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All Journal AKSIOMA: Jurnal Program Studi Pendidikan Matematika Jurnal Edukasi Matematika dan Sains Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Gantang NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Basicedu Eksakta : Berkala Ilmiah Bidang MIPA FIBONACCI: Jurnal Pendidikan Matematika dan Matematika Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Pelita Eksakta Jurnal Ilmiah Pendidikan Matematika Al Qalasadi Jurnal Basicedu Journal of Mathematics UNP UNP Journal of Statistics and Data Science International Journal of Trends in Mathematics Education Research (IJTMER)
Dony Permana
Jurusan Matematika Universitas Negeri Padang
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Analysis of Factors Influencing the Number of Families at Risk of Stunting in Merangin Regency Using Mixed Geographically Weighted Regression Fadlan Rafly, Muhammad; Zilrahmi; Dony Permana; Dina Fitria
UNP Journal of Statistics and Data Science Vol. 2 No. 4 (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-iss4/236

Abstract

The number of families at risk of stunting is among the significant concerns that have been a negative impact on developing superior human resources in Merangin Regency. The number of families at risk of stunting is sought to be solved by identifying the contributing components. MGWR is among the methods that may be employed to obtain a specific model that affects each obesrvasion location locally and a comprehensive model that is global. Multiple linear regression and GWR are used to create models MGWR used when data has the influence of spatial heterogeneity. This project aims to develop an MGWR model which will be used to calculate the amount families at risk of stunting in each sub-district in Merangin Regency who are at risk of stunting in 2022. A fixed gaussian kernel weighting matrix is used in MGWR modeling. At the very least CV of 0.6152241, A fixed gaussian kernel is utilized as the weighting function. The results indicate that the model obtained has an accuracy rate of 99.18%, which means that the predictor variables can explain the model by that percentage. Families with insufficient access to drinking water is one factor that significantly affects how many families are at risk of stunting, families with inadequate sanitation, maternal age less than 20 years and families with babies under five years old.
Library Book Lending Recommendation Using Association Rules with Frequent Pattern Growth (FP-Growth) Algorithm Kamil, Fakhri; Dony Permana; Dodi Vionanda; Dina Fitria
UNP Journal of Statistics and Data Science Vol. 2 No. 4 (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-iss4/284

Abstract

College libraries are libraries managed by higher education institutions such as university libraries. The library functions as an information center management forum for students which includes learning resource functions, access functions, librarian functions, ethical functions, and evaluation functions.  Students prefer to read through e-books rather than reading books or library collections. Limited knowledge of literature is the cause of students choosing to look for books on search engines rather than in the library. Managed book loan circulation history data will be able to improve library services that can assist in finding library collections. Book recommendation services using association rules, can find patterns of borrowing behavior of book titles that have the highest association as the most recommended titles to be borrowed together. The FP-Growth or Frequent Pattern Growth is an algorithm of associations rule that is able to generate association rules as personalized book borrowing recommendations. The results of book recommendations found as many as 50 rules that meet the chi-square assumption test where the recommendation items are independent. The results of 50 rules for book title choices that can be used by students as suggestions for determining books that have a relationship to be borrowed together to enrich references. For students who wish to borrow the books 'Professional Teacher: Mastering Teaching Methods and Skills' is recommended to also borrow the book 'Participatory Learning Methods and Techniques'. With the book recommendation service, the library provides advice to students in choosing related book titles to borrow at the library.
Perbandingan Analisis Diskriminan Kuadratik dengan Analisis Diskriminan Kuadratik Robust martha, Ully Martha; Dodi Vionanda; Dony Permana; Zilrahmi
UNP Journal of Statistics and Data Science Vol. 2 No. 4 (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-iss4/315

Abstract

This study compared the performance of quadratic discrimination analysis and robust quadratic discrimination analysis using the Iris dataset from Kaggle. The robust quadratic discriminant analysis, designed to handle outliers and non-normal distributions, shows better performance with an Apparent Error Rate (APER) of 2.5%. In contrast, the quadratic discriminant analysis, used for data with multivariate normal distribution and different variance-covariance matrices among groups, yields an APER of 3.03%. These results indicate that robust quadratic discriminant analysis is more accurate in classification on this dataset compared to quadratic discriminant analysis. Keywords: Apparent Error Rate, Quadratic Discrimination Analysis, Robust Quadratic Discrimination Analysis
Implementation of Association Rule on Agricultural Commodity Exports in Indonesia Using Apriori Algorithm Dinul Haq, Asra; Fitria, Dina; Dony Permana; Zamahsary Martha
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-iss1/336

