Article Per Year (5 Year)
p-Index From 2021 - 2026
10.723
P-Index
This Author published in this journals
All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Media Statistika BIMASTER Jurnal Pendidikan Matematika dan IPA Jurnal Gaussian Epsilon: Jurnal Matematika Murni dan Terapan CAUCHY: Jurnal Matematika Murni dan Aplikasi Journal of Mathematical and Fundamental Sciences Edumatsains Al-Jabar : Jurnal Pendidikan Matematika Indonesian Journal of Science and Mathematics Education BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Teorema: Teori dan Riset Matematika VOX EDUKASI: Jurnal Ilmiah Ilmu Pendidikan Jambura Journal of Mathematics GERVASI: Jurnal Pengabdian kepada Masyarakat InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal AlphaEuclidEdu Jurnal Diferensial Tensor: Pure and Applied Mathematics Journal Jurnal Abdimas Bina Bangsa Komatika: Jurnal Pengabdian Kepada Masyarakat Jurnal Eurekamatika
Yundari, Yundari
Jurusan Matematika FMIPA Universtas Tanjungpura
Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

Published : 107 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 107 Documents
Search

 7   8   9   10   11 
PERAMALAN CURAH HUJAN MENGGUNAKAN SPACE TIME AUTOREGRESSIVE (STAR) DENGAN BOBOT KERNEL Ningrum, Runi Aisyah Diyah; Huda, Nur’ainul Miftahul; Yundari, Yundari
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 13, No 6 (2024): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v13i6.90509

Abstract

Model Space Time Autoregressive (STAR) dimanfaatkan untuk memetakan data tidak hanya ditentukan oleh waktu, tetapi juga oleh tempat. Salah satu karakteristik unik dari model STAR adalah penggunaan matriks bobot yang menjelaskan hubungan geografis. Dalam penelitian ini, matriks bobot yang digunakan yaitu bobot gaussian kernel, bisquare kernel, dan tricube kernel. Studi kasus yang digunakan adalah data curah hujan di tiga lokasi di Kalimantan Barat, yaitu Pontianak, Sambas, dan Kubu Raya, selama periode Januari 2019 sampai dengan Desember 2023. Perkembangan curah hujan di setiap kota tidak hanya dipengaruhi oleh kondisi di waktu sebelumnya tetapi juga oleh kondisi di lokasi lainnya. Penelitian ini bertujuan untuk membandingkan kinerja tiga jenis bobot lokasi yang berbeda dan menentukan model STAR terbaik berdasarkan nilai MAPE, AIC, dan RMSE paling kecil. Model STAR yang digunakan dibatasi pada orde STAR (1;1). Tahapan-tahapan yang dilakukan meliputi uji stasioneritas data, estimasi parameter, dan uji diagnostik untuk masing-masing model STAR. Hasil penelitian menunjukkan bahwa model dengan bobot tricube kernel merupakan model yang terbaik, karena memiliki nilai MAPE, AIC, dan RMSE paling kecil.  Kata Kunci: residual, stasioner, uji diagnostik
PEMODELAN GEOMETRIC BROWNIAN MOTION DAN PERHITUNGAN RISIKO DENGAN ADJUSTED EXPECTED SHORTFALL PADA SAHAM GOLD Putra, Fajar Rahmana; Yundari, Yundari; Sulistianingsih, Evy
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 14, No 1 (2025): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v14i1.91868

