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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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Fuzzy K-Nearest Neighbor to Predict Rainfall in Padang Pariaman District Annisa Rizki Amalia; Nonong Amalita; Yenni Kurniawati; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 2 No. 1 (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-iss1/126

Abstract

Information about rainfall levels at a time and in a region is very important because rainfall influences human activities. Rainfall is the amount of water that falls to the earth in a certain period of time, measured in millimeters. One piece of information related to rainfall is daily rainfall predictions. In this study, an attempt was made to classify daily rainfall at the Padang Pariaman climatology station into 5 categories, namely very light rain, light rain, moderate rain, heavy rain and very heavy rain. There are 4 weather parameters used, namely air temperature, humidity, wind speed and duration of sunlight. One of the methods used to predict rainfall is data mining, a computer learning to analyze data automatically thus obtaining a perfect new model. One of the best prediction algorithms in data mining is Fuzzy K-Nearest Neighbor (FK-NN). FK-NN uses the largest membership degree value of the test data in each class to predict the class. The number of sample classes for rainfall data in Padang Pariaman Regency has an imbalance class. To overcome the imbalance class, Synthetic Minority Over-sampling Technique (SMOTE) method is used to generate minority data as much as majority data. The results of this study by using FK-NN classification with 343 test data, parameters K = 12, and euclidean distance is quite good at the accuracy level of 76,38%..
Penerapan Algoritma Naive Bayes untuk Klasifikasi Demam Berdarah Dengue di RSUD dr. Achmad Darwis Viola Yuniza; Atus Amadi Putra; Nonong Amalita; Fadhilah Fitri
UNP Journal of Statistics and Data Science Vol. 2 No. 1 (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-iss1/128

Abstract

  Dengue fever is a disease transmitted by the bite of the Aedes aegypti mosquito. Central Agency of Statistic of Lima Puluh Kota District reported that the morbidity rate of this disease was 14.40% per 100,000 population, which was higher than the previous year's morbidity rate of 3.30% per 100,000 population. The main symptoms of this disease are fever lasting 2-7 days, muscle and joint pain with or without rash, dizziness, and even vomiting blood. Dengue infection can cause various clinical symptoms ranging from dengue fever, dengue hemorrhagic fever to dengue shock syndrome. Therefore, a classification method is needed to help and facilitate early diagnosis of this disease. The method used is the Naive Bayes algorithm by classifying the positive and negative patients with dengue fever. The purpose of this research is to determine the classification of patients with dengue fever disease and the accuracy of using the Naive Bayes algorithm. The results of the analysis stated that the Naïve Bayes model successfully classified patients into 12  Dengue fever positive patients and 22  Dengue fever negative patients based on 34 testing data. The accuracy of the model is 91,18%, which shows that the model is very good  in classifying Dengue fever patients.
Forecasting Gold Prices in Indonesia using Support Vector Regression with the Grid Search Algorithm Nindi Syahfitrri; Nonong Amalita; Dodi Vionanda; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 2 No. 1 (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-iss1/145

Abstract

Investment is an effort to increase economic growth in Indonesia.  A popular investment in the community is gold investment.  The value of gold investments tends to increase but is not immune from price fluctuations, therefore it is important to forecast the price of gold in Indonesia. The method that can be used to make this forecast is Support Vector Regression (SVR).  SVR is a method that looks for a function that has a deviation of no more than ε to get the target value from all training data. The best SVR model with a linear kernel was obtained from a combination of parameters C=0,0625 and ε=0,001 with a RMSE value of 0,19734 and a value of 0,974112.  So, the SVR method is appropriate to use for forecasting gold prices in Indonesia.
Comparison of K-Means and Fuzzy C-Means Algorithms for Clustering Based on Happiness Index Components Across Provinces in Indonesia Inna Auliya; Fadhilah Fitri; Nonong Amalita; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 2 No. 1 (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-iss1/150

