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All Journal PROSIDING SEMINAR NASIONAL Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) JURNAL EKSAKTA PENDIDIKAN (JEP) Beta: Jurnal Tadris Matematika JURNAL EDUCATION AND DEVELOPMENT Eksakta : Berkala Ilmiah Bidang MIPA Menara Ilmu Imajiner: Jurnal Matematika dan Pendidikan Matematika Pelita Eksakta ILKOMNIKA: Journal of Computer Science and Applied Informatics Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Leibniz: Jurnal Matematika Journal of Mathematics UNP Rangkiang Mathematics Journal UNP Journal of Statistics and Data Science Indonesian Journal of Statistics and Its Applications
Nonong Amalita
Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Other

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Markov Chain Model Application for Rainfall Pattern in Padang City haniyathul husna; Dony Permana; Nonong Amalita; Fadhilah Fitri
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (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-iss3/179

Abstract

Rainfall is a natural phenomenon that includes climate variables and is observed every time in every place. Daily rainfall data is a time series data, which is random. It is a data transfer from one time to another which can be expressed as a state of light, medium, heavy or very heavy rainfall intensity. Rainfall prediction is needed for people's lives and supports the economy. In addition, rainfall prediction is an anticipation of prevention if high rain intensity will occur in a long time. One of the rainfall prediction methods that can be used is the stochastic process approach. Markov chain is part of the stochastic process that can be used for prediction of rainfall at the present time based on one previous time. The focus of this research is the application of Markov Chains for rainfall prediction. Through Markov chains, long-term opportunities for rainfall phenomena are obtained. This study will look at the rainfall pattern of Padang City using Markov chains and also to predict rainfall in Padang City. The results of predicting the weather conditions of Padang City with any rainfall conditions today are 36.9% for the chance of no rain tomorrow, 46% for the chance of light rain tomorrow, 10% for the chance of moderate rain tomorrow, 5.3% for the chance of heavy rain tomorrow, and 1.8% for the chance of very heavy rain tomorrow.The results of this study are expected to be a recommendation for parties directly involved in taking preventive measures due to rainfall.
Pengelompokan Wilayah Potensi Kebakaran Hutan dan Lahan di Pulau Sumatera Berdasarkan Titik Panas Menggunakan Metode CLARA Melda Safitri; Admi Salma; Nonong Amalita; Fadhilah Fitri
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (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-iss3/180

Abstract

Sumatera Island is one of the areas with the potential for forest and land fires in Indonesia. Sumatra Island has the largest oil palm plantation in Indonesia. The vast land area of oil palm plantations in Indonesia can increase the risk of fires due to land expansion by burning. In addition, the burning of peatlands in Sumatra can exacerbate the impact of forest and land fires. Forest and land fires on the island of Sumatra that occur every year can cause various negative impacts, indicating the need for countermeasures and prevention efforts to minimize the impact of forest and land fires. Hotspots can be used to detect fires in a region and help with prevention and countermeasures to reduce the impact of land and forest fires. Clustering the hotspot data allows one to obtain information on the presence of a fire in a given area as well as its potential status high, medium, or low. The clustering method used is the CLARA method. The CLARA method is a clustering method that breaks the dataset into groups. The advantages of the CLARA method are robust to outliers and effective for large data sets. The results of this research show that the CLARA method can be used for hotspot clustering with a silhouette coefficient of 0.53 in the use of 2 clusters. The analysis of the clustering results shows that cluster 1 is a cluster with low fire potential while cluster 2 is a cluster with high fire potential.
Vector Error Correction Model to Analyze the Impact of Exchange Rates and Money Supply on Inflation in Indonesia Faulina; Fadhilah Fitri; Nonong Amalita; Admi Salma
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (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-iss3/188

Abstract

This study analyzes inflation in Indonesia in relation to the influence of exchange rates and the money supply (M2), which pose challenges in controlling inflation amidst rapid economic growth. Data from the Ministry of Trade of the Republic of Indonesia (Kemendag) were used to investigate the relationship between exchange rates and the money supply (M2) on inflation using the Vector Error Correction Model (VECM). The results indicate that in the short term, inflation tends to decrease towards stability, with a strong exchange rate capable of reducing inflation, while an increase in the money supply slightly raises inflation. However, in the long term, inflation demonstrates a strong self-correction mechanism, with the influence of exchange rates and the money supply becoming limited. This model proves effective in forecasting inflation for the period from March to August 2024, with a Mean Absolute Percentage Error (MAPE) of 19.59%.
Pemetaan Indikator Pertumbuhan Ekonomi Di Provinsi Sumatera Barat Menggunakan Analisis Korespondensi Berganda Vidhiya Addini; Dony Permana; Nonong Amalita; Admi Salma
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (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-iss3/190