Abstract

Dalam pengembalian keputusan investasi, evaluasi risiko merupakan komponen penting dalam pengambilan keputusan investasi. Untuk memahami dan mengelola risiko tersebut, diperlukan pendekatan yang mampu memprediksi pergerakan harga saham serta mengestimasi potensi kerugian. Penelitian ini bertujuan untuk memodelkan pergerakan harga saham dengan memanfaatkan model stokastik Geometric Brownian Motion (GBM) dan hasil ukuran risiko kerugian melalui perbandingan antara Value at Risk (VaR) dan Adjusted Expected Shortfall (Adj-ES). Data yang digunakan adalah harga penutupan saham Gold (GC=F) pada periode September 2023 hingga Agustus 2024. Model GBM diterapkan pada penelitian ini untuk mensimulasikan pergerakan harga saham sebanyak 1000 kali, berdasarkan data volatilitas dan drift yang diperoleh dari data in-sample, di mana drift mencerminkan tingkat pertumbuhan ekspektasi log-return aset dalam jangka waktu tertentu. Setelah menghitung parameter volatilitas dan drift, dilakukan simulasi dengan model GBM pada data out sample. Risiko diukur menggunakan VaR dan Adj-ES dengan tingkat kepercayaan 95%, yang kemudian divalidasi melalui uji backtesting. Hasil analisis menunjukkan bahwa model GBM memiliki tingkat akurasi yang baik, dengan nilai MAPE terkecil sebesar 1,04% serta diperoleh volatilitas sebesar 0,1391 dan drift sebesar 0,2632. Perkiraan kerugian maksimum berdasarkan VaR menunjukkan nilai 1,51%, sedangkan menggunakan Adj-ES menghasilkan estimasi kerugian maksimum sebesar 2,23%. Penelitian ini juga menguji validitas VaR dan Adj-ES pada tingkat kepercayaan 95% melalui metode backtesting menggunakan Uji Kupiec. Berdasarkan hasil uji, VaR dan Adj-ES dinyatakan valid karena nilai Likelihood Ratio (LR) masing-masing 0,09 dan 0,11 lebih kecil dari nilai kritis Chi-Square sebesar 3,84.                                                                                                         Kata Kunci : Stokastik, Value at Risk, Backtesting, Kupiec.
IMPLEMENTASI MODEL MIXED GEOGRAPHICALLY WEIGHTED REGRESSION (MGWR) DALAM PERHITUNGAN JUMLAH PENDUDUK MISKIN DI PROVINSI KALIMANTAN BARAT Ramadhan, Rahul; Yundari, Yundari; Helmi, Helmi
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 14, No 2 (2025): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v14i2.92352

Abstract

Di Indonesia, termasuk di Kalimantan Barat, Kemiskinan merupakan masalah yang kompleks dan multidimensional karena dipengaruhi oleh berbagai faktor. Tantangan ini semakin kompleks karena dipengaruhi oleh faktor spasial dan karakteristik lokal seperti kondisi geografis yang beragam, tingkat pengangguran, dan disparitas pembangunan antarwilayah. Sehingga pendekatan analitis yang mampu menangkap keragaman spasial dan karakteristik lokal menjadi hal penting. Model Mixed Geographically Weighted Regression (MGWR) merupakan salah satu pendekatan yang bisa digunakan dalam menganalisis variasi spasial dalam pengaruh faktor-faktor tertentu terhadap jumlah penduduk miskin. Beberapa variabel mungkin memiliki efek yang stabil di seluruh wilayah atau dikatakan bersifat global, sedangkan variabel lain bisa memiliki efek yang bervariasi di setiap lokasi atau dikatakan bersifat lokal. Tujuan dari penelitian adalah menganalisis model MGWR, menerapkan model MGWR dan membandingkan Regresi Linier Berganda, GWR dan MGWR. Langkah-langkah yang dilakukan adalah menganalisis deskriptif data, melakukan uji heterokedastisitas, melalukan analisis terhadap regresi model GWR, melakukan analisis terhadap regresi model MGWR, dan melakukan perbandingan antara GWR dengan MGWR untuk melihat nilai AIC. Berdasarkan hasil analisis diperoleh bahwa variabel yang bersifat global yaitu persentase penduduk (X1) dan upah minimum kabupaten (X3). Sedangkan yang bersifat lokal yaitu tingkat pengangguran terbuka (X2), dan tingkat pendidikan terakhir (X4). Pada Tingkat pengangguran terbuka berpengaruh signifikan secara lokal pada kabupaten Landak, Sanggau, Sintang, Sekadau, Melawi, Kayong Utara, dan Kota Pontianak. Sedangkan variabel tingkat pendidikan terakhir tidak signifikan berpengaruh pada kabupaten Bengkayang, Ketapang dan Sekadau. Hasil perbandingan antara model regresi linier berganda, Geographically Weighted Regression (GWR), Mixed Geographically Weighted Regression (MGWR) diperoleh bahwa model MGWR yang terbaik karena memiliki nilai AIC terkecil sebesar 301,9651.  Kata Kunci : Spasial, AIC, regresi, GWR
Creating a diagnostic test to assess conceptual understanding of fraction operations Juwita, Dia Prima; T, Ahmad Yani; Yundari, Yundari
Al-Jabar: Jurnal Pendidikan Matematika Vol 15 No 2 (2024): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v15i2.22680