Abstract

Exports of agricultural commodities in Indonesia have the smallest contribution to state revenues and the movement of export values ​​in the last decade has not shown a significant increase compared to other export sectors. This shows that there are weaknesses in the export of agricultural commodities so that an analysis is needed to optimize export results to other countries. These weaknesses can be seen in terms of quality, price, infrastructure and technology. This study uses association rule analysis with the apriori algorithm with the aim of finding out what agricultural commodities are exported simultaneously and the resulting association rules. The apriori algorithm is an algorithm used to find association rules between items in a database by considering two main parameters, namely Support and Confidence. The data used is agricultural commodity export data obtained from the publication of the Central Statistics Agency in Indonesia in 2023. Based on the analysis carried out, there are 32 association rules generated with a minimum Support of 25% and a minimum Confidence of 80%. Then after the Lift Ratio test was carried out, all the rules generated met the Lift Ratio test with a value of more than 1. The association rules produced must have at least 2 to 4 agricultural export commodities in each rule. By knowing the association rules for agricultural commodity exports, it is hoped that export distribution in the agricultural sector can be further optimized for trading abroad so that it can cover existing weaknesses.
Classification of Factors Affecting Preeclampsia in Pregnant Women at RSUP. Dr. M. Djamil Padang using the CART Algorithm YUSWITA, AULIA; Dina Fitria; Dony Permana; Admi Salma
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-iss1/341

Abstract

Preeclampsia is a pregnancy-specific disease characterized by hypertension and proteinuria that occurs after 20 weeks of gestation. Preeclampsia itself is caused by various factors that can influence the occurrence of preeclampsia in pregnant women, including age, parity, history of hypertension, obesity, and kidney disorders. This study aims to determine the risk factors influencing preeclampsia based on preeclampsia diagnosis at RSUP Dr. M. Djamil Padang by classifying each variable using a decision tree. This research employs the CART (Classification and Regression Tree) algorithm. The CART algorithm has a binary nature and can analyze response variables that are either categorical or continuous, handle data with missing values, and produce an interpretable tree structure. The study results indicate that the primary risk factor for preeclampsia is parity. The model developed using the CART algorithm was tested using a confusion matrix, yielding an accuracy of 54%, a precision of 33.3% in correctly classifying patients with mild preeclampsia (PER), and a recall of 23.8% in classifying patients with severe preeclampsia (PEB).
Analysis on Scopus Articles Padang State University Based on SINTA Website Aidillah, Kerin Hagia; Dodi Vionanda; Dony Permana
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-iss1/346

Abstract

Universities have the responsibility to carry out education, research, and community service as mandated by Law Number 20 of 2003 on the National Education System in Article 20. The flagship research theme set by Universitas Negeri Padang (UNP) for the period 2020-2024 is "Development of Digital Learning Services and Development of Minangkabau Cuisine based on Local Potential." The focus of the flagship research activities at Padang State University encompasses two main research areas: 1) Digital Learning Services; and 2) Minangkabau Cuisine. The objective of this research is to compare the flagship research theme with the Scopus articles from Universitas Negeri Padang on the SINTA website. By analyzing the trends of Scopus article topics on the SINTA website using web scraping techniques and wordcloud visualization, it is concluded that there is a match between the trending topics of UNP's Scopus articles and UNP's flagship research theme, particularly in the field of Digital Learning Services. From the wordcloud results, which show keywords such as Learning, Development, Student, and Model. This research allows us to easily observe from the wordcloud visualization the trend of research topics in Scopus articles on SINTA at Universitas Negeri Padang, reflecting the realization of Universitas Negeri Padang flagship research theme for the period 2020-2024
PENGEMBANGAN MULTIMEDIA INTERAKTIF BERBASIS PROBLEM BASED LEARNING PADA MATERI STATISTIKA Refenia Usman; Elita Zusti Jamaan; Arnellis Arnellis; Dony Permana; Afifah Zafirah
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol 14, No 1 (2025)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ajpm.v14i1.8634

