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All Journal International Journal of Public Health Science (IJPHS) Jurnal Ilmu Pertanian Indonesia Jurnal Ekonomi Pembangunan EKSAKTA: Journal of Sciences and Data Analysis JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Sains dan Teknologi Techno.Com: Jurnal Teknologi Informasi CAUCHY: Jurnal Matematika Murni dan Aplikasi JAM : Jurnal Aplikasi Manajemen Jurnal TIMES Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Kubik Journal of Accounting and Investment JURNAL KOLABORASI JIMKesmas (Jurnal Ilmiah Mahasiswa Kesehatan Masyarakat) Al-Jabar : Jurnal Pendidikan Matematika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Desimal: Jurnal Matematika MUST: Journal of Mathematics Education, Science and Technology Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Socioeconomics and Development Jurnal Informatika Universitas Pamulang Journal of Applied Food Technology J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL PENDIDIKAN TAMBUSAI Teorema: Teori dan Riset Matematika Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jambura Journal of Mathematics ComTech: Computer, Mathematics and Engineering Applications Journal of Information System, Applied, Management, Accounting and Research Ecces: Economics, Social, and Development Studies Inferensi Journal of Data Science and Its Applications International Journal of Science, Engineering and Information Technology Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya KUBIK: Jurnal Publikasi Ilmiah Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi MATH LOCUS: Jurnal Riset dan Inovasi Pendidikan Matematika PROFETIK: Jurnal Mahasiswa Pendidikan Agama Islam SRIWIJAYA JOURNAL OF ENVIRONMENT MATHunesa: Jurnal Ilmiah Matematika VARIANSI: Journal of Statistics and Its Application on Teaching and Research Aceh International Journal of Science and Technology Jurnal Sains dan Informatika : Research of Science and Informatic STATISTIKA Scientific Journal of Informatics Journal of Mathematics, Computation and Statistics (JMATHCOS) Jurnal Pendidikan Progresif Indonesian Journal of Statistics and Its Applications Jurnal Info Kesehatan

Fitrianto, Anwar

Departemen Statistika, Fakultas MIPA, IPB University, Bogor 16680

Author-ID : 2752567

Religion Agriculture, Biological Sciences & Forestry Arts Humanities 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 Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

Published : 118 Documents Claim Missing Document

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Comparing Outlier Detection Methods: An Application on Indonesian Air Quality Data Anwar Fitrianto; Amalia Kholifatunnisa; Anang Kurnia
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 2 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v9i2.29434

There are many methods for detecting outliers, but only a few methods consider data distribution. This research compares outlier detection method on univariate data with a skewed distribution. Outlier detection methods used in this research are Tukey's boxplot, adjusted boxplot, sequential fences, and adjusted sequential fences. It identifies areas of concern due to poor air quality during the Implementation of Micro-Community Activity Restrictions. The study used Indonesian air quality index data.The adjusted boxplot method performs best based on the number of outliers detected, error rate, accuracy, precision, specificity, sensitivity, and robustness. Adjusted boxplot and adjusted sequential fences can detect tails that contain outliers accurately because the skewness coefficient makes them more robust. Meanwhile, Tukey's boxplot and sequential fences are poor methods since they couldn’t detect correctly true outliers. Based on the results, adjusted boxplot is the best method. Then, areas that need attention due to poor air quality include South Sumatera, South Sulawesi, West Java, Riau, North Sumatera, Jambi, Jakarta, and East Java.

Analisis Regresi Logistik Biner dan Random Forest untuk Prediksi Faktor-Faktor Stunting di Pulau Jawa Yuniarsyih R.A, Rizqi Dwi; Muhadi, Rizqi Annafi; Fitrianto, Anwar; Silvianti, Pika
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 2 August 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i2.31680

This study aimed to compare the performance and variable identification capabilities of Binary Logistic Regression and Random Forest models in classification analysis. The results showed that both methods consistently identified variables X1, X3, and X4 as the most influential factors in predicting outcomes. However, Binary Logistic Regression also identified variable X6 as statistically significant, which was not reflected in the Random Forest model. In terms of model performance, Random Forest outperformed Binary Logistic Regression across all evaluation metrics, including accuracy, precision, sensitivity, specificity, and balanced accuracy. These findings suggested that Random Forest was more effective in handling complex data structures and delivering optimal classification results, while Binary Logistic Regression excelled in providing deeper interpretability of variable relationships. Therefore, the choice of method should have aligned with the analytical objectives, and combining both approaches could have yielded more comprehensive insights.

