Article Per Year (5 Year)
p-Index From 2021 - 2026
5.546
P-Index
This Author published in this journals
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

Published : 43 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 43 Documents
Search

 1   2   3   4   5 
Evaluating Determinants Of Survival Time In Heart Failure Patients Using Cox Proportional Hazards Regression Fajri Juli Rahman Nur Zendrato; Tessy Octavia Mukhti; Sarmilah; Razita Nur Amalina; Rosa Salsabila Azarine
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): 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/vol4-iss3/477

Abstract

Heart failure represents a severe chronic cardiovascular disorder and remains a major contributor to global mortality rates. Identifying specific risk factors that impact patient survivability is crucial for enhancing clinical interventions. This research investigates the determinants influencing the survival duration of heart failure patients by applying the Cox Proportional Hazards (Cox PH) regression approach. The primary objective of this study is to provide information on the main causes of heart failure and the factors that can influence the condition. Utilizing a secondary dataset of 299 patient records sourced from Kaggle, the study analyzed several variables, including age, gender, anemia, diabetes, smoking habits, and hypertension. The analytical findings reveal that age serves as the most critical determinant; individuals older than 65 face a 2.04 times greater mortality risk than younger cohorts. Furthermore, comorbidities such as anemia and hypertension significantly elevate this risk, presenting hazard ratios of 1.44 and 1.46, respectively. These outcomes emphasize the critical role of age and pre-existing medical conditions in the prognosis of heart failure, offering valuable perspectives for medical practitioners to design targeted therapeutic strategies that prolong patient survival.
Extended Cox Model for Analyzing Factors Influencing Time to First Employment After Graduation in West Sumatra M. Anfasa Prana Karil; Zilrahmi; Rita Diana; Tessy Octavia Mukhti; Dina Fitria; Retno Lis Megawati
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): 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/vol4-iss3/587

Abstract

The transition from education to employment has become one of the employment challenges in West Sumatra Province. This study aims to analyze the factors affecting the duration of obtaining a first job using the Extended Cox Proportional Hazard model. The data used were obtained from the August 2025 National Labor Force Survey (Sakernas) with variables including age, gender, educational attainment, regional classification, training, and work experience. The results show that age, educational attainment, and regional classification significantly affect the duration of obtaining a first job. Age has a positive effect that decreases over time, while higher educational attainment tends to increase job waiting time. Individuals living in rural areas tend to obtain jobs faster than those in urban areas. Meanwhile, gender and work experience are not significant, whereas training is significant through its interaction with time. Overall, the duration of obtaining a first job is influenced by individual factors, regional characteristics, and time-varying effects of the variables
Classification of Toddler Stunting Status Using Naïve Bayes Classifier with K-Fold Cross Validation Vania Riski Afifah; Zilrahmi; Syafriandi Syafriandi; Tessy Octavia Mukhti
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): 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/vol4-iss3/558

Abstract

The growth of toddlers that doesn’t meet age standards can affect their quality of life in the future. In Indonesia, one of the nutritional problems that continues to receive significant attention is stunting, which is generally indicated by a mismatch between a child's height and age (height-for-age, HAZ/TB/U). Considering that determining stunting status requires a high level of accuracy, a data-driven approach is needed to support the identification and evaluation of children's nutritional conditions in a more systematic manner. This study aims to classify stunting status among toddlers using the Naïve Bayes Classifier (NBC) algorithm with a 10-Fold Cross Validation method. NBC was selected because it is simple, efficient, and suitable for probability-based classification of health data. The data were obtained from the Health Office of Pasaman Regency in 2022. The variables used include gender, birth weight, birth height, age at measurement, body weight, body height, Mid-Upper Arm Circumference (MUAC), and height-for-age (HAZ) status. Stunting status was divided into two categories: stunted and severely stunted. The analysis showed that 53.91% of toddlers were classified as stunted, while 46.10% were classified as severely stunted. Based on the evaluation using 10-Fold Cross Validation, the NBC model showed good performance with an accuracy of 86,26%, precision of 73,33%, recall of 68,75%, and an F1-score of 70,97%. The analysis also showed that height, weight, and MUAC at the time of measurement were the characteristics that most clearly distinguished the stunted and severely stunted categories. These findings indicate that anthropometric indicators can support the detection and monitoring of stunting among toddlers. Overall, this study is expected to help health workers identify toddlers who require further nutritional assessment and support more targeted stunting management efforts.
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 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 M. Anfasa Prana Karil 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 Razita Nur Amalina Reihan Dani Eka Saputra Retno Lis Megawati Rita Diana Rizki Akbar Rosa Salsabila Azarine Rudi Anggara Salma, Admi Sari Agustin Sari, Nilam N. Sari, Widia Kemala Sarmilah 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 Vania Riski Afifah Vinna Sulvia Wafiq Alya Aufa Widia Kemala Sari Yenni Kurniawati Yoli Marda Novi Yonggi Septa Pramadia Yonggi Yusra, Zulmi Yusra Zamahsary Martha Zilrahmi, Zilrahmi Zulfadly Harman Harahap