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All Journal Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Sains Matematika dan Statistika Science and Technology Indonesia NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Jurnal Matematika: MANTIK Jurnal Elementer (Elektro dan Mesin Terapan) Desimal: Jurnal Matematika Syntax Literate: Jurnal Ilmiah Indonesia JWP (Jurnal Wacana Politik) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications Buletin Ilmiah Nagari Membangun Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Aplikasi Statistika & Komputasi Statistik M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jurnal Matematika UNAND Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Journal of Science and Technology Makara Journal of Health Research Lattice Journal : Journal of Mathematics Education and Applied STATISTIKA Limits: Journal of Mathematics and Its Applications
Yanuar, Ferra
Universitas Andalas
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Peningkatan Minat dan Kemampuan Santri Pondok Pesantren Al Ashry di Bidang Matematika Melalui Pendekatan Small Group Discussion Izzati Rahmi HG; Admi Nazra; Hazmira Yozza; Ferra Yanuar; Budi Rudianto; Susila Bahri; Narwen Narwen; Maiyastri Maiyastri; Haripamyu Haripamyu; Riri Lestari; Yudiantri Asdi; Efendi Efendi; Dodi Devianto; Zulakmal Zulakmal; Ahmad Iqbal Baqi; Arrival Rince Putri; Radhiatul Husna; Nova Noliza Bakar; Mawanda Almuhayar; Ikhlas Pratama Sandi
Warta Pengabdian Andalas Vol 30 No 4 (2023)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jwa.30.4.715-721.2023

Abstract

Mathematics is a field of study needed in various aspects of life. Accordingly, mathematics should always be considered a compulsory subject at every level of education, including in Islamic Boarding Schools. The fact shows that implementing mathematics learning in several schools needs to run optimally, especially in schools lacking teachers and limited educational facilities and infrastructure, such as The Al Ashry Islamic Boarding School, at the secondary level in Padang. This condition indicates that it is necessary to assist other parties to help students in their mathematics learning process. For this reason, the community service team of The Mathematics and Science Data Department of Andalas University conducted an intensive mathematics tutoring activity for The Al-Asyri Boarding School students. The activity carried out during September-December 2022 combined the lecture and the small group discussion approach. From the evaluation delivered by the students at the end of the activity, it can be concluded that this activity increased students’ interest, motivation, efficacy, and understanding of mathematics subject.
PEMODELAN JUMLAH PENUMPANG PESAWAT DI BANDARA SOEKARNO-HATTA MENGGUNAKAN MODEL HYBRiD SARIMA-FTSMC M. Pio Hidayatullah; Ferra Yanuar; Dodi Devianto
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 3 (2023): 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.v4i3.513

Abstract

The aim of this research is to model the number of airplane passengers at Soelkarno-Hatta airport using a model hybrid SARIMA-FTSMC. The data used in this research is secondary data in the form of data on the number of airplane passengers at Soekarno-Hatta airport from January 2010 to May 2023 which was obtained via the websitebps.go.id. After analyzing the data, the best model was obtained in the SARIMA model, namely SARIMA(1,1,1)(0,1,1)12. Then based on the residual value from the processed data SARIMA will be modeled using the FTSMC model. Next, the residual value of SARIMA(1,1,1)(0,1,1)12 which has been modeled using the FTSMC model is added to the modeling value from SARIMA (1,1,1)(0,1,1)12 known as a modelhybrid SARIMA-FTSMC, with the aim of obtaining a higher level of accuracy or smaller error compared to the SARIMA model. After that, the accuracy level of the model is calculatedhybrid SARIMA-FTSMC uses MAD, MSE, and MAPE. In this research, the level of accuracy of the model was very good, this was shown by the MAPE value being less than 20%.
ESTIMASI PARAMETER BERDISTRIBUSI PARETO MODEL SURVIVAL DENGAN METODE BAYESIAN PRECAUTIONARY LOSS FUNCTION Ridhatul Ilahi; Ferra Yanuar; Dodi Devianto
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): 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.v5i1.590