Abstract

Peningkatan Kemampuan Pemecahan Masalah Matematis (KPMM) dapat dicapai melalui pembelajaran yang terintegrasi dengan teknologi, salah satunya melalui multimedia interaktif. Penggunaan multimedia ini menjadikan proses pembelajaran lebih menarik dan interaktif. Selain itu, model pembelajaran Problem Based Learning (PBL) juga berperan penting dalam mendukung pengembangan KPMM peserta didik. Tujuan dari penelitian ini adalah untuk mengembangkan multimedia interaktif berbasis PBL yang valid, praktis, dan efektif dalam memfasilitasi pengembangan KPMM peserta didik. Penelitian ini menerapkan model Plomp, yang meliputi tiga fase: fase investigasi awal, fase pengembangan atau pembuatan prototipe, dan fase penilaian. Peserta didik kelas X di salah satu SMA di kota Padang menjadi subjek penelitian ini. Instrumen penelitian yang digunakan mencakup pedoman wawancara, lembar angket, lembar observasi, dan tes KPMM. Analisis data yang digunakan yaitu teknik deskriptif dan statistik deskriptif. Hasil penelitian menunjukkan bahwa multimedia interaktif berbasis PBL telah terbukti valid dengan skor 88,88%, praktis digunakan oleh pendidik matematika dan peserta didik dengan skor masing-masing 82,19% dan 80,00%, serta efektif dalam memfasilitasi pengembangan KPMM dengan skor rata-rata 80,00%.The improvement of Mathematical Problem-Solving Ability (MPSA) can be achieved through technology-integrated learning, one of which is through interactive multimedia. the use of multimedia  enhances the learning experience by making it more engaging and interactive. Additionally, the Problem-Based Learning (PBL) model is also essential in supporting the development of students' MPSA. This study aims to create PBL-based interactive multimedia that is valid, practical, and effective in supporting the development of students' MPSA. This study utilizes the Plomp model, which consists of three phases: the initial investigation phase, the development or prototyping phase, and the assessment phase. Tenth-grade students from a high school in Padang served as the study's subjects. The research instruments used include interview guidelines, questionnaires, observation sheets, and MPSA tests. Data analysis involved descriptive and descriptive statistical techniques. The study results show that PBL-based interactive multimedia has proven to be valid with a score of 88.88%, practical for use by mathematics teachers and students with scores of 82.19% and 80.00%, respectively, and effective in facilitating MPSA development with an average score of 80.00%. 
Application of the ARIMA Method for Forecasting the Average Corn Production in Padang Pariaman Regency Alandra, Cindy Resha; Dony Permana
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.v13i1.55288

Abstract

Jagung memegang peranan penting dalam sektor pertanian dan menempati peringkat ketiga sebagai tanaman pokok terpenting di dunia setelah beras dan gandum. Di Indonesia, jagung merupakan komoditas strategis yang banyak digunakan sebagai bahan pangan, pakan ternak, dan bahan baku industri. Produksi jagung di Kabupaten Padang Pariaman berfluktuasi dari waktu ke waktu, sehingga memerlukan peramalan yang akurat untuk mendukung perencanaan dan pembuatan kebijakan pertanian. Penelitian ini bertujuan untuk meramalkan rata-rata produksi jagung di Kabupaten Padang Pariaman selama kurun waktu lima tahun (2022–2026) dengan menggunakan model Autoregressive Integrated Moving Average (ARIMA). Beberapa langkah yang dilakukan dalam penelitian ini meliputi pengumpulan data, pengujian stasioneritas, pemilihan model, pemeriksaan diagnostik, dan peramalan. Hasil penelitian menunjukkan bahwa model ARIMA yang paling sesuai adalah ARIMA(1,0,0), yang menunjukkan bahwa model ini paling sesuai untuk memprediksi tren masa depan rata-rata produksi jagung di Kabupaten Padang Pariaman. Hasil prakiraan menunjukkan penurunan produksi jagung selama lima tahun ke depan, dengan Mean Absolute Percentage Error (MAPE) sebesar 7,57%, yang menunjukkan tingkat akurasi prakiraan yang tinggi. Temuan ini menyoroti perlunya intervensi strategis dari pemerintah dan petani untuk mengatasi masalah ini secara efektif.
Perbandingan metode Double Moving Average(DMA) dan Double Exponential Smoothing (Brown) Terhadap Tingkat Pengangguran Terbuka (TPT) di Kota Padang Panjang. Fishuri, Nufhika; Fadhilah Fitri; Dony Permana
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-iss2/366

Abstract

The Open Unemployment Rate (TPT) is the percentage of unemployed people in the total labor force. The population included in the labor force is the population aged 15 years and over who has a job but is temporarily not working. Unemployment occurs because of a mismatch between the demand for employment and the qualifications of job seekers. Many job vacancies require graduates with a diploma or degree, so unemployment is one of the problems faced by Padang Panjang City. To overcome TPT in Padang Panjang City, one of the needs is to do forecasting to see how the TPT rate will occur in the coming year. This research uses a forecasting method by comparing the Double Moving Average (DMA) and Double Exponential Smoothing (DES) forecasting values of the Unemployment Rate in Padang Panjang City from 2006 to 2023. This forecasting is done to provide insight into the future condition of the workforce in Padang Panjang City. The results of the forecasting indicate that in 2024, there will be an increase of 0.42%, and for the next 2 years, there will be a decrease
Peramalan Total Nilai Ekspor Indonesia Menggunakan Metode Singular Spectrum Analisis Ronald Rinaldo; Yenni Kurniawati; Dony Permana; Dina Fitria
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-iss2/370

