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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Martabe : Jurnal Pengabdian Kepada Masyarakat Imajiner: Jurnal Matematika dan Pendidikan Matematika Pelita Eksakta Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Rangkiang Mathematics Journal VARIANSI: Journal of Statistics and Its Application on Teaching and Research UNP Journal of Statistics and Data Science Mathematical Journal of Modelling and Forecasting Indonesian Journal of Statistics and Its Applications
Fitri, Fadhilah
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Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Comparison of Linear Regression and Polynomial Local Regression in Modeling Prevalence of Stunting Fitri, Fadhilah; Almuhayar, Mawanda
Rangkiang Mathematics Journal Vol. 4 No. 1 (2025): Rangkiang Mathematics Journal
Publisher : Department of Mathematics, Universitas Negeri Padang (UNP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/rmj.v4i1.81

Abstract

Stunting is one of the main focuses of the government in Indonesia. This is because nutritional status is one of the benchmarks of community welfare. Stunting can be influenced by various societal aspects such as health, economy, social status, and education. One factor that is thought to be closely related to stunting is the level of education. Therefore, the prevalence of stunting and the level of education will be modeled; in this case, the mean years of schooling is used. Modeling uses two approaches: parametric through linear regression and nonparametric through local polynomial regression. This study compares both models to see which method better explains the stunting phenomenon. The comparison is made through the determination coefficient value or R2, Root Mean Square Error or RMSE, and the fitted curve plot. The results of R2 and RMSE for both models were obtained. The linear regression model has an R2 of 32.94% and an RMSE of 4.84. Meanwhile, for the local polynomial model, it is R2 43.44% and RMSE 4.32. Based on these results, it can be concluded that local polynomial regression is better at modeling the relationship between the prevalence of stunting and mean years of schooling in Indonesia. This finding confirms that the polynomial local regression method can capture phenomena that occur for data that do not follow a particular pattern.
MODELING TOTAL FERTILITY RATE IN INDONESIA: A COMPARISON OF FOURIER SERIES REGRESSION AND ELASTIC NET REGRESSION Fitri, Fadhilah; Ketrin, Melin Wanike; Almuhayar, Mawanda
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2017-2028

Abstract

The Total Fertility Rate (TFR) describes population growth and socioeconomic development of a country. This statistic plays an important role in predicting future social and economic conditions. Indonesia has experienced a steady decline in TFR over the past few decades, which can be a serious problem if this trend continues. Therefore, the factor influencing the decline must be found. The independent variables include the percentage of women graduating high school, percentage of the poor population, poverty gap index, poverty severity index, prevalence of inadequate food consumption, proportion of people living below 50 percent of median income, unemployment rate, infant mortality rate, child mortality rate, and percentage of ever-married women aged 15–49 years using contraception methods. The aim of this study is to compare both Fourier Series Regression and Elastic Net Regression models to see which approximation can capture the TRF phenomenon that occurs in Indonesia and identify the causes of its decline. Fourier Regression is chosen because there is a repetition of patterns in several variables. Moreover, this data is experiencing multicollinearity; hence, Elastic-net Regression is the best way because this method overcomes the limitations of each Ridge and Lasso approach. These models are compared to see which is more suitable to capture the relationships between these factors and TFR. The best model obtained will provide a clearer understanding of Indonesia's underlying drivers of fertility decline. The result is that the Fourier Series Regression can model all variables better than the Elastic-net Regression, and the independent variables can explain the proportion of variance in the dependent variables by 97.91%, with all the independent variables significantly affecting the Total Fertility Rate.
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.
Comparison of the Fuzzy Time Series Chen Model and the Heuristic Model in Forecasting the Number of International Tourists in West Sumatra Rizki Akbar; Fitri, Fadhilah; Vionanda, Dodi; Mukhti, Tessy Octavia
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 1 (2024): June 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i1.20

