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All Journal Imajiner: Jurnal Matematika dan Pendidikan Matematika Pelita Eksakta Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Mosharafa: Jurnal Pendidikan Matematika Leibniz: Jurnal Matematika UNP Journal of Statistics and Data Science Mathematical Journal of Modelling and Forecasting
Tessy Octavia Mukhti
Universitas Negeri Padang
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

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Perbandingan Metode Naïve Bayes Dan K-Nearest Neighbors Dalam Mengklasifikasikan Indeks Pembangunan Manusia Menurut Kabupaten/ Kota di Indonesia Tahun 2022 Rudi Anggara; Tessy Octavia Mukhti; Yenni Kurniawati; Dina Fitria
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-iss4/319

Abstract

The Human Development Index (HDI) is an indicator used to measure the success of efforts to improve the quality of human life in a particular region. Indonesia's HDI has increased every year, but the HDI in several districts/cities in Indonesia remains in the low category. The low HDI in these districts/cities is due to unequal development between regions in Indonesia. This disparity in development is influenced by HDI indicators as well as other factors. To address this issue, a decision system is needed to determine HDI categories using the Naive Bayes and KNN methods. Naive Bayes is applied with the assumption of Gaussian distribution, while KNN is implemented with the optimization of the nearest K value. Model performance evaluation is conducted to determine the best accuracy of the two methods using a confusion matrix. The analysis results show that the Naïve Bayes model outperforms the KNN algorithm in classifying the Human Development Index (HDI) by district/city in Indonesia for the year 2022, with Naïve Bayes achieving an accuracy of 93%. Therefore, the Naïve Bayes algorithm show good performance in terms of accuracy.
Mapping Indonesian Provinces Based on Leading Plantation Commodities with Export Potential Using Multidimensional Scaling Analysis Dicha Putri Yeni; Tessy Octavia Mukhti; Yenni Kurniawati; Dina Fitria
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-iss4/327

Abstract

Indonesia, as an agrarian country, benefits significantly from its plantation subsector, which contributes substantially to the national economy. However, the processing of plantation products in Indonesia remains largely limited to raw or semi-finished goods, resulting in low added value and restricted income for both farmers and the nation. This study aims to map Indonesia's provinces based on the production of key plantation commodities with high export potential, utilizing the Multidimensional Scaling (MDS) analysis method. The research focuses on commodities such as pepper, palm oil, coconut, rubber, coffee, cocoa, clove, and tea. It seeks to group 34 Indonesian provinces based on similarities in plantation production, providing valuable insights for policymakers to enhance production and increase export value. The analysis calculates inter-provincial similarities to determine distances between objects and evaluates the accuracy of the MDS mapping using STRESS and R2 values. The findings indicate that 12 provinces share similarities in cocoa production, while 7 provinces are closely aligned in the production of pepper, rubber, and coffee. Furthermore, 5 provinces exhibit similarities in palm oil production, and 9 provinces demonstrate commonalities in the production of coconut, clove, and tea. The analysis achieved a STRESS value of 0.024 (2.4%) and an R2 value of 0.9994, indicating that the MDS mapping is highly reliable. However, the results do not fully align with field data, suggesting the need for orthogonal transformation through Principal Component Analysis (PCA) to improve accuracy.
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.
Comparison of Cox Proportional Hazard Models with Interaction and Without Interaction in Heart Failure Patients Bunga Nafandra; Tessy Octavia Mukhti; Yoli Marda Novi; Nurul Mulya Syahwa; Olga Afrilly Putri
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (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-iss2/342

Abstract

 Heart failure is one of the disorders that attack the heart and is a major cause of morbidity and mortality. There is a 5% prevalence of heart failure in Indonesia in 2020. By utilizing survival analysis, this study aims to compare the Cox proportional hazard model with interaction and without interaction, and identify factors that significantly affect the survival time of heart failure patients. The research data is secondary data consisting of 299 heart failure patient data with several variables including high blood pressure, anemia status, and age. Through the stages of analysis that have been carried out, it is found that the variables of high blood pressure and age have a significant effect on the survival time of heart failure patients, while the anemia variable and the interaction between independent variables do not have a significant relationship with survival time. In addition, based on the AIC value, it is also found that the model without interaction is better than the model with interaction, which is characterized by a smaller AIC value in the model without interaction. Based on the best model, patients with high blood pressure have a 1.52 times higher chance of dying than patients without high blood pressure. In addition, the probability of death increased by 4.33% for every one-year increase in patient age. This study concludes that the model without interaction is more suitable for describing the relationship between independent variables and survival time in heart failure patients.
Cox-Stratified Model in Relationship Analysis between Employee Mental Health and Resignation Decision Sari Agustin; Tessy Octavia Mukhti; Suci Rahmadani; Afifah Nabilah; Wafiq Alya Aufa
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (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-iss2/350

