Article Per Year (5 Year)
p-Index From 2021 - 2026
6.948
P-Index
This Author published in this journals
All Journal FORUM STATISTIKA DAN KOMPUTASI Media Statistika 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) 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 Inferensi 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 Indonesian Journal of Statistics and Its Applications Jurnal Info Kesehatan Limits: Journal of Mathematics and Its Applications
Erfiani Erfiani
Pogram Studi Statistika Dan Sains Data, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Institut Pertanian Bogor, Indonesia
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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 70 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 70 Documents
Search

 3   4   5   6   7 
Analisis Pola Konvergensi Transpor Kelembapan Udara di Indonesia Bagian Barat Menggunakan K-Means dengan Pembobotan Statistik dan Hierarchical Shape-Based Clustering Pratiwi, Asri; Azis, Tukhfatur Rizmah; Fitrianto, Anwar; Erfiani, 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.v9i2.39753

Abstract

This study analyzes the convergence patterns of Vertically Integrated Moisture Transport (VIMT) in the western region of Indonesia using the K-Means method with statistical weighting and Hierarchical Shape-Based Clustering based on Dynamic Time Warping (DTW). Daily data on specific humidity, zonal wind speed, and meridional wind speed from 2020–2023 were used to calculate VIMT. Clustering methods were utilized to identify grouping patterns in moisture transport data. The results showed that moisture convergence significantly increased during the rainy season (November–February). Using the K-Means method, five clusters with clearer separations were obtained compared to the four clusters produced by the Hierarchical Clustering method. Performance evaluation using Silhouette and Calinski-Harabasz scores indicated that the K-Means method was superior, with scores of 0.37 and 104.88 compared to 0.13 and 96.34 for the Hierarchical method. This provides an understanding of the moisture transport patterns, serving as a reference for predicting weather and climate patterns, thereby supporting efforts to mitigate the impacts of extreme weather in Western Indonesia.
Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification Indah, Yunna Mentari; Aristawidya, Rafika; Fitrianto, Anwar; Erfiani, Erfiani; Jumansyah, L.M. Risman Dwi
Jambura Journal of Mathematics Vol 7, No 1: February 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v7i1.28290

Abstract

Machine learning classification is an effective tool for categorizing data based on patterns, which is particularly useful in analyzing the Human Development Index (HDI) in Indonesia. HDI serves as a key indicator of regional development progress, making it crucial to classify HDI categories at the regency/city level to support targeted development planning. This study aims to compare the performance of three ensemble-based classification methods—Random Forest, XGBoost, and LightGBM—in classifying HDI categories in Indonesia. Data from the Central Bureau of Statistics (BPS) in 2023, comprising 514 observations across nine variables, was used for analysis. The study applied these algorithms to analyze the most influential variables affecting HDI. The results show that LightGBM outperformed both Random Forest and XGBoost, achieving an accuracy of 0.937 without outlier handling and 0.944 with outlier handling. Additionally, per capita expenditure was identified as the most influential factor in predicting HDI. These findings contribute to the field of statistical modeling by demonstrating how ensemble methods can improve classification accuracy and provide valuable insights for data-driven policymaking, thus enhancing regional development planning and supporting future HDI-related research.
EDMODO IMPACTS: MEDIATING DIGITAL CLASS AND ASSESSMENT IN ENGLISH LANGUAGE TEACHING Aminah, Aminah; Alamanda, Dinda Aprilia; Erfiani, Erfiani; Wati, Wahyuni Kencana; Ihsan, Muhammad Taufik
Jurnal Riset dan Inovasi Pembelajaran Vol. 1 No. 2 (2021): May-August 2021
Publisher : Education and Talent Development Center Indonesia (ETDC Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51574/jrip.v1i2.37