Comparison of GMERF and GLMM Tree Models on Poverty Household Data with Imbalanced Categories Bukhari, Ari Shobri; Notodiputro, Khairil Anwar; Indahwati, Indahwati; Fitrianto, Anwar
Inferensi Vol 8, No 2 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i2.21901

Decision tree and forest methods have become popular approaches in data science and continue to evolve. One of these developments is the combination of decision trees with Generalized Linear Mixed Models (GLMM), resulting in the GLMM Tree, which is applicable to multilevel and longitudinal data. Another model, Generalized Mixed Effect Random Forest (GMERF), extends the concept of decision forests with GLMM, effectively handling complex data structures with non-linear interactions. This study compares the performance of GLMM Tree and GMERF models in classifying poor households in South Sulawesi Province, characterized by imbalanced categories. GLMM Tree provides a simple, interpretable classification through tree diagrams, while GMERF highlights variable importance. Initial tests show all three models (GLMM, GLMM Tree, and GMERF) achieve high accuracy and specificity but exhibit low sensitivity. By applying oversampling, sensitivity and AUC are significantly improved, though this is accompanied by a decline in accuracy and specificity, revealing a trade-off. The study concludes that while GLMM, GLMM Tree and GMERF have their strengths, using them together offers a more comprehensive understanding of poverty classification. Handling imbalanced data with oversampling is effective in increasing sensitivity, but careful consideration is needed due to its impact on overall accuracy.

Perbandingan Metode K-Means dan OPTICS dalam Penggerombolan Kemiskinan Multidimensi di Indonesia Sari, Devi Permata; Rizqi, Tasya Anisah; Fitrianto, Anwar; M.S, Erfiani; Jumansyah, L.M. Risman Dwi
KUBIK Vol 9 No 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v9i2.39877

Kemiskinan multidimensi tetap menjadi tantangan serius di Indonesia meskipun telah mengalami penurunan dalam beberapa tahun terakhir. Penelitian ini bertujuan menganalisis dan membandingkan pola kemiskinan multidimensi di 34 provinsi Indonesia menggunakan metode K-Means dan OPTICS Clustering. Data kemiskinan multidimensi yang digunakan mencakup aspek ekonomi, pendidikan, ketenagakerjaan, dan standar hidup dari Badan Pusat Statistik. Analisis statistik deskriptif mengungkapkan kesenjangan signifikan antar provinsi dalam berbagai dimensi kemiskinan, dengan korelasi tertinggi sebesar 0,4 antara dimensi pendidikan dan status ketenagakerjaan. K-Means Clustering mengidentifikasi 5 cluster provinsi dengan karakteristik beragam, menunjukkan adanya trade-off antara akses fasilitas dan tingkat kemiskinan. Sementara itu, OPTICS Clustering menghasilkan 2 cluster utama, dengan cluster 1 terdiri dari 24 provinsi yang memiliki kondisi cenderung homogen dan cluster 2 terdiri dari 7 provinsi dengan karakteristik yang berbeda secara signifikan. Perbandingan performa menunjukkan OPTICS unggul dengan nilai Silhouette Index dan WCSS yang lebih baik dibandingkan K-Means. Temuan ini memberikan kontribusi penting dalam analisis kemiskinan multidimensi di Indonesia dan dapat dimanfaatkan untuk merancang program pengentasan kemiskinan yang lebih terlokalisasi sesuai karakteristik masing-masing cluster.

