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All Journal Media Statistika Science and Technology Indonesia Jurnal Matematika UNAND Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks STATISTIKA

Asdi, Yudiantri

Universitas Andalas

Author-ID : 3995967

Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Social Sciences Other

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Application of the T2 Hotelling Multivariate Control Chart for Online Learning Evaluation of Compulsory Statistics Courses in the Mathematics Undergraduate Study Program at Andalas University Dina Putri Lestari; IZZATI RAHMI HG; YUDIANTRI ASDI
Jurnal Matematika UNAND Vol 12, No 1 (2023)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.12.1.78-85.2023

The world of education is one aspect of life that has been affected by Covid-19, so on March 17, 2020 the Ministry of Education and Culture issued a Circular regarding online learning. Andalas University Mathematics Undergraduate Study Program is one of the study programs at Andalas University that also implements an online learning process. In this study, an online learning evaluation will be carried out based on the Mathematics Statistics I and Mathematics Statistics II courses in the Andalas University Mathematics Undergraduate Program in the odd semester 2019/2020 and the even semester 2019/2020. The analysis used to measure the success of online learning is the analysis of quality control using the T2 Hotelling control chart. In addition, an analysis of the process ability of the two courses will also be carried out. The results obtained by using the T2 Hotelling control chart are that the online learning process in the two courses is under control, while by analyzing the process ability it can be said that the online learning process in the two courses is still not working well, which means it is not fully within the limits. specifications that have been determined in the academic regulations of Andalas University.

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

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.

Peramalan Harga Minyak Mentah Dunia Menggunakan Metode Fuzzy Time Series Logika Singh Sahroni Hasibuan; Yudiantri Asdi; Admi Nazra
Jurnal Matematika UNAND Vol 13, No 1 (2024)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.13.1.66-74.2024

Minyak mentah merupakan komoditas dan sumber energi yang sangat dibutuhkan bagi pertumbuhan suatu negara. Harga minyak mentah mengalami peningkatan dan penurunan. Naiknya harga minyak mentah akan mempengaruhi perekonomian dan pasar keuangan. Sedangkan turunnya harga minyak mentah akan mengakibatkan masalah defisit anggaran yang serius bagi negara-negara pengekspor minyak. Oleh sebab itu perlu dilakukannya peramalan harga minyak mentah dunia untuk mengurangi dampak dari fluktuasi harga minyak mentah dunia tersebut. Metode peramalan yang dapat digunakan dalam meramalkan data time series harga minyak mentah dunia adalah dengan menggunakan metode fuzzy time series logika Singh. Data yang digunakan merupakan data sekunder yaitu data harga minyak mentah dunia WTI periode November 2014 hingga Juni 2022. Hasil peramalan data harga minyak mentah dunia dengan menggunakan metode tersebut kemudian diukur tingkat akurasinya menggunakan MAPE. Dari metode peramalan fuzzy time series logika Singh diperoleh nilai MAPE sebesar 0.30%. Berdasarkan hasil MAPE tersebut, peramalan harga minyak mentah dunia dengan model Singh mempunyai tingkat akurasi sangat bagus.

Modeling of Human Development Index Using Bayesian Spatial Autoregressive Approach Yanuar, Ferra; Wulandari, Sintya; Asdi, Yudiantri; Zetra, Aidinil; Haripamyu
Science and Technology Indonesia Vol. 10 No. 1 (2025): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.1.72-79

Spatial regression analysis is a technique employed to examine the relationship between independent and dependent variables in datasets that exhibit regional neighborhood influences or spatial effects. When a spatial effect exists for the independent variable, the Spatial Autoregressive (SAR) regression can be utilized. The Maximum Likelihood Estimation (MLE) is a commonly used parameter estimator for SAR. However, due to the limitations of MLE, the Bayesian method provides an alternative approach for parameter estimation. This study compares the results of SAR estimations using both MLE and Bayesian methods to determine the most accurate estimation model. Both methods were implemented in this research to model the factors affecting the Human Development Index (HDI) in East Java Province for the year 2022. The findings indicate that the Bayesian SAR offers a superior proposed model compared to the MLE SAR. The factors influencing the HDI in East Java Province in 2022 include poverty, per capita expenditure, and the presence of an upper middle-class manufacturing industry.

Peramalan Harga Minyak Mentah Dunia Menggunakan Metode Fuzzy Time Series Logika Singh Hasibuan, Sahroni; Asdi, Yudiantri; Nazra, Admi
Jurnal Matematika UNAND Vol. 13 No. 1 (2024)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.13.1.66-74.2024

Penggunaan Metode Support Vector Machine (SVM) dalam Mengidentifikasi Tingkat Keparahan Pada Kecelakaan Lalu Lintas Rahmi, Fatihatur; Ferra Yanuar; Yudiantri Asdi
Statistika Vol. 24 No. 1 (2024): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v24i1.1690