Abstract

This study aims at investigating the impact of the use of Edmodo on the digital class in the English learning assessment. This type of research is the method library research. This study uses journals and articles as reference to collecting data. To answer the literature review, the writer used data that is collected, studied, and treated then combined to get valid and relevant results by using the Internet as a medium to obtain data. In this paper there are three parts used to respond to the literature review: Terminology of Edmodo, Teaching Learning Process and Edmodo, and Edmodo Impact. Research shows that Edmodo's impact on digital classes in the English learning assessments students in the form of learning and made it easier for teachers to convey lessons, content, tasks, and file sharing easy access to all students. And with CBT, it makes it easier for teachers to assess a student's work with computer help. Edmodo became another evaluation so that the results of the examination were objective and accurate. Through Edmodo as a student's performance assessment mode, there is no cheating that students do in studying because students are working independently
Characteristics of Machine Learning-based Univariate Time Series Imputation Method Ramadhani, Dini; Soleh, Agus Mohamad; Erfiani, Erfiani
JUITA: Jurnal Informatika JUITA Vol. 12 No. 2, November 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i2.23453

Abstract

Handling missing values in univariate time series analysis poses a challenge, potentially leading to inaccurate conclusions, especially with frequently occurring consecutive missing values. Machine Learning-based Univariate Time Series Imputation (MLBUI) methods, utilizing Random Forest Regression (RFR) and Support Vector Regression (SVR), aim to address this challenge. Considering factors such as time series patterns, missing data patterns, and volume, this study explores the performance of MLBUI in simulated Autoregressive Integrated Moving Average (ARIMA) datasets. Various missing data scenarios (6%, 10%, and 14%) and model scenarios (Autoregressive (AR) models: AR(1) and AR(2); Moving Average (MA) models: MA(1) and MA(2); Autoregressive Moving Average (ARMA) models: ARMA(1,1) and ARMA(2,2); and Autoregressive Integrated Moving Average (ARIMA) models: ARIMA(1,1,1) and ARIMA(1,2,1)) with different standard deviations (0.5, 1, and 2) were examined. Five comparative methods were also used in this research, including Kalman StructTS, Kalman Auto-ARIMA, Spline Interpolation, Stine Interpolation, and Moving Average. The research findings indicate that MLBUI performs exceptionally well in imputing successive missing values. The results of this study indicate that the performance of MLBUI in imputing consecutive missing values, based on MAPE, yielded values of less than 10% across all scenarios used.
EVALUASI KEPUASAN PENGGUNA JASA LABORATORIUM KIMIA PT KRAKATAU STEEL (PERSERO) TBK TAHUN 2012-2013 Hilda Zaikarina; . Erfiani; I Made Sumertajaya
Indonesian Journal of Statistics and Applications Vol 1 No 1 (2017)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v1i1.50

Abstract

One of the services contained in PT Krakatau Steel (Persero) Tbk is the chemical composition analysis services in the chemistry lab. Management system that will create a well-managed laboratoryperformance is optimal. Manage standard chemistry laboratory is SNI ISO/IEC 17025. Discussed in this standard laboratory management such as through customer feedback. Laboratory customers selected through stratified random sampling with customer categories as strata, like suppliers, derived from plant and internal processes are not routine. In the research lab result that the customer will be satisfied, including services rendered for Customer Satisfaction Index (CSI) is greater than 70% with the overall characteristics of the respondents subscription in the laboratory was 11.6 years. Overall the indicators included in the priority importance performance analysis (IPA) and has a value kesenjangan beyond the maximum tolerance through kesenjangan analysis approach is the completeness of laboratory equipment (F) and speed of service (K). Keywords : customer satisfaction index (CSI), gap analysis, importance performance analysis (IPA)
PENERAPAN CYLINDRICAL DAN FLEXIBLE SPACE TIME SCAN STATISTIC DALAM MENGIDENTIFIKASI KANTONG KEMISKINAN DI PULAU JAWA TAHUN 2011-2015 Zaima Nurrusydah; Erfiani Erfiani; Bagus Sartono
Indonesian Journal of Statistics and Applications Vol 3 No 2 (2019)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v3i2.274