Abstract

The aim of this research is to determine the estimation of the scale parameters (θ) of a Pareto distributed survival model with known shape parameters (λ) using the Bayesian Precautionary Loss Function method using the Gamma prior. The data used in this research is secondary data in the form of data on the length of stay for Coronary Heart Disease patients from January 2023 - August 2023 obtained from M. Zein Painan Regional Hospital. Estimation of survival function parameters with the Bayesian Precautionary Loss Function method from the Pareto distribution using Gamma priors obtained  and the value of the survival function with the Bayesian Precautionary Loss Function method calculates the chances of living in cases of Coronary Heart Disease sufferers to be higher. And will be evaluated using the AIC and BIC methods
ANALISIS PERTAMBAHAN TINGGI BADAN BALITA STUNTING DI PROVINSI SUMATERA BARAT MENGGUNAKAN METODE REGRESI KUANTIL BINER BAYESIAN Cintya Mukti; Ferra Yanuar; Dodi Devianto
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 1 (2024): 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.v5i1.591

Abstract

Stunting is one of the national health problems in Indonesia, where children experience growth failure. This study aims to construct a model for the classification of height gain of stunting toddlers in West Sumatra Province using the Bayesian binary quantile regression method. Quantile analysis is used in the Bayesian concept to produce more effective and natural estimates, especially for data that are not normally distributed. In the Bayesian approach, the Asymmetric Laplace Distribution (ALD) is used in determining the likelihood function as the basis for forming the posterior distribution used in the parameter estimation process. Bayesian binary quantile regression is an extension of quantile regression where the scale of the dependent variable used is binary. The research data used is data on 1000 stunting toddlers in West Sumatra Province in August 2021 and February 2022. In this study, it was found that the Bayesian binary quantile regression method at quantile 0.50 was the best conjecture model in classifying the level of height gain of stunting toddlers in West Sumatra Province. The criteria for model goodness are based on the greatest accuracy value. Factors that are significant in influencing the height gain of stunting toddlers in West Sumatra Province are birth weight, exclusive breastfeeding, and immunization
UPAYA MEMBANGUN KARAKTER SISWA MELALUI INTEGRASI KONSEP HIMPUNAN DAN AL-QUR’AN DALAM PEMBELAJARAN MATEMATIKA Izzati Rahmi HG; Admi Nazra; Budi Rudianto; Mahdhivan Syafwan; Ferra Yanuar; Hazmira Yozza; Narwen Narwen; Monika Rianti Helmi; Maiyastri Maiyastri
BULETIN ILMIAH NAGARI MEMBANGUN Vol 6 No 4 (2023)
Publisher : LPPM (Institute for Research and Community Services) Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/bina.v7i4.538

Abstract

The Quran is the source of all knowledge, including mathematics. On the other hand, mathematics is closely related to everyday life and the development of other fields of knowledge. Mathematics is one of the disciplines closely connected to the verses of the Quran. Mathematics education is expected to improve to meet the advancements in time and technology continually. It is also anticipated that mathematics education can build the character of each student through religious values. This activity aims to introduce the concept of sets integrated with the content of verses found in the Quran. The activity was conducted as an online Zoom meeting and YouTube streaming seminar. Participants included mathematics lecturers, teachers, and students from Islamic junior and senior high schools from ten provinces in Indonesia. The event was titled "The Quran and Set Theory" and received high appreciation from the seminar participants. This was evident from the enthusiastic participation and numerous questions raised during the Q&A session. This activity has motivated teachers and lecturers to integrate the mathematical concepts learned with the Quranic verses. Teachers who participated in this activity are expected to act as agents in popularizing the method of integrated mathematics education with the content of Quranic verses, especially set theory.
Quantile Regression Analysis; Simulation Study With Violation of Normality Assumption Hasibuan, Lilis Harianti; Yanuar, Ferra; Devianto, Dodi; Maiyastri, Maiyastri
JOSTECH Journal of Science and Technology Vol 4, No 2: September 2024
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v4i2.9643

