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All Journal FORUM STATISTIKA DAN KOMPUTASI Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Sains dan Teknologi Techno.Com: Jurnal Teknologi Informasi JUITA : Jurnal Informatika Kubik KEUNIS Sinkron : Jurnal dan Penelitian Teknik Informatika Syntax Literate: Jurnal Ilmiah Indonesia BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) J Statistika : Jurnal Ilmiah Teori Dan Aplikasi Statistika Zero : Jurnal Sains, Matematika, dan Terapan Teorema: Teori dan Riset Matematika Krea-TIF: Jurnal Teknik Informatika Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Jambura Journal of Mathematics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Inferensi International Journal of Advances in Data and Information Systems InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika KUBIK: Jurnal Publikasi Ilmiah Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Jurnal Riset dan Inovasi Pembelajaran PROSIDING SEMINAR NASIONAL FISIKA (E-JOURNAL) VARIANSI: Journal of Statistics and Its Application on Teaching and Research Xplore: Journal of Statistics Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications Jurnal Info Kesehatan Biodiversitas Journal of Biological Diversity

Erfiani Erfiani

School Of Data Science, Mathematics, And Informatics, IPB University, Bogor, Indonesia

Author-ID : 260170

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Teknik Oversampling Pada Regresi Logistik Ordinal Dalam Menduga Faktor Yang Memengaruhi Risiko Penyebaran Zona Covid-19 di Kabupaten Garut Ghina Fauziah; Indahwati; Erfiani; Anwar Fitrianto; Reni Amelia
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 15 No 2 (2022): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/jstat.vol15.no2.a5596

Covid-19 merupakan penyakit yang disebabkan oleh infeksi virus SARS-CoV-2, pertama kali masuk ke Indonesia pada awal tahun 2020. Adanya wabah covid-19 menyebabkan setiap daerah yang ada di Indonesia khususnya kabupaten Garut harus terbagi ke dalam beberapa risiko zona covid-19 sesuai dengan kondisi dari suatu daerah tersebut. Beberapa faktor yang dapat memengaruhi suatu daerah masuk pada risiko zona tertentu dapat ditentukan berdasarkan jumlah kasus positif covid-19, kasus suspek, kasus kontak erat, jumlah desa, dan kepadatan penduduk daerah tersebut. Regresi logistik ordinal merupakan salah satu analisis regresi yang digunakan untuk menganalisa hubungan antara variabel prediktor dan variabel respon, dimana variabel respon tersebut bersifat kategorik dengan skala ordinal. Oleh karena itu, maka digunakan regresi logistik ordinal untuk mengetahui faktor apa saja yang memberikan pengaruh terhadap pembagian risiko zona covid-19 di kabupaten Garut pada bulan Juli tahun 2021. Sebelum melakukan pemodelan regresi logistik ordinal dilakukan terlebih dahulu proses teknik resampling dengan metode oversampling untuk menangani data yang tidak seimbang pada peubah respon. Berdasarkan pemodelan hasil dari pemodelan serta pengujian secara parsial, didapatkan bahwa peubah bebas yang memiliki pengaruh terhadap risiko zona covid-19 di kabupaten Garut yaitu jumlah desa, kepadatan penduduk, kasus suspek, dan kasus konfirmasi positif dengan nilai akurasi sebesar 85.71%.

Faktor – Faktor yang Memengaruhi Permasalahan Stunting di Jawa Barat Menggunakan Regresi Logistik Biner Silmi Annisa Rizki Manaf; Erfiani; Indahwati; Anwar Fitrianto; Reni Amelia
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 15 No 2 (2022): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/jstat.vol15.no2.a5654