Abstract

This study examines the relationship between employee mental health and turnover decisions using the Cox Stratified model. Utilizing secondary worker turnover data from Kaggle, the research investigates the impact of anxiety and self-control on job tenure. Results indicate that the Cox Proportional Hazard model significantly explains this relationship, with self-control emerging as a key factor negatively associated with turnover risk. Stratification of profession variables, which did not meet the proportional hazard assumption, revealed variations in survival rates across different professions. Professions requiring strong self-control, such as HR and sales, exhibited higher survival probabilities, whereas high-pressure professions like consulting andshowed lower survival rates. A reduced model confirmed the importance of self-control in employee retention. The findings suggest that interventions aimed at enhancing self-control could serve as an effective strategy for mitigating turnover, especially in high-stress occupations. Elevated job pressure can negatively impact employee mental well-being, potentially disrupting self-control and increasing anxiety levels. Future research could incorporate additional influential factors, such as job satisfaction, work environment, and social support, to further develop this research. Furthermore, the implementation of real-time data collection could enable continuous monitoring of mental conditions, behaviors, and relevant factors such as self-control and anxiety, providing dynamic insights over short time intervals.
Survival Analysis of Heart Failure Patients Using the Cox Proportional Hazard Model and Weibull Regression Rahmika Alya; Tessy Octavia Mukhti; Sri Wahyuni; Bunga Miftahul Barokah; Azizah Apriyerni
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (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-iss2/351

Abstract

Cardiovascular disesase is the leading cause of death globally, claiming around 17,9 million lives each year, accounting for 31% of all deaths worldwide. Hearth failure is a common event caused by cardiovascular disease. Hearth failure is one of the principal health issues with excessive mortality and morbidity costs. Heart failure is the main reason of mortality worldwide. This take a look ambitions to analyze the factors influencing the survival of heart failure patients using the Cox proportional hazard Cox (PH) model and the Weibull regression. The main purpose of this study is to provide information on the causes of heart failure deaths and what effects occur when having heart disease. It is hoped that the results of this study can provide the general public to be more careful in order to prevent heart failure disease. The data used are secondary data from Kaggle consisting of 299 patients with the variables anemia, diabetes, hypertension, gender and smoking status. The analysis showed that only hypertension significantly increased the risk of events in both models, whereas other variables were not statistically significant. The selection of the best model is based on the assumptions of proportional hazard, flexibility, and Akaike information criterion (AIC) values. The Cox-PH model was chosen as the model of choice because it is more flexible and does not require certain fundamental assumptions regarding risk distribution. This study provides important insight into the risk factors that influence the prognosis of heart failure patients.
Clustering Regions in West Sumatera Based on the Special Protection Index for Children Using K-Means Clustering with Silhouette Coefficient Siti Nurhaliza; 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-iss1/356

Abstract

Child protection is a crucial aspect of social development, especially in West Sumatra Province, which consists of 19 regencies/cities with diverse child protection characteristics. This study aims to cluster regencies/cities in West Sumatra based on the 2021 Child Special Protection Index (IPKA) using the K-Means Clustering method with the Silhouette Coefficient. Secondary data were obtained from the Office of Women's Empowerment and Child Protection, Population Control, and Family Planning (DP3AP2KB) of West Sumatra Province, covering variables such as the percentage of working children, internet access, education level, poverty, and child neglect. The results show that the K-Means method is effective in quickly and accurately grouping data into homogeneous clusters, while a Silhouette Coefficient value of 0.70 indicates a strong cluster structure and high-quality grouping.
Mortality Trends in Heart Failure Patients : A Study Using Cox Regression Models: Tren Mortalitas pada Pasien Gagal Jantung: Sebuah Studi Menggunakan Model Regresi Cox Ervi Dayana Putri; Tessy Octavia Mukhti; Rahmatul Annisa; Adinda Putri; Sepniza Nasywa
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (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-iss2/359

