Article Per Year (5 Year)
p-Index From 2021 - 2026
0.983
P-Index
This Author published in this journals
All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Indonesian Journal of Applied Statistics Jambura Journal of Mathematics Jurnal Pengabdian kepada Masyarakat
Husna Afanyn Khoirunissa
Universitas Sebelas Maret
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
Comparison of Random Forest, Logistic Regression, and MultilayerPerceptron Methods on Classification of Bank Customer Account Closure Husna Afanyn Khoirunissa; Amanda Rizky Widyaningrum; Annisa Priliya Ayu Maharani
Indonesian Journal of Applied Statistics Vol 4, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i1.41461

Abstract

The Bank is a business entity that is dealing with money, accepting deposits from customers, providing funds for each withdrawal, billing checks on the customer's orders, giving credit and or embedding the excess deposits until required for repayment. The purpose of this research is to determine the influence of age, gender, country, customer credit score, number of bank products used by the customer, and the activation of the bank members in the decision to choose to continue using the bank account that he has retained or closed the bank account. The data in this research used 10,000 respondents originating from France, Spain, and Germany. The method used is data mining with early stage preprocessing to clean data from outlier and missing value and feature selection to select important attributes. Then perform the classification using three methods, which are Random Forest, Logistic Regression, and Multilayer Perceptron. The results of this research showed that the model with Multilayer Perceptron method with 10 folds Cross Validation is the best model with 85.5373% accuracy.Keywords: bank customer, random forest, logistic regression, multilayer perceptron
Early Detection of South Korean Financial Crisis using MS-GARCH Based on Term of Trade Indicator Husna Afanyn Khoirunissa; Sugiyanto Sugiyanto; Sri Subanti
Indonesian Journal of Applied Statistics Vol 4, No 2 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i2.49169

Abstract

Abstract. The 1997 Asian financial crisis, which occurred until 1998, had a significant impact on the economies of Asian countries, including South Korea. The crisis brought down the South Korean currency quickly and sent the economy into sudden decline. Because the impact of the financial crisis was severe and sudden, South Korean requires a system which able to sight crisis signals, therefore that, the crisis will be fended off. One in all the indicators that can detect the financial crisis signals is that the term of trade indicator which has high fluctuation and change in the exchange rate regime. The mixture of Markov Switching and volatility models, Generalized Autoregressive Conditional Heteroscedasticity (GARCH), or MS-GARCH could explain the crisis. The MS-GARCH model was built using data from the South Korean term of trade indicator during January 1990 until March 2020. The findings obtained in this research can be inferred that the best model of the term of trade is MS-GARCH (2,1,1). Term of trade indicator on that model could explain the Asian monetary crisis in 1997 and also the global monetary crisis in 2008. The smoothed probability of term of trade indicators predicts in April till December 2020 period, there will be no signs of the monetary crisis in South Korea.Keywords: financial crisis, MS-GARCH, South Korea, term of trade indicator
Pemetaan Risiko Penyakit Tuberkulosis (TBC) di Kota Surakarta dengan Spatial Empirical Bayes Husna Afanyn Khoirunissa
Indonesian Journal of Applied Statistics Vol 3, No 2 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v3i2.41282