Abstract

Cluster analysis is a statistical technique used to group objects based on their shared characteristics. This research aims to assess how 34 provinces in Indonesia are clustered using happiness index indicators for the year 2021. The study compares two non-hierarchical cluster analysis methods, K-Means and Fuzzy C-Means. K-Means categorizes objects into clusters based on their proximity to the nearest cluster center, while Fuzzy C-Means employs a fuzzy grouping model assigning membership degrees from 0 to 1. The results indicate that both methods form three clusters. Evaluating standard deviation values and ratios, Fuzzy C-Means proves superior, displaying a larger standard deviation between groups and a smaller ratio (0.6680004) compared to K-Means. Consequently, the study concludes that the Fuzzy C-Means method is more optimal than K-Means.
Classification of Unemployment at West Sumatra Province in 2021 using Algorithm Classification and Regression Tree Nur Nur Fadillah; Syafriandi Syafriandi; Nonong Amalita; Dony Permana
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (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-iss2/166

Abstract

Unemployment is a problem that often occurs in developing countries. This is caused by the imbalance between the number of labor force and the number of working population. According to the Central Bureau of Statistics, West Sumatra Province in 2021 is the eighth province with a high open unemployment rate of 6,52%, which is higher than the average Indonesian open unemployment rate of 6,49%. The increase in unemployment has occurred from 2017 to 2021 which is caused by educated unemployment. This is due to the habit of job seekers who tend to pick and choose the types of jobs available, while business needs are very limited. The problem of unemployment will get higher if it is not resolved. As a result, unemployment can lead to poverty and other social problems. In this study, CART analysis is used to classify unemployment in West Sumatra Province in 2021 which aims to determine the factors that affect unemployment. CART is a decision tree that shows the relationship between the response variable and one or more predictor variables. The purpose of CART analysis is to obtain the right data group for classification purposes. Based on the analysis obtained, the variables that affect unemployment in West Sumatra Province in 2021 are marital status, gender, household status, education level, age, and place of residence with an accuracy value of 71,73%.
Pemetaan Intensitas Gempa Bumi di Wilayah Sumatera Barat Menggunakan Model Epidemic Type Aftershock Sequence Spatio-Temporal Hidayatul Fikra; Dina Fitria; Nonong Amalita; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (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-iss2/171

Abstract

The random spatial and temporal occurrence of earthquakes means that this are still being researched from a seismological and stochastic perspective. Point processes are examples of stochastic processes which explain seismic activity, one of them is Epidemic Type Aftershock Sequence (ETAS) model. It lackness ignores the location or spatial component of. Consequently, the components of time, location, and magnitude will be taken into consideration when discussing the ETAS model in this study. The spatio-temporal model is the name given to this concept. Therefore, in this research,mapping of earthquake intensity will be carried out in the West Sumatra region using the spatio-temporal ETAS model stated in conditional intensity function with eight parameters. The data used are earthquake events in the West Sumatra region with a magnitude threshold of 4 SR and a depth of ≤ 70 km for the period January 2000 to January 2024. Parameter model estimated using the maximum likelihood method and solved using the Davidon Fletcher Powell algorithm. The result shows area of West Sumatra with high earthquake intensity is coastal area, namely West Pasaman, Padang, Mentawai Islands and the South Pesisir. This makes the area vulnerable to seismic disasters
Random Forest Implementation for Air Pollution Standard Index Classification in DKI Jakarta 2022 Hanifa Hasna; Nonong Amalita; Dony Permana; Admi Salma
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (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-iss2/173

Abstract

Air pollution is a serious challenge in various cities, including DKI Jakarta. Based on measurements of the Air Pollution Standard Index carried out by the DKI Jakarta Environmental Service, the air quality in DKI Jakarta is considered moderate to unhealthy. Deteriorating air quality in the Jakarta metropolitan area is very dangerous for humans and living things. Therefore, to prevent the problem, the classification of air quality based on pollutant content is carried out using Random Forest (RF). The application of RF will form several trees that can provide better predictions and are able to produce low errors. The result of this study obtained optimal tree formation, namely tree formation using a combination of mtry (any input variables randomly selected in one sorting node)=2 and ntree (number of trees in the forest) as many as 5000 trees. The resulting accuracy was 99.17% with an OOB error rate of 0.83%. This research identifies that particulate pollutants are the main factor causing air pollution in DKI Jakarta. Based on these results, it shows that RF is able to provide accurate predictions about the level of air pollution in DKI Jakarta and can be identify important factors that affect air pollution.
Comparison of Estimate Method of Moment and Least Trimmed Squares in Models Robust Regression Tri Wahyuni Nurmulyati; Dony Permana; Nonong Amalita; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 2 No. 2 (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-iss2/176