Salah satu bentuk akibat dari kurangnya asupan gizi kronis pada balita adalah stunting. Stunting merupakan permasalahan kesehatan yang saat ini sedang digencarkan untuk diturunkan angka prevalensinya. Permasalahan kesehatan ini berhubungan erat pada pertumbuhan tinggi badan yang lebih rendah dengan anak seusianya. Berdasarkan data Kemenkes per Agustus 2021, Provinsi Jawa Barat menduduki posisi pertama dengan angka balita stunting paling tinggi di Indonesia. Penelitian ini bertujuan untuk mengetahui faktor apa saja yang memengaruhi terjadinya stunting pada balita dan memodelkan dengan metode regresi logistik biner untuk wilayah Jawa Barat. Metode ini dapat menunjukkan faktor yang memengaruhi berdasarkan peubah yang signifikan. Regresi logistik biner akan memodelkan hubungan antara satu atau beberapa peubah prediktor dengan peubah respon yang kategorik. Peubah respon didefinisikan sebagai persentase angka balita stunting dan dibagi kedalam dua kategori yakni tinggi dan rendah. Pengategorian kelas didasarkan pada nilai median pada persentase angka balita stunting. Unit penelitian menuju pada 27 wilayah Kabupaten/Kota di Jawa Barat. Hasil analisis menunjukkan dari 11 peubah prediktor, setelah dilakukan pemodelan terdapat 3 peubah yang berpengaruh signifikan pada taraf nyata 0,10 yakni imunisasi dasar lengkap, tempat pengelolaan makanan yang memenuhi syarat kesehatan, dan penduduk miskin. Model yang terpilih berdasarkan nilai akurasi seimbang terbesar dibandingkan model lainnya yakni dihasilkan nilai akurasi seimbang sebesar 81,59%.

Rancangan G-Optimal pada Peningkatan Kadar Kemurnian Silikon Dioksida Nindya Wulandari; Erfiani Erfiani; Irzaman Irzaman; Utami Dyah Syafitri
Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Vol. 19 No. 2 (2022): Sainmatika : Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam
Publisher : Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/sainmatika.v19i2.9492

Rancangan percobaan merupakan serangkaian uji yang bertujuan mengamati dan mengidentifikasi perubahan-perubahan pada output respon disebabkan oleh perubahan-perubahan pada variabel input dari suatu proses. Penelitian ini bertujuan untuk mendapatkan rancangan terbaik untuk peningkatan kadar SiO2. Silikon Dioksida (SiO2) merupakan salah satu mineral yang paling banyak ditemukan di bumi. SiO2 banyak digunakan di berbagai bidang sehingga ketersediaannya semakin berkurang. Prosedur kemurnian dapat digunakan untuk meningkatkan kemurnian silika yang memiliki kualitas rendah dengan mengubah suhu dan laju kenaikan suhu. Metode yang digunakan adalah desain G-optimal menggunakan algoritma Variable Neighborhood Search (VNS). Model yang digunakan dalam meningkatkan kemurnian silikon dioksida adalah model non-linier yang mengikuti distribusi eksponensial decay. Titik rancangan terbaik yang diperoleh dari rancangan G-optimal pada hubungan antara suhu (oC) dan laju kenaikan suhu (oC/menit) yaitu titik Â 800 ÂoCÂ hingga 900 ÂoC adalah kombinasi titik Â 800 ÂoC dan 1,67 oC/menit, 800 ÂoC dan 2,17 oC/menit, 815 oC dan 4,67 oC/menit, 825 ÂoC dan 4,17 oC/menit, 835 ÂoC dan 5 oC/menit, 855 ÂoC dan 2,17 oC/menit, 880 ÂoC dan 2,34 oC/menit, 895 ÂoC dan 4,67 oC/menit,Â serta 900 oC dan 4 oC/menit dengan nilai G-efisiensinya adalah 96,09%.

Synthetic Minority Oversampling Technique Pada Model Logit dan Probit Status Pengangguran Terdidik Fatimah Fatimah; Anwar Fitrianto; Indahwati Indahwati; Erfiani Erfiani; Khusnia Nurul Khikmah
Jambura Journal of Mathematics Vol 5, No 1: February 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjom.v5i1.17050

Educated unemployment is caused by a misalignment of educational development planning and employment development, resulting in underemployed graduates from various educational institutions. Unemployment data in DKI Jakarta shows an unequal class. Unbalanced data is a severe problem of modeling because it can cause prediction errors that affect the accuracy of the resulting model. Using SMOTE to handle unbalanced data will likely increase the model’s accuracy. This study aims to find the best model for identifying the factors influencing the status of educated unemployment using logit and probit models and handling unbalanced data using SMOTE. The results showed that the independent variables that affect the status of educated unemployment in the logit and probit models are the same: age group and participation in training. The independent variables that affect the status of educated unemployment in the logit and probit models with SMOTE are also the same: age group, marital status, and participation in training. Unbalanced data handling using SMOTE can increase the balanced accuracy value significantly. Balanced accuracy values for the logit and probit models with SMOTE are higher than the logit and probit models without SMOTE. The logit model with SMOTE is the best because it has the highest balanced accuracy value compared to other models. According to the logit model with SMOTE, the educated unemployed in DKI Jakarta are young and have never married. There is a need for the government to play a role in improving the quality of educational institutions in producing graduates who meet company qualifications and can be hired by employers. Unemployed people who have attended the training, despite having a higher education, may also become unemployed. The training provided has not been able to reduce the unemployment rate. As a result, the government should be able to provide training to improve entrepreneurship skills while also providing capital in the form of business loans to reduce educated unemployment.