Abstract

Quantile regression is an extension method of simple linear regression whose work is to separate or divide data into certain quantiles. This method minimizes the asymmetric absolute residual and estimates the conditional quantile function. Parameter estimation in the quantile regression method does not require the parametric assumption of normality. The data in this study are generated from different distributions. The distribution of the independent variables in this study comes from the t distribution, normal and exponential distribution. Meanwhile, the error distribution comes from the chi square distribution. This research produces various models of the selected quantiles. The estimated parameter values at each quantile are almost close to the initial values set. This research found the best model at quantile 0.5 by looking at the smallest MSE value of all quantiles of 1.2662. The best model obtained is .
ESTIMASI PARAMETER DARI DISTRIBUSI LOMAX MENGGUNAKAN METODE BAYESIAN ENTROPY LOSS FUCTION Sani, Ridha Fadhila; Yanuar, Ferra; Devianto, Dodi
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 3 (2024): 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.v5i3.596

Abstract

The purpose of this research is estimating shape parameter (θ) of  Lomax distribution with known shape parameter (β). Estimating parameter of Lomax Distribution using Bayesian Entropy Loss Function method with Gamma prior as conjugate prior of parameter (θ). The data used in this research is generated data which is obtained from R-Studio. Estimating parameter with Bayesian Entropy Loss Function Method from Lomax distribution with used shape parameter (θ=1) is  and estimating parameter with Bayesian Entropy Loss Function Method from Lomax distribution with used shape parameter (θ=1,5) is . Estimating shape parameter (θ) will be evaluated used AIC, AICc, and BIC method
MODEL PERGERAKAN HARGA MINYAK MENTAH BRENT MENGGUNAKAN PENDEKATAN TIME SERIES DENGAN EFEK LONG MEMORY Ramadhani, Eza Syafri; Devianto, Dodi; Yanuar, Ferra
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 3 (2024): 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.v5i3.746

Abstract

Oil price movements are highly volatile and tend to be influenced over extended periods, often displaying long memory effect. This study utilizes the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model, a long memory model, to analyze and forecast crude oil prices using monthly Brent data from November 1998 to November 2023. The analysis confirms the presence of long memory in the Brent crude oil price data. The ARFIMA model is then developed by estimating the parameter  using the Rescaled Range Statistics (R/S) method. The best model is selected based on the lowest AIC and BIC values. The results indicate that the optimal ARFIMA model closely aligns with the actual data patterns, demonstrating its effectiveness in capturing the movements of Brent crude oil prices.
PEMODELAN JUMLAH PENUMPANG KAPAL DOMESTIK DI PELABUHAN TANJUNG PERAK MENGGUNAKAN MODEL VARIASI KALENDER SEASONAL ARIMAX Riau, Ninda Permata; Yanuar, Ferra; Devianto, Dodi
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 3 (2024): 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.v5i3.748

Abstract

Indonesia is the largest archipelagic country in the world, heavily reliant on maritime transportation, with Tanjung Perak Port being the second busiest port, playing a strategic role in East Java's economy. Analysis shows that fluctuations in the number of ship passengers at Tanjung Perak Port are influenced by seasonal patterns and calendar variations, such as spikes in passenger numbers during the Eid Al-Fitr holiday. To model these fluctuations, the SARIMAX (Seasonal ARIMA with Exogenous Variables) model is used, which accounts for both seasonal factors and exogenous variables. Results of this research show a significant relationship between the number of ship passengers and a dummy variable representing the month before and during Eid al-Fitr. The SARIMAX model used in this analysis confirms that the period leading up to and during the Eid al-Fitr celebration contributes significantly to fluctuations in passenger numbers.
PENERAPAN METODE NAÏVE BAYES CLASSIFIER DALAM MENGANALISIS SENTIMEN PADA MEDIA SOSIAL X TERHADAP PILPRES 2024 DI INDONESIA Majbur, Ridha Fauza; Yanuar, Ferra; Devianto, Dodi
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 3 (2024): 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.v5i3.794