Abstract

The Indonesian government formed the National Team for the Acceleration of Poverty Reduction (TNP2K) to eradicate poverty. TNP2K requires identification of priority areas or poverty hotspots so that the program can be targeted. Scan statistic is one of the most widely used methods to identify poverty hotspots. Cylindrical STSS uses cylindrical scanning windows while most geographical areas are not circular. Flexible STSS is able to detect poverty hotspots in a flexible form. This study aims to identify poverty hotspots using Cylindrical and Flexible STSS then compare the results of both and then determine the best STSS method. Cylindrical STSS tends to have wider hotspots than Flexible STSS. There are a number of districts that are not eligible to be included as poverty Flexible STSS is able to produce better poverty hotspots by not including these districts Poverty hotspots produced by Flexible STSS have higher LLR values. The more suitable STSS method has optimal K values and high suitability with TNP2K priority areas. Cylindrical STSS has an optimal K value when K = 8 and 9. Flexible STSS has a constant LLR value. Flexible STSS has a higher LLR value than Cylindrical STSS at each K value. Flexible STSS with K = 9 has optimal K and high suitability with TNP2K priority areas so that it is the more suitable STSS method to identify poverty hotspots in Java.
IMPLEMENTASI TRANSFORMASI FOURIER UNTUK TRANSFORMASI DOMAIN WAKTU KE DOMAIN FREKUENSI PADA LUARAN PURWARUPA ALAT PENDETEKSIAN GULA DARAH SECARA NON-INVASIF Umam Hidayaturrohman; Erfiani Erfiani; Farit M Afendi
Indonesian Journal of Statistics and Applications Vol 4 No 2 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i2.504

Abstract

Diabetes mellitus is the result of changes in the body caused by a decrease of insulin performance which is characterized by an increase of blood sugar level. Detection of blood sugar can be done with Invasive methods or non-invasive methods. However, non-invasive methods are considered better because they can check early, faster and accurate. The prototype output is values of intensity in the time domain, thus fourier transformation is very much needed to transform into the frequency domain. In this study, Fourier transformation methods used are Discrete Fourier Transform (DFT), Fast Fourier Transform Radix-2, and Fast Fourier Transform Radix-4. Evaluation for the best method is done by comparing the processing speed of each method. The FFT Radix-4 method is more effective to perform the transformation into the frequency domain. The average processing speed with the FFT Radix-4 method reaches 2.67×105 nanoseconds, and this is much faster 5.06×106 nanoseconds than the FFT Radix-2 method and 2.40×107 nanoseconds faster than the DFT method.
ROBUST SPATIAL REGRESSION MODEL ON ORIGINAL LOCAL GOVERNMENT REVENUE IN JAVA 2017 Winda Chairani Mastuti; Anik Djuraidah; Erfiani Erfiani
Indonesian Journal of Statistics and Applications Vol 4 No 1 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i1.573

Abstract

Spatial regression measures the relationship between response and explanatory variables in the regression model considering spatial effects. Detecting and accommodating outliers is an important step in the regression analysis. Several methods can detect outliers in spatial regression. One of these methods is generating a score test statistics to identify outliers in the spatial autoregressive (SAR) model. This research applies a robust spatial autoregressive (RSAR) model with S- estimator to the Original Local Government Revenue (OLGR) data. The RSAR model with the 4-nearest neighbor weighting matrix is the best model produced in this study. The coefficient of the RSAR model gives a more relevant result. Median absolute deviation (MdAD) and median absolute percentage error (MdAPE) values ​​in the RSAR model with 4-nearest neighbor give smaller results than the SAR model.
Comparison of Functional Regression and Functional Principal Component Regression for Estimating Non-Invasive Blood Glucose Level: Perbandingan Metode Regresi Fungsional dan Regresi Komponen Utama Fungsional untuk Menduga Kadar Glukosa Darah pada Alat Non-Invasif Nurul Fadhilah; Erfiani Erfiani; Indahwati Indahwati
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i1p14-25