Abstract

The poverty line is the minimum income that a person must earn to be considered to have a decent standard of living in a particular area. In 2022, the poverty line in West Sumatra Province was higher than the poverty line in Indonesia as a whole. An analysis was conducted to identify the factors influencing the poverty line in West Sumatra Province. However, the observational data on the poverty line and its influencing factors contained outlier. Therefore, robust regression analysis was performed to address the data containing outlier, comparing two estimates: MM estimation and LTS estimation. By examining the value, the best estimate was found to be MM estimation, with significant factors being average net wages/salaries, TPT, APM, and AMH. If the average net wages/salaries, TPT, APM, and AMH increase, the poverty line in West Sumatra will rise. With an of 0.9582, the model can explain 95.82% of the variation in the poverty line, while the remaining variation is explained by other factors not included in the model.
STUDI KOMPARATIF PENDIDIKAN KARAKTER DI NEGARA INDONESIA, MALAYSIA, DAN JEPANG Nonong Amalita; Azwar Ananda; Nurhizrah Gistituati; Rusdinal Rusdinal
JURNAL EDUCATION AND DEVELOPMENT Vol 12 No 1 (2024): Vol 12 No 1 Januari 2024
Publisher : Institut Pendidikan Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37081/ed.v12i1.5314

Abstract

Character problems in school-age children who deviate from the norms and values ​​in society. This is a problem in society. For this reason, character education is needed, especially in schools. Several countries have implemented character education in the school curriculum, for example Indonesia, Malaysia and Japan. Furthermore, the governments of the three countries have made character education a topic of discussion and priority in human resource development. Through character education, quality human beings are produced in all dimensions of personality. The purpose of this research is to describe and compare character education in Indonesia, Malaysia and Japan. This type of research is qualitative research with a literature study approach. Next, character education will be described and compared in the three countries.
ANALISIS KEMISKINAN DI INDONESIA MENGGUNAKAN LOCAL INDICATOR OF SPATIAL ASSOCIATION DAN SPATIAL ERROR MODEL Khairani, Putri Rahmatun; Kurniawati, Yenni; Amalita, Nonong; Mukhti, Tessy Octavia
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 6 No. 1 (2025): 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.v6i1.966

Abstract

Poverty in Indonesia remains a significant socio-economic challenge with notable regional disparities. The eastern provinces, particularly Papua, Maluku, and East Nusa Tenggara, experience persistently high poverty rates, suggesting a strong spatial influence. This study examines the spatial distribution of poverty using the Local Indicators of Spatial Association and the Spatial Error Model with 2024 data from the Indonesian Central Statistics Agency (BPS) for 38 provinces. The analysis employs a K-Nearest Neighbors weighting matrix (k = 10) for spatial dependencies. The LISA results identify High-High poverty clusters in Papua, Maluku, and East Nusa Tenggara. In contrast, Low-Low clusters are concentrated in Java and Bali, indicating a strong spatial pattern (Moran’s I = 0.4448). SEM findings reveal that the Gini index (β = 29.97) and population density (β = 0.016) significantly influence poverty, whereas inflation and total population do not. The model explains 76.1% of poverty variance (R² = 0.760966), highlighting its superiority over traditional regression models. These findings underscore the need for spatially adaptive policies to address poverty effectively. Policymakers should prioritize equitable economic development, regional investment, and infrastructure improvements, particularly in high-poverty clusters. Integrating spatial econometric models with KNN provides deeper insights into interregional disparities, supporting more precise and inclusive development strategies
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 FAZHIRA ANISHA Fenni Kurnia Mutiya Fitri, Fadhilah Gezi Fajri Ghaly, Fayyadh Hamida, Zilfa Hana Rahma Trifanni 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 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