Perbandingan Metode K-Means dan OPTICS dalam Penggerombolan Kemiskinan Multidimensi di Indonesia Sari, Devi Permata; Rizqi, Tasya Anisah; Fitrianto, Anwar; M.S, Erfiani; Jumansyah, L.M. Risman Dwi
KUBIK Vol 9 No 2 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v9i2.39877

IDENTIFICATION OF PRIMARY SCHOOL LITERACY ACHIEVEMENT FACTORS IN PROVINCE X USING ORDINAL STEPWISE LOGISTIC Azizah, Siti Nur; Gustiara, Dela; Fitrianto, Anwar; Erfiani; Silvianti, Pika
Jurnal Statistika dan Aplikasinya Vol. 9 No. 1 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09103

Literacy is a foundational skill that underpins students’ academic success and lifelong opportunities. Low literacy skills can result in long-term disadvantages such as limited access to higher education, low productivity, and social inequality. Indonesia continues to face challenges in improving students' literacy achievement, particularly at the primary school level. According to the PISA 2022 results, Indonesia ranked 69th out of 81 countries, indicating that students’ literacy levels remain relatively low. This study aims to identify the factors that influence the literacy achievement of primary school students in Province X. The analytical method employed is ordinal logistic regression with a backward stepwise approach. The dependent variable is the level of literacy achievement (categorized as low, moderate, and good), while the independent variables include learning quality, teacher reflection and improvement, instructional leadership, school climate (including safety, diversity, and inclusiveness), and curriculum type. The results show that the final selected model follows the partial proportional odds assumption and includes only the significant predictors identified through backward stepwise elimination. Variables that positively influence literacy achievement include safety climate, diversity, inclusiveness, curriculum type, and teachers’ reflection and improvement of learning. Model evaluation using AIC, BIC, and accuracy measures indicates good predictive performance. These findings offer valuable insights for policymakers in designing strategies to enhance literacy through strengthening school climate and improving the quality of teaching and learning.

Logistic regression model for identifying factors affecting hospitalization of children with pneumonia Fitrianto, Anwar; Wan Muhamad, Wan Zuki Azman
Al-Jabar: Jurnal Pendidikan Matematika Vol 13 No 2 (2022): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v13i2.10641

Pneumonia is a lung infection that could happen in babies, children, adults and older people. However, pneumonia in infants and older adults is more serious. Several studies found that infants are more likely to get pneumonia if they live in low-income families. The study aimed to identify factors that cause children to be hospitalized for pneumonia. The binary logistic regression analysis was performed to build a full model regardless of the significance of the variables. The forward selection approach was used to select the significant variables. It was found that the age of the mother, cigarette smoked by the mother during pregnancy, duration (in months) of the children on solid food, and the age when the child had pneumonia with the p-value of 0.0009, 0.0010, 0.0003 and less than 0.0001, respectively. The odds ratio of mother's age, cigarette smoked by mother during pregnancy, how many months the child on solid food, and children’s age when they had pneumonia are 0.69, 6.22, 0.40 and 0.60, respectively.

Statistical integration in excise supervision: Multinomial logistic regression for detecting risk factors of tobacco factory excise violations Riansyah, Boy; Nisa Nur Aisyah; Anwar Fitrianto; Aam Alamudi
Desimal: Jurnal Matematika Vol. 8 No. 2 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/xxvpmv08

Excise tax serves as a fiscal instrument used by the government to control the consumption of goods with negative externalities for society and the environment, such as tobacco and alcoholic beverages. In Indonesia, tobacco excise remains the largest contributor to national excise revenue, amounting to IDR 216.9 trillion in 2024, or approximately 95.8% of the total. Monitoring violations in the tobacco excise sector is crucial to safeguarding state revenue and ensuring regulatory effectiveness. In the context of classifying violations with more than two categories, multinomial logistic regression is an appropriate statistical method for analyzing the influence of independent variables on the probability of each violation type. This study aims to classify types of excise violations based on internal characteristics of tobacco manufacturers using multinomial logistic regression. The data were obtained from enforcement documentation in 2023 by the Directorate General of Customs and Excise, with four categories of violations serving as the response variable. The issue of class imbalance was addressed by comparing oversampling and weighting techniques. Evaluation results indicate that oversampling produced superior model performance. Partially, variables such as business entity type, asset ownership status, and company age significantly influenced the likelihood of specific violations. Companies with non-permanent asset ownership and complex organizational structures tend to have a higher risk of non-compliance. These findings underscore the importance of implementing risk-based supervision that considers operational profiles as key indicators of potential violations.