Abstract

The Fuzzy Time Series Chen and Heuristic are two forecasting methods based on fuzzy logic used to predict values in time series. The FTS Chen and Heuristic models have almost identical forecasting processes, but the main difference lies in how they develop fuzzy logical relationships. The FTS Chen model uses Fuzzy Logical Relationship Groups obtained from the results of Fuzzy Logical Relationships for the forecasting process. On the other hand, the FTS Heuristic model uses Fuzzy Logical Relationships directly in the forecasting process. Fuzzy Logical Relationships are a collection of fuzzy logical relationships used to connect values in time series. By using Fuzzy Logical Relationships, the Heuristic model can predict values in time series more accurately and effectively. The forecasting is done to plan the development of tourism infrastructure, determine service needs, and optimize tourism promotion. The data shows that the number of foreign tourists visiting West Sumatra has continued to grow from 2006 to 2023. The comparison of the accuracy of the forecasting results of FTS Chen and Heuristic models for foreign tourists in West Sumatra yielded a MAPE of 0.241% for FTS model Chen and 0.194% for FTS model Heuristic. This indicates that the best forecasting model for foreign tourists is the Heuristic model due to its lower MAPE value.
Peramalan Harga Emas Menggunakan Fuzzy Time Series-Markov Chain Putri, Eno Dwi; Permana, Dony; Syafriandi, Syafriandi; Fitri, Fadhilah
Imajiner: Jurnal Matematika dan Pendidikan Matematika Vol 7, No 4 (2025): Imajiner: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/imajiner.v7i4.23893

Abstract

Emas dikenal sebagai instrumen investasi andal dalam menghadapi inflasi dan ketidakpastian ekonomi global. Namun, karakteristik data harga emas yang tidak linier dan fluktuatif menjadikannya sulit diprediksi. Penelitian ini bertujuan untuk meramalkan harga emas harian di Indonesia menggunakan metode Fuzzy Time Series-Markov Chain (FTSMC) berdasarkan data periode 1 Januari hingga 13 Juni 2025 sebanyak 118 observasi. Metode FTSMC menggabungkan teori himpunan fuzzy untuk menangani ketidakpastian linguistik dan model rantai Markov dalam memetakan transisi probabilistik antar kondisi harga. Pemodelan dilakukan menggunakan bahasa pemrograman Python, sedangkan evaluasi akurasi menggunakan Mean Absolute Percentage Error (MAPE). Hasil peramalan menunjukkan tren penurunan harga emas secara bertahap selama tujuh hari ke depan, yang mengindikasikan fase koreksi setelah tren kenaikan sebelumnya. Model FTSMC menunjukkan tingkat akurasi sangat tinggi dengan nilai MAPE sebesar 1,10%. Hasil ini konsisten dengan penelitian sebelumnya yang menerapkan pendekatan serupa dan menunjukkan kapabilitas model dalam menginterpretasi serta beradaptasi terhadap dinamika data harga komoditas. Penelitian ini terbatas pada peramalan jangka pendek dan data univariat. Penelitian lanjutan disarankan untuk mempertimbangkan variabel makroekonomi lain seperti suku bunga dan nilai tukar. Kebaruan penelitian terletak pada penerapan metode FTSMC terhadap data harga emas terkini di Indonesia dengan akurasi tinggi, yang dapat mendukung pengambilan keputusan investasi secara praktis.
Penerapan Partial Least Squares dan Pendekatan Robust dalam Analisis Diskriminan untuk Data Berdimensi Tinggi Rahmadina Adityana; Vionanda, Dodi; Permana, Dony; Fitri, Fadhilah
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-iss3/396

Abstract

Classical discriminant analysis, namely linear discriminant analysis and quadratic discriminant analysis, is generally known to suffer from singularity problems when exprerienced with high-dimensional data and is not robust to outliers that make the data not multivariate normally distributed. This research focuses on investigating the classification performance of discriminant analysis on high-dimensional data by applying two approaches, namely the Partial Least Square (PLS) dimension reduction approach as a solution to high-dimensional data and a robust approach with the Minimum Covariance Determinant (MCD) estimator technique that is robust to outliers. The data used for this study is Lee Silverman Voice Treatment (LSVT) data. PLS forms five optimal latent variables that represent predictor variable information. Based on the assumption test of covariance homogeneity between groups, the test statistic value is greater than the chi-square table or the p-value is smaller than the significance level, which means that the assumption is unfulfilled, so quadratic discriminant analysis is applied. The evaluation results showed that the quadratic discriminant analysis analysis model with the MCD approach on the PLS transformed data was able to achieve 81% accuracy, 71% precision, 86% recall, and 77% F1-score. These values indicate that both approaches are able to maintain the efficiency of discriminant analysis classification performance on high-dimensional and multivariate non-normally distributed data.
Comparison of K-Means and Fuzzy C-Means Algorithms for Clustering Based on Happiness Index Components Across Provinces in Indonesia Inna Auliya; Fitri, Fadhilah; Nonong Amalita; Tessy Octavia Mukhti
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-iss1/150

