21.8 °C, so this city has a fairly high level of rainfall with an average of 300 to 400 mm/year. This article discusses rainfall forecasting for Padang Panjang City by comparing the Singular Spectrum Analysis and Seasonal Autoregressive Integrated Moving Average methods. The data used spans 8 years, from January 2016 to December 2023. Forecasting results are obtained from the best method selected based on the smallest Mean Absolute Percentage Error value. The Singular Spectrum Analysis method has a Mean Absolute Percentage Error value of 5.59% and Singular Spectrum Analysis and Seasonal Autoregressive Integrated Moving Average  has a value 7.43%. The best forecasting method is obtained by the Singular Spectrum Analysis method.
Classification of Rice Growth Phase Using Regression Logistic Multinomial Model and K-Nearest Neighbors Imputation on Satellite Data Ghaly, Fayyadh; Kurniawati, Yenni; Amalita, Nonong; Fitria, Dina
Indonesian Journal of Statistics and Applications Vol 9 No 1 (2025)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v9i1p1-9

Abstract

One of the efforts made by the government to maintain food security is to provide statistical data on rice production through accurate calculation of harvest areas using the area sampling framework approach. Although area sampling framework surveys produce accurate estimates, the costs required are quite high when applying this method. To overcome this problem, one solution that can be applied is to utilize satellite imagery to monitor the greenness index of plants using the enhanced vegetation index. However, in real conditions, the Landsat-8 optical satellite is susceptible to cloud cover, which results in missing data. This study aims to model the phase of rice plants using the regression logistic multinomial model by utilizing Landsat-8 satellites and k-nearest neighbors imputation handling to overcome missing data. The results showed that the model had varying performance in each phase, with an average balanced accuracy of 66.45%. This figure shows that the model can classify the area sampling framework data imputed using the k-nearest neighbors imputation method well. The model shows optimal performance in the late vegetative and generative phases but is less effective in detecting the harvest, puso, and non-rice paddy phases.
Application of Singular Spectrum Analysis in Predicting Rupiah Exchange Yuan Hendrawan, Muhammad; Zilrahmi, Zilrahmi; Kurniawati, Yenni; Fitria, Dina
Indonesian Journal of Statistics and Applications Vol 9 No 1 (2025)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v9i1p75-85

Abstract

The exchange rate between two countries is the price of the currency used by residents of these countries to trade with each other, the relationship between the Rupiah exchange rate and the Yuan is one of the important aspects in the dynamics of international trade. Therefore, forecasting the exchange rate is important as an effort to predict the exchange rate of Rupiah against Yuan in the future. The method used for forecasting is Singular Spectrum Analysis, namely decomposition and reconstruction. The accuracy of the resulting forecast is measured using the Mean Absolute Percentage Error criterion. The exploration results obtained are forecasting accuracy based on the Mean Absolute Percentage Error value of 2.15% with a window length of 23 which identifies that the forecasting results are accurate and effective. Forecasting is said to be accurate if the Mean Absolute Percentage Error value is lower than 10% and close to 10%
Peramalan Curah Hujan Sebagai Upaya Mitigasi Bencana Menggunakan Seasonal Autoregressive Integrated Moving Average Fayyadh Ghaly; Amelia Susrifalah; Yenni Kurniawati
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 1 (2025): VOLUME 13 NO 1 TAHUN 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i1.55289

Abstract

Rainfall prediction is important in disaster mitigation to reduce impacts such as drought, flood, and landslide. Rainfall data that has a seasonal pattern requires an appropriate forecasting method, one of which is SARIMA. This study predicts rainfall at the Deli Serdang Climatology Station, North Sumatra, based on monthly observation data for 2018–2023, showing a seasonal pattern with a 12-month cycle. The best model obtained is SARIMA (0,0,1) (0,0,1)12 with a MAPE of 19.5%, indicating a prediction accuracy of 80.5%. The forecasting results indicate a decrease in rainfall in the first semester of 2024, which is in the medium rainfall category. These findings can support disaster risk mitigation strategies and natural resource management planning related to climate change. The SARIMA model also has the potential to be applied in further climatology studies.
Binary Logistic Regression to Factors Affecting Unmet Need for Limiting in East Java, Indonesia Sri Wahyuni; Yenni Kurniawati; Sepniza Nasywa; Ardiyatul Putri
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (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-iss2/353

Abstract

East Java, Indonesia's second most populated province, is anticipated to see significant annual population growth in the future, potentially resulting in a population explosion. The elevated birth rate facilitates the swift increase in population size. The unmet need for knowledge-based information among women of reproductive age has posed obstacles for the execution of family planning initiatives aimed at reducing birth rates. This study used binary logistic regression to identify the factors affecting the unmet demand for family planning among women of reproductive age in East Java Province in 2017.The investigation revealed that the woman's age, employment status, and husband's educational level significantly influenced the unmet need for constraint. Moreover, women aged 15-24 who are unemployed, lack schooling, have an illiterate partner, and reside in rural regions are more prone to experiencing an unmet need for contraception. Women aged 15-19 years compared to women aged 45-49 years were at 3,182 times higher risk of having an unmet need for family planning compared to a met need for family planning. Women aged 20-24 years compared to women aged 45-49 years were at 1,316 times higher risk of having an unmet need for family planning compared to a met need for family planning. Women who did not work compared to women who worked were 1,311 times more likely to have an unmet need for family planning compared to a met need for family planning. The binary logistic analysis model that was formed provided a good accuracy of 92,135% in predicting
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