Abstract

Tuberculosis is an infectious disease that can attack human with a poor immune system. In 2017, there were 723 residents of Surakarta tested positive for tuberculosis. The spatial empirical Bayes method is a good method for mapping the risk of tuberculosis because this method includes spatial dependency information and can overcome small area problems. This method can help the prevention of tuberculosis in Surakarta. In the analysis, it was found that the number of cases of tuberculosis in Surakarta has a spatial dependency that has an impact of the spread of tuberculosis. Sub-district classification with the highest risk value is Jebres, Tegalharjo, Jajar, Laweyan, Sondakan, Purwosari, Mangkubumen, Keratonan, Timuran, and Punggawan.Keywords : tuberculosis, mapping, spatial empirical Bayes, Surakarta
PENINGKATAN LITERASI STATISTIKA : MEWUJUDKAN SANTRI CERDAS SEBAGAI UPAYA OPTIMALISASI ZAKAT DAN PEMBERDAYAAN POTENSI UMMAT Slamet, Isnandar; Zukhronah, Etik; Sulandari, Winita; Subanti, Sri; Sugiyanto, Sugiyanto; Susanto, Irwan; Isnaini, Bayutama; Afanyn Khoirunissa, Husna; Adi Wicaksono, Nanda; Indra Raditya , Dionisius
J-ABDI: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 3: Agustus 2025
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pemberdayaan Potensi Ummat”. Tujuan utama kegiatan adalah membekali peserta dengan pengetahuan dasar statistika sebagai alat berpikir rasional dan analitis, serta memperkuat kesadaran akan kewajiban dan keutamaan (fadhilah) zakat dalam kehidupan sosial-keagamaan. Kegiatan diikuti oleh 114 peserta, terdiri dari 102 santri dan 12 ustadz. Materi yang disampaikan meliputi statistika dasar, konsep kewajiban zakat menurut syariat Islam, serta fadhilah zakat dalam rangka pemberdayaan umat. Tim pengabdian berasal dari Grup Riset Statistika dan Sains Data Bidang Industri dan Ekonomi, Universitas Sebelas Maret (UNS). Metode pelaksanaan meliputi pre-test, penyampaian materi secara interaktif, praktik pengolahan data sederhana, diskusi aplikatif, dan post-test. Hasil evaluasi menunjukkan peningkatan signifikan pada pemahaman peserta terhadap materi yang disampaikan. Kegiatan ini diharapkan menjadi langkah awal dalam membentuk generasi santri yang cerdas secara statistik, sadar zakat, dan siap berkontribusi dalam penguatan ekonomi umat berbasis pesantren.
Exploring Spatial Nonstationarity in the Number of Motor Vehicles in East Java Using Robust Geographically Weighted Regression with an MM-Estimator Isnaini, Bayutama; Isnandar Slamet; Sulandari, Winita; Khoirunissa, Husna Afanyn
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 20 No. 2 (2025)
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v20i2.90866

Abstract

The number of motor vehicles in each region is quite diverse, not least in East Java Province. The variety of number of motor vehicles can be affected by local factors that are important to study so that vehicle growth can be adequately anticipated. On the other hand, economic growth incentives are influenced by people's purchasing power. In addition, motor vehicles are one of the essential things in the sustainability of economic activities. This study aims to evaluate a robust, geographically weighted regression model with an MM-estimator (RGWR MM-estimator), which is considered suitable for analyzing the number of motor vehicles in East Java. The results showed that the RGWR MM-estimator model generates an estimate of the number of motor vehicles based on the HDI explanatory variables, road length, sex ratio, poverty gap index, and the number of colleges that is accurate compared to other models formed. In addition, there are significant differences in the influence of the five explanatory variables in each region. Districts/cities located near the capital of East Java Province tend to have many explanatory variables that have a significant effect compared to regencies/cities far from the provincial capital.
Comparative Analysis of Hierarchical Cluster Methods in Inflationary Cities in Indonesia Based on Sectoral Inflation Patterns Khoirunissa, Husna Afanyn; Safitriani, Nur Rezky; Widyaningrum, Erlyne Nadhilah; Putri, Rizka Amalia; Fathan, Morina A.; Nisa, Nabilla Rida Tri
Jambura Journal of Mathematics Vol 8, No 1: February 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v8i1.35105

Abstract

This study aims to assess the performance of single linkage, complete linkage, and average linkage hierarchical clustering algorithms in grouping cities used as inflation benchmarks in Indonesia into clusters based on sectoral inflation patterns. The data utilized are 150 regencies/cities divided into 11 sectors that drive inflation, identified by BPS Indonesia. Prior to clustering, a distance analysis using Euclidean distances was conducted to measure similarity between regions. Evaluation of the optimal number of clusters was conducted by applying the stability measure approach (APN, AD, ADM, and FOM), which showed that creating five clusters produced the most stable results. The results of the analysis revealed that the single linkage approach had the lowest within-cluster to between-cluster standard deviation ratio compared to the other two approaches, which revealed a greater level of homogeneity between the clusters. From an economic perspective, this clustering pattern revealed impressive differences in sectoral inflation pressures between provinces, even between cities within a province. Consequently, the single linkage method is proposed as the optimal method for identifying spatial variations in sectoral inflation in Indonesia.
Co-Authors Adi Wicaksono, Nanda Amanda Rizky Widyaningrum Annisa Priliya Ayu Maharani Erlyne Nadhilah Widyaningrum Fathan, Morina A. Indra Raditya , Dionisius Irwan Susanto Isnaini, Bayutama Isnandar Slamet Isnandar Slamet, Isnandar Nisa, Nabilla Rida Tri Putri, Rizka Amalia Safitriani, Nur Rezky Sri Subanti Sugiyanto - Sugiyanto Sugiyanto Winita Sulandari Zukhronah, Etik