Abstract

Economic growth is a key factor in sustainable regional development. This study employs Multiple Correspondence Analysis (MCA) to explore the relationships among economic growth indicators in the districts/cities of West Sumatra Province. Data from 2022 provided by the Central Statistics Agency are used to analyze economic growth indicators, including Gross Regional Domestic Product (GRDP) at Constant Prices (X1), Human Development Index (X2), Labor Force Participation (X3), Domestic Investment (X4), Government Expenditure (X5), and Balance Fund Allocation (X6). The results of MCA reveal complex relationships among these variables, with the first and second dimensions explaining approximately 44.43% of the data variance. The MCA plots visualize clusters of districts/cities based on their economic characteristics. From these plots, it is concluded that there are disparities in economic growth indicators in West Sumatra Province, with 11 districts/cities requiring special attention to achieve equitable and sustainable economic growth. This study contributes to a deeper understanding of regional economic disparities in West Sumatra Province and their relevance to more targeted and sustainable development policies.
Metode Density Based Spatial Clustering of Applications with Noise (DBSCAN) dalam Mengelompokkan Provinsi di Indonesia Berdasarkan Kasus Kriminalitas Tahun 2022 Syifa Miftahurrahmi; Zilrahmi; Nonong Amalita; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (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-iss3/203

Abstract

Based on Central Statistics Agency 2023 data, in 2022 there was a significant increase in the number of crime cases in Indonesia compared to 2021, from 239,481 cases to 372,965 cases. The increase in the number of criminal acts occurred along with community activities that began to loosen up after the Covid-19 pandemic. The types of crimes that occur in Indonesia themselves vary, ranging from murder, theft, drug-related crimes, and others. This research will cluster provinces in Indonesia based on crime cases with certain types of crimes in 2022 using the Density Based Spatial Clustering of Applications with Noise (DBSCAN) method. The results of the study are expected to help the government and police in an effort to deal with crime in Indonesia. Clustering using the DBSCAN method produces 2 clusters with a silhouette coefficient value of 0,68. The resulting cluster is cluster 0 with noise category consisting of 5 provinces with a high number of crime cases, while cluster 1 consists of 29 provinces with a low number of crime cases.
Application of Multivariate Adaptive Regression Splines for Modeling Stunting Toddler on The Island of Java Dzakyyah Rahma; Nonong Amalita; Yenni Kurniawati; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (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-iss3/205

Abstract

Stunting is a chronic nutritional problem experienced by toddlers, characterized by a shorter body height compared to children their age. The aim of this research is to model and determine the factors that influence Stunting on The Island of Java using Multivariate Adaptive Regression Spline (MARS). MARS is a modeling method that can handle high-dimensional data. The results of this study show that the best MARS model is a combination (BF=24, MI=3, and MO=2) with a minimum GCV value of 0.9475. Based on the model, the factors that significantly influence Stunting on the island of Java are babies receiving complete basic immunization (X4), babies getting exclusive breastfeeding (X3), pregnant women getting K4 (X1), and pregnant women getting TTD (X2). The level of importance of each variable is 100%, 81.64%, 60.38%, and 43.90%. Based on research results, babies receiving complete basic immunization is the variable that most influences stunting on The Island of Java in 2021.
Regularized Ordinal Regression with LASSO: Identifying Factors in Students' Public Speaking Anxiety at Universitas Negeri Padang natasyalinggaa Natasya Dwi Ovalingga; Nonong Amalita; Yenni Kurniawati; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 2 No. 4 (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-iss4/316

Abstract

Public speaking anxiety is a common issue faced by students, particularly in academic settings. It may arise from a range of factors, including humiliation, physical appearance, preparation, audience interest, personality traits, rigid rules, unfamiliar role, negative result, and mistakes. This research seeks to determine the factors influencing different levels of public speaking anxiety among students at Universitas Negeri Padang through the application of ordinal regression with LASSO regularization. This method allows for automatic selection of significant variables and addressesmulticollinearity issues. The results indicate that eight factors influence low public speaking anxiety levels, while only six factors impact high public speaking anxiety levels. The ordinal regression model with LASSO penalty demonstrates good performance in classifying public speaking anxiety levels, achieving an accuracy of 71.33%. This study is expected to help students and educators better understand and manage public speaking anxiety, thereby enhancing public spekaing competence among students
Sentiment Analysis of The Constitutional Court Decision Regarding Changes to The Age Limit for Presidentian and Vice Presidential Candidates Using Support Vector Machine Abilya Amanda; Nonong Amalita; Dodi Vionanda; Zilrahmi
UNP Journal of Statistics and Data Science Vol. 2 No. 4 (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-iss4/321

Abstract

The Constitutional Court (MK) as a judicial institution granted a judicial review on October 16, 2023 related to the Election Law Article 169 (q) Law No.7 of 2017 number 90/PUU-XXI/2023. The Constitutional Court approved the material test, leading to changes in the age limit for presidential and vice presidential candidates. This change caused controversy because it was considered to benefit one of the candidate pairs. This research aims to see the trend of public opinion towards policy changes by the government. This research uses the Support Vector Machine (SVM) method which divides the data into two classification classes. The application of linear, Radial Bias Function (RBF), and polynomial kernels resulted in the highest accuracy of 84%. The calculation of accuracy, precision, and recall is 84%, 22%, and 90%, respectively. Based on the resulting wordcloud, Positive words indicate backing for presidential and vice presidential candidates. Meanwhile, negative sentiments express disapproval of the Constitutional Court's decision concerning the changes to the age limit requirements for presidential and vice presidential candidates.
Error Correction Model Approach for Analysis of Original Regional Income in West Sumatra Herlena Purnama Sari; Fadhilah Fitri; Nonong Amalita; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 3 No. 1 (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-iss1/332

