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All Journal IPTEK The Journal for Technology and Science Techno.Com: Jurnal Teknologi Informasi BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Statistika dan Aplikasinya Journal of Multidisciplinary Applied Natural Science Makara Journal of Science Javanologi: International Journal of Javanese Studies STATISTIKA Society
Yekti Widyaningsih
Universitas Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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POISSON REGRESSION MODELS TO ANALYZE FACTORS THAT INFLUENCE THE NUMBER OF TUBERCULOSIS CASES IN JAVA Widyaningsih, Yekti; Budiawan, Zalfa Alifah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1761-1772

Abstract

Tuberculosis is an infectious disease and one of the world's top 10 highest causes of mortality in Indonesia. Based on this fact, it is necessary to study what factors affect number of tuberculosis cases. The number of tuberculosis cases as dependent variable is a count data that generally analyzed using Poisson regression. However, equidispersion assumption must be met, so Generalized Poisson Regression and Negative Binomial Regression are applied if the assumption is not met. Spatial aspects can be considered so Geographically Weighted Generalized Poisson Regression and Geographically Weighted Negative Binomial Regression were also conducted. Four models were built to evaluate relationship between number of tuberculosis cases and factors affecting it in Java in 2020. The explanatory variables are population density, percentage of children receiving BCG immunization, percentage of poor people, percentage of eligible drinking water facilities, percentage of family cards with access to proper sanitation, percentage of public places meet health requirements, and percentage of food management places meet hygienic requirements. This study shows that the best model for modeling the data is GWNBR with 2 groups of significant explanatory variables. Seven explanatory variables are statistically significant in 88 districts and six explanatory variables statistically significant in 12 districts.
WEIBULL-POISSON DISTRIBUTION AND THEIR APPLICATION TO SYSTEMATIC PARALLEL RISK Widyaningsih, Yekti; Ivana, Rugun
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0053-0064

Abstract

The Weibull-Poisson distribution represents a continuous distribution type applicable to various forms of hazard, including monotone up, monotone down, and upside-down bathtub shapes that ascend. The distribution characterizes lifetimes and can effectively model failures within a series of systems, which evolves from the Exponential-Poisson distribution. This distribution emerges through the compounding of the Weibull Distribution and Zero Truncated Poisson Distribution. The compounding itself integrates several mathematical properties, such as statistical order and Taylor’s number expansion, to reach its final form. Alongside the formulation of the Weibull-Poisson distribution, this paper includes the probability density function, distribution function, rth moment, rth central moment, mean, and variance. For illustration, the Weibull-Poisson distribution is applied to guinea pig survival data after being infected with Turblece virus Bacilli.
Analysis of Factors that Explain Customer Satisfaction and Its Relationship with Repurchase Intention at Fresh Food E-Commerce in Jabodetabek Post Pandemic Agustin, Natania; Widyaningsih, Yekti; Setiadi, Rianti
Statistika Vol. 25 No. 2 (2025): 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.v25i2.4966

Abstract

Abstract. Consumers now have the flexibility to purchase fresh food both online and offline in the post-pandemic era. In this competitive landscape, only companies that can retain their customers are likely to survive. This study investigates the factors influencing customer satisfaction and its impact on repurchase intention in the context of fresh food e-commerce. Specifically, it examines the effects of product quality, fair price, perceived ease of use, service response speed, and service convenience on customer satisfaction, and further explores the moderating role of customer experience in the relationship between satisfaction and repurchase intention. Primary data were collected using a purposive sampling technique from 160 respondents who had purchased fresh food from Sayurbox, Segari, Allofresh, or Astro within the last six months. Data was analyzed using Partial Least Square, a non-parametric statistical technique suitable for modeling latent variable relationships without distributional assumptions. The results show that product quality, fair price, service response speed, and service convenience significantly and positively influence customer satisfaction. In contrast, perceived ease of use does not have a significant effect. Customer satisfaction has a strong positive influence on repurchase intention. However, customer experience does not significantly moderate the relationship between customer satisfaction and repurchase intention. These findings highlight the importance of maintaining product and service quality to enhance customer satisfaction and encourage repeat purchases in the fresh food e-commerce sector.
Pola Hubungan Dampak Fatherless terhadap Kecanduan Internet, Kecenderungan Bunuh Diri dan Kesulitan Belajar Siswa SMAN ABC Jakarta Wibiharto, Bunga Maharani Yasmin; Setiadi, Rianti; Widyaningsih, Yekti
Society Vol 9 No 1 (2021): Society
Publisher : Laboratorium Rekayasa Sosial, Jurusan Sosiologi, FISIP Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/society.v9i1.275