Abstract

Forecasting export data presents unique challenges due to seasonal fluctuations and complex global economic dynamics. Inaccurate forecasts may lead to misguided economic policies, particularly in the export sector, which plays a critical role in national economic growth. This study aims to forecast the total export value of two major sectors in Indonesia from January to December 2024 using the Singular Spectrum Analysis (SSA) method. Forecasting is essential in supporting economic policy planning and strategic decision-making. SSA is chosen for its ability to decompose time series data into interpretable components such as trend, seasonality, and noise. The forecasting model's performance is evaluated using the Mean Absolute Percentage Error (MAPE), which provides an intuitive accuracy interpretation in percentage terms. The optimal parameter for SSA was found at L=28L = 28L=28, yielding a MAPE of 16.63%, indicating good forecasting accuracy. The forecasted export values show that the highest export is expected in December 2024 (USD 39,578.67 million), and the lowest in January 2024 (USD 21,689.14 million). These findings suggest that SSA is effective in forecasting economic time series data, particularly Indonesia’s export values. This study contributes to the practical application of SSA in economics and serves as a reference for future research and policymakers in formulating export strategies.
Co-Authors 01, Riska Addini, Vidhiya Ade Eriyen Saputri Admi Salma Admi Salma Afdhal, Afdhal Rezeki Afifah Zafirah Ahmad Fauzan Aidillah, Kerin Hagia Alandra, Cindy Resha Aldi Prajela Ali Asmar Andini Diva Luthfiyah april leniati Armiati Arnellis Arnellis Arssita Nur Muharromah Atus Amadi Putra Azma, Meil Sri Dian Bahri Annur Sinaga Bonita Nurul Afifah Carina, Fadhillah Meisya Denny Armelia Dewi Febiyanti Dina Fitria Dina Fitria, Dina Dinul Haq, Asra Dodi Vionanda Dwi Putri Amilia Dwi Ratih Listiani Yusri Dwi Sulistiowati Edwin Musdi Elita Zusti Jamaan Elsa Oktaviani Elvina Catria Emi Suryani Putri Fadhilah Fitri Fadhillah Fitri Fadlan Rafly, Muhammad Fanni Rahma Sari Fauzan Arrahman Febri Ramayanti Fenni Kurnia Mutiya Fishuri, Nufhika Hana Rahma Trifanni Hana Zafirah haniyathul husna Hardi, Afifah Hasna, Hanifa Hefiani Mustika Hasanah Helma Helma Huriati Khaira I Made Arnawa Ibnul farizi, Gilang iin aini fitri Indonesia Irma Surya Anisa Isra Miraltamirus Kamil, Fakhri Kurnia Andrea Diva martha, Ully Martha Media Rosha Meidiani Sandra Meliani Maya Sari Meliani Putri Mohammad Reza febrino Muslimah, Nailul Amani Muthia Sakhdiah Mutiara Amazona Sosiawati nabillah putri Nadya Nadya nazhiroh, hanifah Nilda Yanti Nisa Ulkhairat Asfar Nisa, Farras Luthfyah Nonong Amalita Nur Fadillah, Nur Nurdalia Nurul Afifah Putra, M. Farel Rusde rahmad revi fadillah rama novialdi Refenia Usman Refina Rintani Revina Rahmadani Ridha Fajria rios Riry Sriningsih RIZKIA, DHEA PUTRI Ronald Rinaldo roza maylinda Salsabilla Khairani Septrina Kiki Arisandi Siltima Wiska Siregar, Fauzan Al-Hamdani Sofni Fajriani SRI RAHAYU Suherman Suherman Suwanda Risky Syafriandi Syafriandi Syafriandi Tessy Octavia Mukhti Titin Mardianingsih Tri Wahyuni Nurmulyati Vinka Haura Nabilla Wahda Aulia Assara Welgi Okta Irawan Widia Handa Riska Yarman Yarman Yatri Asri Yenni Kurniawati Yerizon Yerizon Yoga Perdana Yuli Andari Wulan Yulia Pertiwi Yulia Utami Putri Yulyanti Harisman Yurivo Rianda Saputra YUSWITA, AULIA Zamahsary Martha Zilrahmi, Zilrahmi