Abstract

In this research, an error correction model approach is used, namely looking at long-term and short-termrelationships. Meanwhile, Original Regional Income (PAD) is all regional income originating from original regionaleconomic sources. Sources of Original Regional Income according to Law Number 33 of 2004 Chapter V Article 6consist of Regional Taxes, Regional Levies, Separated Regional Wealth Management Results and Other Legal PAD.because this approach uses long-term and short-term relationships, it is known that only variables x1 and x3 have along-term relationship and variables x1 and x3 have a short-term relationship. so it can be concluded that not allindependent variables have a connection with the dependent variable
Implementation of the Self Organizing Maps (SOMS) Method in Grouping Provinces in Indonesia Based on the Number of Crimes by Type of Crime Putri fajriyanti nur; Tessy Octavia Mukhti; Nonong Amalita; Admi Salma
UNP Journal of Statistics and Data Science Vol. 3 No. 1 (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-iss1/334

Abstract

Crime cases are often the main topic of daily news in various media in Indonesia. Some of these crime cases are detrimental to the surrounding community and some are detrimental and these actions cannot be avoided in human life because they have become one type of social phenomenon. To protect the community by providing a sense of security and peace, the Indonesian government, especially the police, must pay attention to conditions like this. The results of this study used the Self Organizing Maps (SOMs) method to obtain 3 clusters with the characteristics of each cluster. The first cluster with a low impact crime rate consists of 29 provinces. The second cluster with a moderate impact consists of 3 provinces showing the most dominant crime rate, namely crimes related to fraud, embezzlement, smuggling & corruption compared to other clusters. The third cluster with a high impact consists of 2 provinces with the most prominent characteristics by showing almost all indicators of the number of crimes according to the type of crime experiencing the highest average crime cases compared to other clusters.
Co-Authors Abilya Amanda Ade Eriyen Saputri Adinda Dwi Putri Aldwi Riandhoko Ali Asmar Amelia Fadila Rahman Andini Yulianti Anggi Adrian Danis Anjelisni, Nining Annisa Rizki Amalia april leniati Arnellis Arnellis Atika Ahmad Atus Amadi Putra Azwar Ananda Chairina Wirdiastuti Cindy Febrianita Denia Putri Fajrina Dewi Febiyanti Dewi Murni Dina Fitria Dina Fitria Dina Fitria, Dina Dodi Vionanda Dodi Vionanda Dony Permana Dwi Sulistiowati Dwi Sulistiowati, Dwi Dzakyyah Rahma Edwin Musdi Elita Zusti Jamaan Elsa Oktaviani Fadhilah Fitri Fadhilah Fitri Fadilah, Salwa Hifa Fajrin Putra Hanifi Fatma Yulia Sari Faulina Fayyadh Ghaly FAZHIRA ANISHA Fenni Kurnia Mutiya Fitri, Fadhilah Gezi Fajri Hamida, Zilfa Hana Rahma Trifanni Handayani, Faddiah Gusti Hanifa Hasna haniyathul husna Helma Helma Helma Helma Herlena Purnama Sari Hidayatul Fikra Huriati Khaira Ichlas Djuazva Inna Auliya Jihe Chen Juwita Juwita Khairani, Putri Rahmatun Lilis Sulistiawati Media Rosha Media Rosha Meira Parma Dewi Melda Safitri Melly Kurniawati Minora Longgom Mohammad Reza febrino Mudjiran Mudjiran Muhammad Tibri Syofyan nabillah putri Nadha Ovella Syaqhasdy Nafandra, Bunga natasyalinggaa Natasya Dwi Ovalingga Nindi Syahfitrri Nini Erdiani Nur Leli Nur Nur Fadillah Nurhizrah Gistituati Okia Dinda Kelana Oktaviani, Bernadita Permana, Dony Prida Nova Sari Puti Utari Maharani Putri fajriyanti nur Resti Febrina Retsya Lapiza Rizqia Salsabila Rusdinal Rusdinal Saddam Al Aziz Salma, Admi Sarmilah, Sarmilah Seif Adil El-Muslih Shavira Asysyifa S Sujantri Wahyuni Suparman Suparman Swithania Rizka Putri Syafriandi Syafriandi Syafriandi Syafriandi Syafriandi Syafriandi Syifa Miftahurrahmi Tamur, Maximus Tessy Octavia Mukhti Tessy Octavia Mukhti Tri Wahyuni Nurmulyati Venny Oktarinda Vidhiya Addini Viola Yuniza Wella Saputri Wilia Sondriva Wulan Septya Zulmawati Yarman Yarman, Yarman Yenni Kurniawati Yulia Pertiwi Zamahsary Martha Zilla Zalila Zilrahmi, Zilrahmi