Abstract

Background: Fraction operations are fundamental in mathematics education, yet many students face challenges in mastering these concepts. Effective assessment tools are crucial for identifying areas of difficulty and guiding instructional improvements.Aim: This study aims to develop a diagnostic test to accurately measure the conceptual understanding of fraction operations among students in the Elementary School Teacher Education Program (PGSD) at STKIP Melawi.Method: Utilizing a research and development approach with mixed methods, this study follows Ebel's Model of Test Development. The process includes item selection, validation, and reliability testing, involving both qualitative and quantitative analyses.Results: The developed diagnostic test demonstrated strong validity and reliability metrics. Analysis revealed that students commonly struggle with both the conceptual and procedural aspects of fraction operations. Frequent errors were noted in the interpretation and execution of solution steps. No student achieved the highest possible score, indicating significant gaps in understanding. The N-Gain analysis showed an average score of 0.5610, suggesting medium to high effectiveness in identifying learning challenges, with individual scores ranging from 0.32 to 0.93.Conclusion: The diagnostic test developed in this study provides a robust tool for assessing the conceptual understanding of fraction operations. It highlights specific areas where students encounter difficulties, offering valuable insights for targeted instructional strategies. Integrating this diagnostic test into the curriculum can enhance the ability to diagnose and address learning obstacles, ultimately improving mathematics education outcomes.
Enhancing senior high school students' visual imagery creativity in geometry through Geoboard Hengki, Marius; Jamiah, Yulis; Yundari, Yundari
Indonesian Journal of Science and Mathematics Education Vol. 7 No. 2 (2024): Indonesian Journal of Science and Mathematics Education
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijsme.v7i2.22624

Abstract

This study examines innovative learning tools to enhance students' understanding of geometry subjects. The research aims to describe the use of Geoboards in fostering the visual imagery creativity of 12th-grade students in geometry learning. The method used is descriptive qualitative, with subjects consisting of six students selected through purposive sampling. The results show that students with high visual imagery creativity possess good abilities in fluency, diversity, originality, and detail aspects. Students with moderate creativity still require guidance, while students with low creativity experience difficulties and need intensive practice. Using Geoboards has proven effective in enhancing visual imagery creativity, making learning more interesting and meaningful, and facilitating understanding of three-dimensional geometric concepts. The implications of this research suggest that Geoboards can be an effective learning tool in mathematics education.
PENERAPAN METODE GEOGRAPHICALLY WEIGHTED PANEL REGRESSION (GWPR) PADA KASUS KEMISKINAN DI INDONESIA Martha, Shantika; Yundari, Yundari; Rizki, Setyo Wira; Tamtama, Ray
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 2 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (392.215 KB) | DOI: 10.30598/barekengvol15iss2pp241-248

Abstract

To analyze the factor affecting poverty during several periods by considering some geographical factors, we can use a geographically weighted panel regression (GWPR) method. GWPR is a combination of the geographically weighted regression (GWR) model and the panel regression model. The research conducts to identify the factors affecting the percentage of poor people in 34 provinces in Indonesia during 2015-2019. The results show that a suitable GWPR model is a fixed-effect model (FEM) with an exponential adaptive kernel function. Referring to the model, the province is divided into four groups based on variables having a significant effect on the percentage of poor people. That factors causing the poor people percentage in Indonesia are the poor people percentage aged above 15 years old and unemployment, the people percentage aged above 15 years old and employed in the agricultural sector, the literacy rate of the poor aged between 15 to 55 years old, and the life expectancy rate. Keywords: fixed effect model, exponential adaptive kernel.
ANALYSIS OF THE VACCINATION'S IMPACT ON THE INCREASE IN COVID-19’S DAILY NEW AND RECOVERED CASES USING THE VECTOR AUTOREGRESSIVE (VAR) MODEL (CASE STUDY: WEST KALIMANTAN) Yundari, Yundari; Huda, Nur'ainul Miftahul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (738.663 KB) | DOI: 10.30598/barekengvol16iss3pp761-770