Abstract

Fatherless is the absence of a father figure. Some impacts of fatherlessness are loneliness, openness, depression, self-control, and self-esteem. These factors can influence internet addiction and suicidal tendencies. It also can cause difficulty in the learning process for students. This study aims to determine the significant impacts caused by fatherlessness and the relation to internet addiction, suicidal tendencies, and learning difficulties. The method used is Partial Least Square. The results showed that the significant impacts caused by fatherlessness are loneliness, depression, and self-esteem. The impacts of fatherless that influence internet addiction are loneliness and depression. The impact of fatherlessness that influences suicidal tendencies is depression. Internet addiction and suicidal tendencies influence learning difficulties.
CLUSTERING OF COUNTRIES BASED ON WORLD HAPPINESS INDICATORS USING K-MEANS Adylla, Fahira Puti; Lestari, Dian; Widyaningsih, Yekti
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09209

Abstract

Happiness is a multidimensional concept encompassing emotional well-being, life satisfaction, and perceived quality of life. The increasing use of happiness indicators as complementary measures of development beyond economic growth has attracted growing attention in statistical and applied research. This study aims to classify countries based on a comprehensive set of world happiness indicators using the K-Means clustering method. The indicators include the Happiness Index (subjective), gross domestic product (GDP) per capita, social support, healthy life expectancy, freedom to make life choices, generosity, negative perceptions of corruption, crime index, and cost of living. The optimal number of clusters is determined using the Silhouette Index, while Biplot analysis is employed to visualize cluster characteristics and relationships among indicators. The results identify three distinct clusters. Cluster 1 is dominated by countries with low happiness levels, Cluster 2 represents countries with moderate happiness profiles, and Cluster 3 consists of countries with high happiness levels. The findings demonstrate the effectiveness of multivariate clustering techniques in revealing structural patterns in happiness data and provide empirical evidence that may support comparative statistical analysis and policy-oriented applications.
Co-Authors Abdullah, Sarini Abraham Raja Swara Darwanto Adylla, Fahira Puti Agustin, Natania Aji H. Wigena Aldinda Albanna Anis Dela Desela Antoni Wibowo Arum, Graceilla Puspita ASEP SAEFUDDIN Budiawan, Zalfa Alifah Bunga Maharani Yasmin Wibiharto Cahyadi, Danu Julian Curie Nabilah Nasution Dewi Retno Sari Saputro, Dewi Retno DIAN LESTARI Dian Lestari Geraldine Immanuel Tangyong Hendri Murfi Ivana, Rugun Khairil Anwar Notodiputro Melia Rizki Fitrianingrum Mohammad Zahran Pratomo Natasha Latifatu Soliha Nisa, Alfia Choirun Pin, Tjiong Giok Prawira, Kevin Rahmawati, Aprilia Rianti Setiadi Rianti Setiadi Sabila, Fatsa Vidyaningtyas SAFITRI, NABILA Setiadi, Rianti Setjiadi, Nerissa Netanaya Silvia Soemartojo, Saskya Mary Taza Luzia Viarindita Tjiong Giok Pin Wahyu, Nugroho Lambang Wibiharto, Bunga Maharani Yasmin Yudi Satria