KOMPARASI TEKNIK UNDERSAMPLING DAN OVERSAMPLING PADA REGRESI LOGISTIK BINER DALAM MENDUGA FAKTOR DETERMINAN BERHENTI MEROKOK PENDUDUK LANJUT USIA Amelia, Reni; Indahwati; Erfiani; Fitrianto , Anwar; Rizki, Akbar
Jurnal TIMES Vol 10 No 2 (2021): Jurnal TIMES
Publisher : STMIK TIME

Teknik resampling adalah salah satu teknik pre-processing untuk menyeimbangkan distribusi data sehingga mengurangi efek distribusi kelas atau kategori yang tidak seimbang. Teknik resampling yang biasa digunakan adalah random oversampling dan random undersampling. Dalam penelitian ini, random oversampling digunakan untuk menyeimbangkan data dengan cara oversampling secara acak pada kelas minoritas (penduduk lansia yang berhenti merokok). Random undersampling digunakan untuk menyeimbangkan data dengan cara undersampling (mengeliminasi) secara acak kelas mayoritas (penduduk lansia yang masih merokok). Data yang telah diproses dengan resampling selanjutnya dilakukan pemodelan dengan model regresi logistik biner. Model regresi logistik biner dengan random undersampling merupakan model terbaik karena memiliki balanced accuracy terbesar. Peubah yang signifikan memengaruhi berhenti merokok adalah pendidikan, pekerjaan, akses internet, dan usia lansia.

PENDEKATAN GEOGRAPHICALLY WEIGHTED ZERO INFLATED POISSON REGRESSION (GWZIPR) DENGAN PEMBOBOT FIXED BISQUARE KERNEL PADA KASUS DIFTERI DI INDONESIA Ismah, Ismah; Sumertajaya, I Made; Djuraidah, Anik; Fitrianto, Anwar
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 1 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The number of deaths due to diphtheria is counts data and there is a considerable presence of zeros (excess zeros). Besides, data on the spread of disease are generally geographically oriented or observed in each particular region, which is a type of spatial data. Geographically Weighted Zero Inflated Poisson Regression (GWZIPR), as the development of Geographically Weighted Regression (GWR) and Zero Inflated Poisson (ZIP) models will be used as a model in processing provincial diphtheria data in Indonesia in 2018, with the independent variable percentage of diphtheria cases (X1), percentage of vaccinated numbers (X2) and percentage of the population (X3) in each province in Indonesia. Estimating model parameters uses the method of maximum likelihood estimation. While the weighting function used is fixed bisquare kernel. Data is processed using software R packages lctools. The results were obtained if the model involved all three independent variables, the effect of the three independent variables on the number of deaths due to diphtheria was not significant. This is because there is a strong and significant relationship between independent variables, so that if the model does not involve a variable percentage of the population (population density), the percentage of vaccinated people affects the number of deaths caused by diphtheria significantly in an area. So that the provision of immunization vaccines can reduce the number of deaths caused by diphtheria