Abstract

One of the efforts to suppress the increasing number of COVID-19 cases is the government's provision of a COVID-19 vaccine. This study examines the effect of the number of people who have been vaccinated, the first dose of vaccine, on the addition of new cases and cured cases. The three variables were analysed simultaneously using the help of the Vector Autoregressive (VAR) model. The data is on the number of new, recovered cases and people vaccinated per day from January 13 to December 30, 2021, in West Kalimantan Province. The main steps in this study are order identification, parameter estimation, and interpretation of the results. In this study, the order selection of the VAR model is limited to a maximum of the fourth order. Parameter estimation uses the Ordinary Least Square (OLS) method from several possible orders. Furthermore, the model selection is based on the smallest AIC and BIC values. The result is that the second-order VAR model has the smallest AIC and BIC values, so this model is said to be the best model. The interpretation of the equation obtained is that 74.1% of the factors adding new cases, the number of people being vaccinated, and the addition of cured cases at one and two last times affect the addition of new cases on that day. Meanwhile, the addition of new cases today was only influenced by 42.2% by new cases, the number of people being vaccinated, and the addition of recovered cases in the previous one and two days.
MODIFIED WEIGHT MATRIX USING PRIM’S ALGORITHM IN MINIMUM SPANNING TREE (MST) APROACH FOR GSTAR(1;1) MODEL Huda, Nur'ainul Miftahul; Fran, Fransiskus; Yundari, Yundari; Fikadila, Lisa; Safitri, Fauziah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (663.366 KB) | DOI: 10.30598/barekengvol17iss1pp0263-0274

Abstract

The Generalized Space-Time Autoregressive (GSTAR) model is able to utilize modeling of both space and time simultaneously. The existence of a weight matrix is one of the aspects that established this model. The matrix illustrates the spatial impact that occurs between locations. In this research, a modified weight matrix is presented using the Minimum Spanning Tree approach of graph theory. Prim's algorithm is utilized for calculation here. Not only does the modified weight matrix depend distance, but also highlights the correlation. It makes the modified weight matrix unique. Before starting Prim's algorithm, the correlation is first utilized as an input in forming the initial graph. Following that, find the graph with the least of MST weight. Afterwards, the graph is described utilizing weight matrix, which is applied to the normalization process. Following this, the GSTAR(1;1) modelling process is carried out, beginning with estimating the parameters and then forecasting. The case study is Covid-19 cases that occurred on Java Island between July 2020 (when early Covid-19 entered Indonesia) and the beginning of January 2021. The aim of the research is to model the Covid-19 cases using modified weights and to predict the following five times. The outcome is a GSTAR(1;1) model with modified weights can captures both temporal and spatial patterns. The accuracy of the model is achieved for both the training data and the testing data by the MAPE computations, which yielded of 11.40% and 21.57%, respectively. Predictions are also obtained for each province in the next five times.
A COMPLETION THEOREM FOR COMPLEX VALUED S-METRIC SPACE Kiftiah, Mariatul; Yundari, Yundari; Suryani, Suryani; Lauren, Nover
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2747-2756

Abstract

Any complex valued S-metric space where each Cauchy sequence converges to a point in this space is said to be complete. However, there are complex valued S-metric spaces that are incomplete but can be completed. A completion of a complex valued S-metric space ( is defined as a complete complex valued S-metric space with an isometry such that is dense in In this paper, we prove the existence of a completion for a complex valued S-metric space. The completion is constructed using the quotient space of Cauchy sequence equivalence classes within a complex valued S-metric space. This construction ensures that the new space preserves the essential properties of the original S-metric space while being completeness. Furthermore, isometry and denseness are redefined regarding a complex valued S-metric space, generalizing those established in a complex valued metric space. In addition, an example is also presented to illustrate the concept, demonstrating how to find a unique completion of a complex valued S-metric space.
DEVELOPMENT OF INSTRUCTIONAL MATERIALS TO IMPROVE SKILLS IN OPERATING INTEGERS USING THE ARTICULATE STORYLINE APPLICATION Arizal, Arizal; Suratman, Dede; Yundari, Yundari; Rif'at, Mohammad; Hamdani, Hamdani
Jurnal Pendidikan Matematika dan IPA Vol 16, No 3 (2025): September 2025
Publisher : Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jpmipa.v16i3.84206

