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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 Mathematical Journal of Modelling and Forecasting Indonesian Journal of Statistics and Its Applications
Fitri, Fadhilah
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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.
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.
Nonparametric Fourier Series Regression for Unemployment Analysis in Banten Province Barokah, Bunga Miftahul; Fitri, Fadhilah; Wirdiastuti, Chairina
Rangkiang Mathematics Journal Vol. 5 No. 1 (2026): 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.v5i1.90

Abstract

The Open Unemployment Rate (OUR) is a vital indicator of regional economic performance, particularly in Banten Province, which faces disparities in education and poverty. This study models the unemployment rate using two predictors: average years of schooling and poverty level, through a nonparametric Fourier series regression for the 2017–2024 period. This method provides greater flexibility in capturing the nonlinear and fluctuating patterns often observed in socio-economic data. The analysis used secondary data from Statistics Indonesia (BPS), beginning with descriptive statistics and data visualization. Models were evaluated using Generalized Cross-Validation (GCV) and the coefficient of determination (R²). The optimal model was found at K = 3, with a GCV of 2.4057 and an R² of 0.5155. The model effectively captured the non-linear relationships between unemployment, education, and poverty. Although the R² value is moderate, this indicates that including additional explanatory variables could enhance the model’s performance. These findings support the use of Fourier series regression as an alternative approach for labor market analysis, especially when linear methods fall short and provide insights for developing more targeted employment policies.
Pemodelan Spasial Tingkat Pengangguran Terbuka Kabupaten/Kota di Pulau Sumatera Menggunakan Pendekatan Geographically Weighted Panel Regression Rahmatullah, Figo; Syafriandi, Syafriandi; Fitri, Fadhilah
Imajiner: Jurnal Matematika dan Pendidikan Matematika Vol 8, No 3 (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.v8i3.27285

Abstract

This study aims to analyze the factors affecting the Open Unemployment Rate (OUR) at the regency/city level in Sumatra Island during the 2022–2024 period by considering spatial and temporal variations. The study employs panel data obtained from Statistics Indonesia, with the Open Unemployment Rate as the dependent variable and the Human Development Index, Mean Years of Schooling, Labor Force Participation Rate, and Gross Regional Domestic Product as independent variables. Panel data regression and Geographically Weighted Panel Regression (GWPR) are applied as analytical methods. The best panel regression model is selected using the Chow and Hausman tests, which indicate that the Fixed Effect Model is the most appropriate. The Breusch–Pagan test confirms the presence of spatial heterogeneity, justifying the use of the GWPR approach. The GWPR model with an adaptive bisquare kernel weighting function and optimal bandwidth successfully captures local variations in the relationship between explanatory variables and unemployment. The results reveal that Mean Years of Schooling and Gross Regional Domestic Product have a positive effect on the Open Unemployment Rate, while the Labor Force Participation Rate has a negative effect, with varying magnitudes across regions. The GWPR model outperforms the global panel regression, achieving a coefficient of determination of 96.8%. These findings highlight the importance of incorporating spatial approaches in formulating region-specific employment policies in Sumatra Island.
Co-Authors Almuhayar, Mawanda Barokah, Bunga Miftahul Chairina Wirdiastuti Dina Fitria, Dina Dodi Vionanda Fishuri, Nufhika Ikhsan, Easbi Ketrin, Melin Wanike Maulani Meutia Rani Muhammad Faisal Nonong Amalita Permana, Dony Prima Sari, Devni Putri, Eno Dwi Putri, Fadhira Vitasha Rahmatullah, Figo Rizki Akbar Sari, Widia Kemala Syafriandi Syafriandi Tessy Octavia Mukhti Widiyanti Yenni Kurniawati Yuki Fitria Zamahsary Martha Zilrahmi, Zilrahmi