Abstract

The purpose of this research is to analyze sentiment on social media X regarding the 2024 Presidential Election by testing data using k-fold cross validation. The data used in this study are tweets about the 2024 Presidential Election on social media X, obtained through data crawling techniques. Sentiment analysis is the process of identifying and classifying opinions, which are in text form into positive or negative sentiments. Classification methods are used to group these sentiments. One of the classification methods used in this study is the Naive Bayes Classifier (NBC). The accuracy of this NBC method is measured using k-fold cross-validation, with k = 10. The value of k = 10 was chosen for this study because it is considered to provide more stable and robust accuracy results. Based on the measurements conducted, it was found that the highest accuracy value occurred in the 10th fold, which was 92.06%. The average accuracy across all folds for the NBC method was 82.33%. This indicates that the Naive Bayes Classifier (NBC) method can classify public sentiment towards the 2024 Presidential Election with a relatively high level of accuracy.
Co-Authors Abdi Mulya Admi Nazra AMALIA DWI PUTRI Amalia Dwi Putri ANGGUN CITRA DELIMA ANNISA RAHMADIAH Arfarani Rosalindari Arrival Rince Putri Asdi, Yudiantri Astari Rahmadita ATIKAH RAHMAH PUTRI Azmi Arsa Bahri, Susila Baqi, Ahmad Iqbal Boby Canigia Budi Rudianto Catrin Muharisa Cichi Chelchillya Candra Cichi Chelchillya Candra Cici Saputri Cintya Mukti Cintya Mukti Des Welyyanti Deva, Athifa Salsabila Devianto, Dodi Dila Mulya Dina Monica DINIE ANEFI HAJARA Efendi Efendi Elfa Rafulta Ermanely Ermanely Fadilla Nisa Uttaqi Fajriyah, Rahmatika Farhah Anggana Febriyuni, Rahmi Firdawati, Firdawati FITARI RESMALANI Fitri Aulia FITRI SABRINA Gusmanely Z Harahap, Vika Pradinda Haripamyu Haripamyu Hasibuan, Lilis Harianti Hazmira Yozza Helmi, Monika Rianti Ihsan Kamal Ikhlas Pratama Sandi Indah Pratiwi Izzati Rahmi HG Izzati Rahmi HG Jenizon Jenizon Kamarni, Neng Kartini Aboo Talib @Khalid Khatimah, Havifah Husnatul Lilis Harianti Hasibuan Livia Amanda M. Pio Hidayatullah M. Rizki Oktavian Maiyastri Maiyastri, Maiyastri Majbur, Ridha Fauza Mardha Tillah Mawanda Almuhayar MEILINA DINIARI Melisa Febriyana Mesi Oktafia Meutia Fikhri MIFTAHUL JANNAH HB Mira Serma Teti Mita Oktaviani Muhammad Iqbal Muhammad Qolbi Shobri Muharisa, Catrin Mutiara Fara Nabilla Nadia Cindi Eka Putri Nadiah Ramadhani NADYA PUTRI ALISYA Nadya Putri Alisya Narwen Narwen Nayla Desviona Nova Noliza Bakar Noverina Alfiany Nurmaylina Zaja Nurwijayanti Qalbi, Latifatul Radhiatul Husna RAHMI HG, IZZATI Rahmi, Fatihatur Ramadhani, Eza Syafri Religea Reza Putri Rescha, Ratna Vrima Resti Mustika Sari Resti Nanda Yani Riau, Ninda Permata Ridhatul Ilahi Riri Lestari Riri Lestari Rudiyanto Rudiyanto, Rudiyanto SAIDAH . Sani, Ridha Fadhila Saputri, Ovi Delviyanti Sari, Putri Trisna Sarmada Sarmada Sarmada, Sarmada Selfinia, Selfinia SHINTA MUTIA KARNEVA Shinta Wulandari SHINTA YULIANA Silvia . SILVIA YUNANDA Sisi Andriani Siti Juriah SITI LATHIFAH IRMA SUMINDANG YUZAN Surya Puspita Sari, Surya Puspita Susi Marisa Syafwan, Mahdhivan Syauqi, Irfan Tari Adriana Musana Tasya Abrari Tasya Abrari Uswatul Hasanah VIKI ANDRIANI Widya Wijayanti WINDA LIDYA Winda Oktari WULANDARI, FRILIANDA Wulandari, Sintya wulandari, sisca Yanita Yanita Yosika Putri Yulmiati Yulmiati Yurinanda, Sherli Zahratul Aini Zetra, Aidinil Zetra, Aidinil Zulakmal, Zulakmal Zulhazizah .