Abstract

Cluster analysis is a statistical technique used to group objects based on their shared characteristics. This research aims to assess how 34 provinces in Indonesia are clustered using happiness index indicators for the year 2021. The study compares two non-hierarchical cluster analysis methods, K-Means and Fuzzy C-Means. K-Means categorizes objects into clusters based on their proximity to the nearest cluster center, while Fuzzy C-Means employs a fuzzy grouping model assigning membership degrees from 0 to 1. The results indicate that both methods form three clusters. Evaluating standard deviation values and ratios, Fuzzy C-Means proves superior, displaying a larger standard deviation between groups and a smaller ratio (0.6680004) compared to K-Means. Consequently, the study concludes that the Fuzzy C-Means method is more optimal than K-Means.
PELATIHAN PINJAMAN ONLINE: KENALI YANG LEGAL DAN ILEGAL, HINDARI JEBAKAN Prima Sari, Devni; Fitri, Fadhilah; Fitria, Yuki
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 8, No 1 (2025): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v8i1.279-285

Abstract

Meningkatnya penggunaan pinjaman online di masyarakat, terutama di kalangan pelajar dan pendidik, menimbulkan masalah baru dalam literasi keuangan. Kegagalan untuk memahami perbedaan antara pinjaman online yang legal dan ilegal, beserta risiko-risiko yang menyertainya, membuat banyak orang rentan terjebak dalam utang yang berbahaya. Di SMAN 3 Padang Panjang, instruksi khusus diberikan mengenai dimensi hukum pinjaman online. Program ini mencakup peserta tentang perbedaan antara pinjaman yang legal dan melanggar hukum, strategi untuk menghindari jebakan utang, dan kriteria untuk memilih pinjaman yang sesuai. Hasil penilaian menunjukkan adanya peningkatan pemahaman peserta terhadap dimensi hukum pinjaman online, yang diharapkan dapat meningkatkan literasi keuangan dan memfasilitasi penilaian keuangan yang lebih bijaksana di masa depan.
PENINGKATAN KEMAMPUAN GURU DALAM VISUALISASI DATA UNTUK PENELITIAN TINDAKAN KELAS MELALUI PELATIHAN MICROSOFT EXCEL DAN QUIZIZZ Prima Sari, Devni; Fitri, Fadhilah; Meutia Rani, Maulani
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 8, No 1 (2025): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v8i1.286-294

Abstract

Pelatihan bertujuan untuk meningkatkan keterampilan guru dalam menganalisis dan memvisualisasikan data, mendukung pengambilan keputusan berbasis bukti di kelas. Fokus pelatihan ini adalah penggunaan alat analisis data, seperti Microsoft Excel dan Quizizz, yang membantu guru memahami dan menyajikan data secara efektif. Hasil pelatihan menunjukkan peningkatan signifikan dalam keterampilan visualisasi data peserta, di mana guru-guru lebih mampu mengaplikasikan fitur grafik dan diagram untuk menampilkan hasil pembelajaran secara jelas dan menarik. Dengan peningkatan ini, guru-guru menjadi lebih siap dalam merencanakan dan melaksanakan Penelitian Tindakan Kelas (PTK), yang memungkinkan mereka menghasilkan solusi berbasis bukti untuk meningkatkan efektivitas pembelajaran. Pelatihan ini diharapkan dapat memperkuat peran guru sebagai agen perubahan dalam pendidikan, mendorong peningkatan kualitas pendidikan di sekolah dan masyarakat secara keseluruhan.
Digitalization Data of Talawi Mudiak 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.
Co-Authors Almuhayar, Mawanda Dina Fitria Dina Fitria, Dina Dodi Vionanda Faulina Fishuri, Nufhika Ikhsan, Easbi Inna Auliya Ketrin, Melin Wanike Larissa, Dwika Maulani Meutia Rani Muhammad Faisal Mukhti, Tessy Octavia Nonong Amalita Permana, Dony Prima Sari, Devni Putri, Eno Dwi Putri, Fadhira Vitasha Rahmadina Adityana Rizki Akbar Safitri, Melda Salma, Admi Sari, Widia Kemala Syafriandi Syafriandi Tessy Octavia Mukhti Widiyanti Yenni Kurniawati Yuki Fitria Zamahsary Martha Zilrahmi, Zilrahmi