Abstract

This study was conducted to address the low level of students' skills in performing operations with integers. This issue arose because, since the Covid-19 pandemic, many elementary school students have experienced learning loss, which has impacted their learning processes upon entering secondary school. Therefore, to optimize classroom learning time, students were also provided with opportunities for independent learning using interactive instructional materials. This study employed a quantitative development method using the ADDIE model and involved 50 seventh-grade students from SMPN 1 Lembah Bawang and SMPN 3 Lembah Bawang. Data collection techniques included tests and interviews using questionnaires. The collected data were analyzed by comparing pre-test and post-test results, as well as calculating effect size to determine the extent of influence after using the instructional materials. The study resulted in the development of instructional materials validated by experts and shown to improve students' skills in integer operations. After using the developed materials, more than 50% of students demonstrated high proficiency in operating integers, compared to 66% who had low proficiency beforehand. The resulting effect sizes after using the instructional materials were categorized as medium (d = 0.7) and high (d = 1.0). It can thus be concluded that the developed instructional materials effectively enhance students"™ skills in performing integer operations and are suitable for production and use in secondary schools.
Co-Authors Adrian, Ferry Ahmad Yani T Alexander Ananda, Adelia Angraini, Wanda Aprizkiyandari, Siti Ariani, Prisilia Arizal, Arizal Asyrad, Adam Ayu Lestari Ayu Sri Utami Bambang Poniman Barita Riana Sitours Bayu Prihandono Brella Glysentia Vilgalita Chintya, Yuni Daniel Happy Putra Daska, Hipin Dea Rizki Darmawanti Dede Suratman Deni Winda Sari Desi Desi Ditanti Putri Shofia Eka Febrianti, Eka Eligia Helvianti Tri Lina P Elishabet Yohana Enis Rahayu Erlando Erlando Ervina Febyolga Evangelista, Gitta Evi Novian Evi Noviani Evy Sulistianingsih Fajria, Intan Luthfiani Fansiskus Fran Fikadila, Lisa Firhan Januardi Firmansyah, Dimas Fran, Fransiskus Fransiskus Fran Fransiskus Fran Hamdani Hamdani Hanssen, Calvin Helmi Helmi Helmi Helmi Helmi Helmi Helmi Hendra Perdana Hengki, Marius Henny Priandini Amalia Huda, Nur'ainul Miftahul HUDA, NUR’AINUL MIFTAHUL Huda, Nur’ainul Miftahul Ikbal Muhaimin Jonathan, Ryan Juwita, Dia Prima Laksono Trisnantoro Lauren, Nover Laurens Paskhia Dirda Rusanditia Lina Astuti Mariatul Kiftiah Martha, Shantika Meisita, Cheril Meliana Pasaribu Melinda Mareta Sari Mohamad Rif'at Mudinillah, Adam Muhammad Ilyas Mujiarti, Eka May Muslimah (F54210032) Nadia Putri Kurniawati Neno Juli Triami Neva Satyahadewi Nilamsari Kusumastuti Ningrum, Runi Aisyah Diyah Novia Kristefany Kabang Nurfadilah, Kori’ah NURFITRI IMRO’AH Nurfitri Im’roah Nurliantika, Nurliantika NUR’AINUL MIFTAHUL HUDA Pranata Anggi Priyatna, Tegar Rama Puspita, Urfila Dian Putra, Fajar Rahmana Putri Romanda Rachmawati, Febby Rahmah, Mhaulia Ramadhan, Rahul Ramadhanti, Tasya Redika Rif'at, Mohammad Rifatullah, Rohit Riski Apriadi Rivaldi, Syahrul Rizki, Setyo Wira Ryan Jonathan Safitri, Fauziah Sasqia Aklysta Antaristi Setyo Wira Rizki Setyo Wira Rizki Shantika Martha Shantika Martha Silvia, Elma Silvy Heriyanti Suryani Suryani Takuan, Julianus Tambunan, Ayu Oktavia Tamtama, Ray Udjianna Sekteria Pasaribu Utriweni Mukhaiyar Venti, Monalisa Wele, Bruno Sala Winanda Epriyanti Yudhi Yulis Jamiah Zada Almira Zubaidah Zubaidah