Penetapan Ekstrakurikuler Wajib untuk Siswa Sekolah Menengah Atas Berdasarkan Kecerdasan Majemuk Muggy David Cristian Ginzel; Asep Saefuddin; Erfiani Erfiani
Xplore: Journal of Statistics Vol. 9 No. 1 (2020)
Publisher : Department of Statistics, IPB

Senior high school in Indonesia is divided into two groups, namely Natural science and Social science. Those grouping of majors is allegedly not appropriate enough the potential of students yet because of the multiple intelligence of each student is different. This study aims to establish an extracurricular program for everyone grouped by multiple intelligences carried out by each student. The method used in this study are the non-hierarchical clustering k-Means and hierarchical clustering Ward method. The k-Means method used to determine the effective number of groups, while Ward method used to identify the member of each cluster and the recommendation of extracurricular in the cluster obtained. Based on the results of the clustering analysis, there are five clusters obtained, Language and Fine Arts; Communication; Leadership; Nature Lovers; and also Design and Photography.

Penerapan Structural Equation Modelling-Partial Least Squares pada Faktor Kemiskinan di Jawa Tengah Arini Annisa Adi; Mohammad Masjkur; Erfiani Erfiani
Xplore: Journal of Statistics Vol. 11 No. 2 (2022):
Publisher : Department of Statistics, IPB

The number of poverty-stricken people in Central Java in March 2020 was 3.98 million people (11.41%), the second-largest in Java. The approximately high number of poverty-stricken people is a priority for the government to reduce poverty. One of the solutions to reduce poverty is knowing the factors that may affect it. The purpose of this study is to identify the factors that affected poverty in Central Java using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) method. This study used data from districts/ cities in Central Java in 2020. In this case, there is one exogenous latent variable for health and three endogenous latent variables for poverty, economy, and human resources. The problem encountered that the observed data is relatively small, specifically for 35 observations and the data distribution is suspected not fulfilled the normal assumptions. In conclusion, the appropriate analysis used in this study is Structural Equation Modeling-Partial Least Squares (SEM-PLS). The results showed that the economic latent variable had a positive but not significant effect on the latent variable of poverty, Human Resources also had a positive but not significant effect, while the latent health variable had a negative and significant effect on the latent variable of poverty. The Q2 value for the latent variable of poverty is 0.333, this shows that 33.3% of the diversity of the latent variable of poverty can be explained by the latent variables of economy, health, and human resources.

Klasifikasi Kadar Glukosa Darah Keluaran Alat Non-invasif Menggunakan Regresi Logistik Ordinal dengan Peringkasan Luas Yuniar Istiqomah; Erfiani Erfiani; Utami Dyah Syafitri
Xplore: Journal of Statistics Vol. 12 No. 1 (2023): Vol. 12 No. 1 (2023)
Publisher : Department of Statistics, IPB

Diabetes Mellitus (DM) is the silent killer because its symptoms tend to go unnoticed. The IPB Non-Invasive Biomarking Team developed a non-invasive monitoring device to check blood. The tool uses the spectroscopy principle and produces an output in the form of a residual value of light intensity. A method is needed to predict the category of blood glucose levels based on the measurement results of non-invasive tools. Classification modeling is one of the methods that can be used to analyze the relationship between the blood glucose level class of invasive measurement results and the residual value of the intensity of non-invasive measurement results. One of the commonly used classification methods is ordinal logistic regression. Light spectrum-based data used as predictor X changes often provide changes that correlate with each other. The principal component analysis reduces its dimensions to become a new set of changes that do not correlate. Graph area summation in the period is the best summarization method because it can take advantage of the general data information. This study uses the ordinal logistic regression method as a modeling method by applying principal component analysis and graph area summation applied to 2017 data and 2019 data. Classification modeling in the 2017 data had a balanced accuracy value of 64,64%. Classification modeling in the 2019 data produced a balanced accuracy value of 57,57%. The design used in the 2017 tool and the 2019 tool is different, causing the residual intensity graph of the non-invasive measurement results to be read differently. The 2017 data model is better applied to homogeneous data and the 2019 data model is better applied to heterogeneous data.