ABSTRAK Kendaraan sudah menjadi kebutuhan pokok yang digunakan semua orang untuk berpindah dari satu tempat ke tempat lain dengan cepat. Namun, bertambahnya jumlah kendaraan juga menimbulkan dampak negatif, salah satunya adalah kecelakaan. Berdasarkan data yang diperoleh dari website Badan Pusat Statistik (BPS) Sumatera Barat pada tahun 2018-2021, kasus kecelakaan terbanyak terjadi di Kota Padang yaitu sebesar 22,79% dari semua kasus kecelakaan yang terjadi di provinsi Sumatera Barat. Tingkat keparahan yang dialami korban pasca kecelakaan dikelompokkan kedalam 3 kategori yaitu korban yang mengalami luka ringan, luka berat dan meninggal dunia. Metode klasifikasi dapat digunakan untuk mengklasifikasi tingkat keparahan kecelakaan berdasarkan faktor-faktor yang mempengaruhi terjadinya kecelakaan. Salah satu metode yang dapat digunakan adalah metode Support Vector Machine (SVM). SVM adalah suatu learning machine yang digunakan untuk mengklasifikasi data secara statistika dalam ruang fitur berdimensi tinggi dan solusi yang dihasilkan dari klasifikasi menggunakan SVM bersifat sama untuk setiap percobaan yang dilakukan. Pada penelitian ini akan digunakan klasifikasi dengan SVM multiclass dengan metode one againts one (satu lawan satu) dengan dua fungsi kernel yang selanjutnya akan dilakukan perbandingan kualitas model berdasarkan akurasi, nilai APER dan F1-score. Data yang digunakan pada penelitian ini adalah data kecelakaan yang dialami pengendara sepeda motor di kota Padang pada bulan Januari-Maret 2022. Hasil penelitian menunjukkan bahwa penggunaan kernel RBF lebih baik dibanding kernel linear dengan tingkat akurasi sebesar 94,62% dengan nilai APER sebesar 5,38% dan diperoleh F1-score untuk kategori luka ringan sebesar 97,07%, luka berat sebesar 59,90% dan meninggal dunia sebesar 80%. ABSTRACT Transportation has become a basic necessity that everyone uses to move from one place to another quickly. However, the increasing number of transportation also has negative impacts, one of them was a traffic accident. According to BPS, the highest number of accidents occurred in Padang city, which was around 22.79% of the total cases that occurred in West Sumatra. The classification method can be used to classify the severity of accidents based on the factors that influence the occurrence of accidents. One method that can be used is the Support Vector Machine (SVM). SVM is a learning machine that is used to classify data statistically in a high-dimensional feature space and the solution resulting from classification using SVM is the same for every experiment carried out. In this research, multiclass SVM classification will be used with the one-against-one method with two kernel functions, then the model quality will be calculated based on accuracy, APER value and F1 score. The data used in this research is traffic accidents by motorcyclists in Padang City in January-March 2022. The results of the research show that the RBF kernel is better than the linear kernel with an accuracy level is 94.62%, an APER value is 5.38% and a F1-score for the minor injuries category is 97.07%, while serious injuries and deaths are 59.90% and 80%.

ANALYSIS OF SOLVING THE BLACK-SCHOLES EQUATION USING THE FINITE DIFFERENCE METHOD WITH A NON-UNIFORM GRID Bulandari, Manisya; Syafwan, Mahdhivan; Asdi, Yudiantri
Jurnal Matematika UNAND Vol. 14 No. 4 (2025)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.14.4.451-462.2025

Artikel ini mengimplementasikan metode beda hingga dengan skema eksplisit berbasis grid tidak seragam pada persamaan Black–Scholes untuk menghitung harga opsi call Eropa. Skema diturunkan menggunakan deret Taylor sehingga diperoleh sistem persamaan beda yang kemudian ditransformasikan ke dalam bentuk matriks dan diselesaikan secara rekursif melalui pemrograman Matlab. Berdasarkan simulasi numerik untuk nilai-nilai parameter tertentu, hasil yang diperoleh menunjukkan bahwa skema beda hingga dengan grid tidak seragam menghasilkan solusi yang lebih akurat dibandingkan grid seragam. Galat relatif lebih besar untuk harga saham yang berada di sekitar harga pelaksanaan, tetapi dapat dikurangi secara signifikan melalui penggunaan grid tidak seragam. Selain itu, pendekatan grid tidak seragam memberikan efisiensi komputasi yang lebih baik dibandingkan skema seragam.

Co-Authors Adellara Mutya R Admi Nazra Agni Horti Maharani ALEX MARDIANA Arrival Rince Putri Awanda Amelia Maron AYU ALIFAH Azmi Arsa Bahri, Susila Baqi, Ahmad Iqbal Bulandari, Manisya DEBY CINTYA RIZAL Degika Widya Tama Devianto, Dodi Dila Mulya Dina Maulidya Dina Putri Lestari DONI PUTRA EFENDI . Efendi Efendi Eko Fachrozi Putra ELSA FEBRIANI Elvi Yati Evan Ilham Zulheri Falin Tristanti Ayu FANNY PRIMANDA PITER Fatihatur Ramadhani Ginal Reski Hari Samadi Haripamyu Haripamyu Hasibuan, Sahroni Hazmira Yozza Ikhlas Pratama Sandi Isnani Isnani Karina Foresty Khaulah Binti Afrinaldi Lolita Amelia Maisan Nusa Putri Maiyastri, Maiyastri Mawanda Almuhayar Meutia Fikhri Mita Oktaviani Mutiara Laily Ramadhany Nanda Prasetya Narwen Narwen Nila Choirotunnisa Nova Noliza Bakar Nur Elvi Sahra Nurwijayanti Olivia Atinri Prawati Ningsih Putri Atika Putri Putri PUTRI RIZKA ATIKA YUSLI Radhiatul Husna Rahmi, Fatihatur RANDA PRATAMA SURIANTO Refnaldo Refnaldo Resti Mustika Sari RESTY OKTAVIANI Riri Lestari RIZKI FITRAH Sahroni Hasibuan Sari, Putri Trisna SHINTA YULIANA Silmiati Silmiati Sisi Andriani Sovia Marhamah SUCHI RACHMADANY Syafwan, Mahdhivan Tari Adriana Musana VIKI ANDRIANI William Huda Wulandari, Sintya Yanuar, Ferra Zetra, Aidinil Zulakmal, Zulakmal

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