Abstract

Heart failure is classified as a cardiovascular disease, which is the leading cause of death worldwide. In Indonesia, heart failure has a high mortality rate, which in 2019 became the second leading cause of death after stroke. One method that can be used to examine the factors affecting mortality in heart failure patients is the cox proportional hazards regression. Cox proportional hazards regression is one of the most commonly used methods for analyzing survival data to date. The study data consisted of 299 observations involving 5 predictor variables, such as age, serum creatinine, serum sodium, high blood pressure, and diabetes. The conclusion of the analysis indicates that the variables of age, serum creatinine, serum sodium, and high blood pressure are significant. High blood pressure and serum creatinine are the factors that most affect the death of heart failure patients. Patients with high blood pressure have a 56,71% higher risk of death than patients without high blood pressure, and every 1 mg/dL in creatinine in the blood, the risk of death for heart failure patients will increase by 29,77%.
Grouping of Provinces in Indonesia Based on Active Family Planning Participants Using Modern Methods Using Fuzzy C-Means Annisa Ramadhani; Tessy Octavia Mukhti; Yenni Kurniawati; Zamahsary Martha
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (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-iss2/365

Abstract

Indonesia’s rapid population growth presents a significant challenge to national welfare and public health. One of the key strategies implemented by the government to address this issue is the Family Planning (FP) program, which emphasizes the use of modern contraceptive methods. However, the utilization of these methods remains uneven across provinces. This study aims to cluster Indonesian provinces based on the number of active participants using modern contraceptive methods in 2023 by applying the Fuzzy C-Means (FCM) clustering algorithm. FCM was selected due to its ability to handle overlapping data characteristics, allowing for a more flexible and representative analysis. The clustering results reveal two main clusters: Cluster 1, which consists of provinces with high levels of active modern contraceptive users, and Cluster 2, which includes provinces with low participation levels. These findings are expected to serve as a reference for more targeted policy formulation to enhance the equity and effectiveness of the FP program across the country.
Co-Authors Adinda Putri Adrianingsih, Narita Y. Afifah Nabilah Aisyah Novriani Andini Diva Luthfiyah anice kartika Annisa Ramadhani Azizah Apriyerni Berliana Nofriadi Bimbim Oktaviandi Bunga Miftahul Barokah Bunga Nafandra Devni Prima Sari Dhio Ervandi Dicha Putri Yeni Dina Fitria Dina Fitria, Dina Dinda Putri Adilla Dodi Vionanda Dodi Vionanda Dony Permana Ervi Dayana Putri Fadhilah Fitri Fadhilah Fitri Fajri Juli Rahman Nur Zendrato Fathina Nafisa Fauzan Al Hamdani Siregar Fauzan Al-Hamdani Siregar Fauzan Arrahman Fauzan Gustiandra Fenni Kurnia Mutiya Figo Rahmatullah Fitri Hayati Fitri Fitri, Fadhilah Herlena Purnama Sari Khairani, Putri Rahmatun Khairanisa Salsabila Luthfiyah, Andini Diva Muhammad Arief Rivano Nikma Hasanah Nonong Amalita Nurul Mulya Nurul Mulya Syahwa Olga Afrilly Putri Olivin Adelia Huqmi Padafani, Lekison Permana, Dony Putri fajriyanti nur Rahmadani Rahmat Kurniawan Rahmatul Annisa Rahmika Alya Reihan Dani Eka Saputra Rizki Akbar Rudi Anggara Salma, Admi Sari Agustin Sari, Nilam N. Sari, Widia Kemala Sepniza Nasywa Septrina Kiki Arisandi Septrina Kiki Arisandi Siti Nurhaliza Sonia Ardhi Sri Wahyuni Suci Rahmadani Suliswati, Yeni Syafriandi Syafriandi Syafriandi Syafriandi Syifa Miftahurrahmi Taslim, Fauziah Vinna Sulvia Wafiq Alya Aufa Yenni Kurniawati Yoli Marda Novi Yonggi Septa Pramadia Yonggi Yusra, Zulmi Yusra Zamahsary Martha Zilrahmi, Zilrahmi Zulfadly Harman Harahap