Analisis Kualitas Aplikasi Mobile JKN dan Layanan Care-Center terhadap Kepuasan Peserta JKN-KIS dengan Metode PLS-SEM Made Agung Prebawa Parama Artha; Aji Hamim Wigena; Erfiani Erfiani
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Sains data (data science) telah menjadi perhatian ahli statistika dunia akhir-akhir ini. Dunia industri, bisnis dan ilmu pengetahuan sangat memerlukan ilmu ini untuk melakukan analisis data maupun prediksi untuk perkembangan bisnis, industri maupun bidang - bidang lain di masa depan. Penelitian ini bertujuan untuk mengetahui pengaruh kualitas aplikasi Mobile JKN dan Layanan Care-Center terhadap kepuasan peserta JKN-KIS dengan menggunakan metode PLS-SEM. Teknik pengumpulan data menggunakan kuisioner dengan jumlah responden sebanyak 1.389 orang. Penelitian ini menggunakan pendekatan Partial Least Square-Strucural Equation Modelling (PLS-SEM) yang dapat memprediksi hubungan kausalitas variabel laten eksogen dengan variabel laten endogen. Hasil yang diperoleh dari penelitian ini yaitu nilai loading factor dari semua indikator sudah memenuhi kriteria melebihi dari angka 0.7 atau sering digunakan batas 0,5 sebagai batasan minimal dari nilai loading factor (Kock, 2020). Inner model yang diperoleh pada data dengan taraf nyata 5%: Kepuasan Peserta = 0.38 Kualitas Aplikasi + 0.31 Kualitas Layanan CareCenter +z. Ini artinya Peubah kualitas aplikasi berpengaruh signifikan pada taraf nyata 5% dengan nilai koefisen sebesar 0.38, sedangkan peubah kualitas layanan CareCenter berpengaruh signifikan dengan nilai koefisien sebesar 0.31. Nilai t-statistik untuk peubah Kualitas aplikasi terhadap Kepuasan Peserta sebesar 11,297 dan peubah Kualitas Layanan Care-Center terhadap Kepuasan Peserta sebesar 9,256. Hal ini menunjukkan nilai t-statistik lebih besar dari t-tabel yang artinya Kualitas Aplikasi Mobile JKN dan Layanan Care-Center berpengaruh terhadap Kepuasan Peserta.

The Comparison between Ordinal Logistic Regression and Random Forest Ordinal in Identifying the Factors Causing Diabetes Mellitus Assyifa Lala Pratiwi Hamid; Anwar Fitrianto; Indahwati Indahwati; Erfiani Erfiani; Khusnia Nurul Khikmah
Jambura Journal of Mathematics Vol 5, No 2: August 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjom.v5i2.20289

Diabetes is one of the high-risk diseases. The most prominent symptom of this disease is high blood sugar levels. People with diabetes in Indonesia can reach 30 million people. Therefore, this problem needs further research regarding the factors that cause it. Further analysis can be done using ordinal logistic regression and random forest. Both methods were chosen to compare the modelling results in determining the factors causing diabetes conducted in the CDC dataset. The best model obtained in this study is ordinal logistic regression because it generates an accuracy value of 84.52%, which is higher than the ordinal random forest. The four most important variables causing diabetes are body mass index, hypertension, age, and cholesterol.