Co-Authors -, Salsabila A. A., Muftih Aam Alamudi Abd. Rahman Adeline Vinda Septiani Agus M Soleh Agus Mohamad Soleh Ahmad Syauqi Aimandiga, Carlya Agmis Aji Hamim Wigena Alfa Nugraha Alfa Nugraha Pradana Alfa Nugraha Pradana Alfa Nugraha Pradana Alfa Nugraha Pradana Alfi Indah Nurrizqi Alfiryal, Naufalia Alifviansyah, Kevin Aliu, Mufthi Alwi ALIU, MUFTIH ALWI Amalia Kholifatunnisa Amanda, Nabila Amatullah, Fida Fariha Amelia, Reni Amir Abduljabbar Dalimunthe Anadra, Rahmi Anang Kurnia Anang Kurnia Angelia, Riza Rahmah Anik Djuraidah Anisa Nurizki Annissa Nur Fitria Fathina Ardhani, Rizky Arifa, Panji Lokajaya Aristawidya, Rafika Askari, M. Aiman Asri Pratiwi, Asri Assyifa Lala Pratiwi Hamid Azis, Tukhfatur Rizmah Aziza, Vivin Nur Bagus Sartono Budi Susetyo Bukhari, Ari Shobri Cahya Alkahfi Choon, Lai Ming Daswati, Oktaviyani Defri Ramadhan Ismana Deri Siswara Dessy Rotua Natalina Siahaan Dessy Siahaan Devi Permata Sari Dian Handayani Dwi Jumansyah, L.M. Risman Erfiani Erfiani Erfiani Erfiani Erfiani Erfiani Fadilah, Anggita Rizky Fahira, Fani Farit M Affendi Farit M. Afendi Farit M. Afendi Farit Mochamad Afendi Fatimah Fatimah Fauziah, Monica Rahma Febriati, Baiq Nina Fulazzaky, Tahira Ghina Fauziah Gustiara, Dela Hari Wijayanto Harismahyanti A., Andi Hasnataeni, Yunia Hasnita Hasnita Heri Cahyono I Made Sumertajaya Ilham Azagi Ilmani, Erdanisa Aghnia Imam Hanafi Indah, Yunna Mentari Indahwati Indahwati Indahwati Indahwati, Indahwati Irsyifa Mayzela Afnan Irzaman, Irzaman Ismah, Ismah Isna Shofia Mubarokah Iswan Achlan Setiawan Iswati Ita Wulandari Jamaluddin Rabbani Harahap Jap Ee Jia Jia, Jap Ee Jumansyah, L. M. Risman Dwi Jumansyah, L.M. Risman Dwi Kamila, Sabrina Adnin Kapiluka, Kristuisno Martsuyanto Kevin Alifviansyah Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Khusnia N. K. Khusnia Nurul Khikmah Kriswan, Suliana Kusman Sadik L.M. Risman Dwi Jumansyah La Ode Abdul Rahman La Ode Abdul Rahman Linganathan, Punitha lmam Hanafi M. Aiman Askari M.S, Erfiani Maisa Salsabila Manaf, Silmi Annisa Rizki Marshelle, Sean Megawati Megawati Muftih Alwi Aliu Muftih Alwi Aliu Muh Akbar Idris Muh. Sunan Muhadi, Rizqi Annafi Muhammad Irfan Hanifiandi Kurnia Muhammad Syafiq Muhammad Yusran mutiah, siti Nabila Fida Millati Nabila Ghoni Trisno Hidayatulloh Nadira Nisa Alwani Nashir, Husnun Nisa Nur Aisyah Novi Hidayat Pusponegoro Nugraha, Adhiyatma Nur Hidayah Nur Khamidah NURADILLA, SITI Nurizki, Anisa Pangestika, Dhita Elsha Pika Silvianti Pradnya Sri Rahayu Prasetya, I Putu Gde Inov Bagus Pratiwi, Nafisa Berliana Indah Punitha Linganathan Putri Auliana Rifqi Mukhlashin Putri, Mega Ramatika Putri, Oktaviani Aisyah Rachmat Bintang Yudhianto Rafika Aufa Hasibuan Rahmasari, Hazelita Dwi Rahmatun Nisa, Rahmatun Rais Ramadhan, Syaifullah Yusuf Reka Agustia Astari Reni Amelia Reni Amelia Retna Nurwulan Reyuli Andespa Riansyah, Boy Rifda Nida’ul Labibah Riska Yulianti, Riska Rizaldi Boer Rizki Manaf, Silmi Anisa Rizki, Akbar Rizqi, Tasya Anisah Sachnaz Desta Oktarin salsa bila Sari, Jefita Resti Seta Baehera Setyowati, Silfiana Lis Siau Hui Mah Siau Man Mah Silmi Annisa Rizki Manaf Siregar, Indra Rivaldi Siti Hafsah Siti Hasanah Siti Nur Azizah, Siti Nur Sofia Octaviana Sony Hartono Wijaya Suantari, Ni Gusti Ayu Putu Puteri Suliana Kriswan Sundari, Marta Tangke, Nabillah Rahmatiah Titin Agustina Titin Yuniarty Yuniarty Uswatun Hasanah Utami Dyah Syafitri Utami, Annisa Putri Utomo, Agung Tri Vitona, Desi Vivin Nur Aziza Wahda, Aisya Wina Waliulu, Megawati Zein Wan Muhamad, Wan Zuki Azman Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Waode, Yully Sofyah Wawan Saputra Widyawati, Amalia Safira Winata, Hilma Mutiara Xin, Sim Hui Yenni Angraini Yudhianto, Rachmat Bintang Yuniarsyih R.A, Rizqi Dwi Yusuf, Fajar Athallah Zaenal, Mohamad Solehudin Zahid, Muhammad Farhan Zahra, Latifah Zein Rizky Santoso

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