Agglomerative Nesting Cluster Analyst in Mapping District/City Health Facilities in West Java Province Nadira Nisa Alwani; Megawati Megawati; Anwar Fitrianto; Erfiani Erfiani; Alfa Nugraha Pradana
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.32043

The use of Hierarchical Clustering is used to group districts or cities in West Java according to the number of health facilities, distance to health facilities and population density using Agglomerative Nesting (AGNES). Clustering in this study utilizes complete linkage clustering. The elbow method produces two optimal clusters which are then validated with the sillhoute coefficient and Calinski-Harabasz. In this study, there are 27 variables in the form of health facilities spread across 27 regencies/cities in West Java in 2021. The results of the cluster analysis formed in this study are 18 districts/cities in cluster one and 9 districts/cities in cluster two

Co-Authors . Aunuddin A. A., Muftih Abd. Rahman Abqorunnisa, Farah Adisti Permatasari Putri Hartoyo Agung Tri Utomo Agus M Soleh Agus Mohamad Soleh Ahmad Khairul Reza Ahmad Nur Rohman Ahmad Syauqi Aji Hamim Wigena Aji Wigena Alamanda, Dinda Aprilia Alfa Nugraha Pradana Alfa Nugraha Pradana Alfa Nugraha Pradana Alifviansyah, Kevin Aliu, Mufthi Alwi ALIU, MUFTIH ALWI Amatullah, Fida Fariha Amelia, Reni Aminah Aminah Amri Luthfi Najih Anadra, Rahmi Anang Kurnia Andi Harismahyanti A. Anik Djuraidah Anissa Tsalsabila Anuraga Jayanegara Ardhani, Rizky Arini Annisa Adi Aristawidya, Rafika ASEP SAEFUDDIN Asri Pratiwi Asri Pratiwi, Asri Assyifa Lala Pratiwi Hamid Aunuddin . Aunuddin Aunuddin Az-Zahra, Putri Nisrina Azis, Tukhfatur Rizmah Bagus Sartono Bartho Sihombing Bimawan Sudarmoko Budi Susetyo Dahlia Misrika Daswati, Oktaviyani Daulay, Nurmai Syaroh Deti Anggraeni Ekawati Dian Kusumaningrum Diaztri Hazam Dwi Jumansyah, L.M. Risman Dwi Putri Kurniasari Fanny Amalia Farit M Afendi Farly Shabahul Khairi Fatimah Fatimah Fauziah, Monica Rahma Ferdian Bangkit Wijaya Fitrianto, Anwar Freza Riana Fulazzaky, Tahira Ghina Fauziah Hamim Wigena, Aji Hari Wijayanto Hasnataeni, Yunia Hilda Zaikarina I Gusti Ngurah Sentana Putra I Made Sumertajaya Ihsan, Muhammad Taufik Ilmani, Erdanisa Aghnia Indah, Yunna Mentari Indahwati Irzaman, Irzaman Ismah, Ismah Julianti, Elisa D Jumansyah, L. M. Risman Dwi Jumansyah, L.M. Risman Dwi Kevin Alifviansyah Khikmah, Khusnia Nurul Khusnia Nurul Khikmah L.M. Risman Dwi Jumansyah Lestari, Nila Made Agung Prebawa Parama Artha Mahfuz Hudori Marshelle, Sean Megawati Megawati Mohammad Masjkur Muggy David Cristian Ginzel Muh Akbar Idris Muhammad Alam Firmansyah Muhammad Nur Aidi Muhammad Syafiq mutiah, siti Mutmainah, Zamrah Nabila Fida Millati Nadira Nisa Alwani Nenden Rahayu Puspitasari Nindya Wulandari Novitri Novitri Nugraha, Adhiyatma Nur Khamidah NURHENI WIJAYANTO Nurul Fadhilah Pardomuan Robinson Sihombing Qalbi, Asyifah R, Arifuddin Rachmat Bintang Yudhianto Rahmatun Nisa, Rahmatun Ramadhani, Dini Ratih Dwi Septiani Reka Agustia Astari Reni Amelia Reni Amelia Retno Dwi Jayanti Rika Rachmawati Riska Asri Pertiwi Sachnaz Desta Oktarina Sari, Jefita Resti Silmi Annisa Rizki Manaf Siregar, Indra Rivaldi Sofia Octaviana Tangdilomban, Claudian Tikulimbong TEGUH JATI PURNAMA Tetinia Gulo Tiara, Yesan Tukhfatur Rizmah Azis Umam Hidayaturrohman Unique DA Resiloy Uswatun Hasanah Utami Dyah Syafitri Vitona, Desi Waode, Yully Sofyah Wati, Wahyuni Kencana Weisha, Ghea Wijaya, Ferdian Bangkit Winda Chairani Mastuti Windi D.Y Putri Yulia Christina Yuniar Istiqomah Zaima Nurrusydah

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