Abstract

The calibration method is an alternative method that can be used to analyze the relationship between invasive and non-invasive blood glucose levels. Calibration modeling generally has a large dimension and contains multicolinearities because usually in functional data the number of independent variables (p) is greater than the number of observations (p>n). Both problems can be overcome using Functional Regression (FR) and Functional Principal Component Regression (FPCR). FPCR is based on Principal Component Analysis (PCA). In FPCR, the data is transformed using a polynomial basis before data reduction. This research tried to model the equations of spectral calibration of voltage value excreted by non-invasive blood glucose level monitoring devices to predict blood glucose using FR and FPCR. This study aimed to determine the best calibration model for measuring non-invasive blood glucose levels with the FR and FPCR. The results of this research showed that the FR model had a bigger coefficient determination (R2) value and lower Root Mean Square Error (RMSE) and Root Mean Square Error Prediction (RMSEP) value than the FPCR model, which was 12.9%, 5.417, and 5.727 respectively. Overall, the calibration modeling with the FR model is the best model for estimate blood glucose level compared to the FPCR model.
PERBANDINGAN METODE KEKAR BIWEIGHT MIDCOVARIANCE DAN MINIMUM COVARIANCE DETERMINANT DALAM ANALISIS KORELASI KANONIK Riana, Freza; Hamim Wigena, Aji; ., Erfiani
Krea-TIF: Jurnal Teknik Informatika Vol 3 No 2 (2015)
Publisher : Fakultas Teknik dan Sains, Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (475.8 KB) | DOI: 10.32832/kreatif.v3i2.410

Abstract

Canonical Correlation Analysis(CCA) is a multivariate linear used toidentify and quantify associationsbetween two sets of random variables. Itsstandard computation is based on samplecovariance matrices, which are howeververy sensitive to outlying observations.The robust methods are needed. Thereare two robust methods, i.e robustBiweight Midcovariance (BICOV) andMinimum Covariance Determinant(MCD) methods. The objective of thisresearch is to compare the performanceof both methods based on mean squareerror. The data simulations aregenerated from various conditions. Thevariation data consists of the proportionof outliers, and the kind of outliers: shift,scale, and radial outlier. Theperformance of robust BICOV method inCCA is the best compared to MCD andClassic
Co-Authors . Aunuddin A. A., Muftih Abd. Rahman Abqorunnisa, Farah Agung Tri Utomo Agus Mohamad Soleh Ahmad Khairul Reza Ahmad Nur Rohman Ahmad Syauqi Aji Hamim Wigena Alamanda, Dinda Aprilia Alfa Nugraha Pradana Alfa Nugraha Pradana Alfa Nugraha Pradana Aliu, Mufthi Alwi ALIU, MUFTIH ALWI Amatullah, Fida Fariha Amelia, Reni Aminah Aminah Anadra, Rahmi Anang Kurnia Anik Djuraidah Anissa Tsalsabila Ardhani, Rizky Arini Annisa Adi Aristawidya, Rafika ASEP SAEFUDDIN Asri Pratiwi, Asri Assyifa Lala Pratiwi Hamid Aunuddin . Aunuddin Aunuddin Azis, Tukhfatur Rizmah Bagus Sartono Bartho Sihombing Bimawan Sudarmoko Budi Susetyo Daswati, Oktaviyani Daulay, Nurmai Syaroh Deti Anggraeni Ekawati Dian Kusumaningrum Dini Ramadhani Dwi Jumansyah, L.M. Risman Dwi Putri Kurniasari Fanny Amalia Farit M Afendi Farly Shabahul Khairi Fatimah Fatimah Fauziah, Monica Rahma Fitrianto, Anwar Freza Riana Fulazzaky, Tahira Hamim Wigena, Aji Hari Wijayanto Harismahyanti A., Andi Hasnataeni, Yunia Herlin Fransiska Hilda Zaikarina 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 Khikmah, Khusnia Nurul Khusnia Nurul Khikmah Lestari, Nila Made Agung Prebawa Parama Artha Mahfuz Hudori Marshelle, Sean Megawati Megawati Misrika, Dahlia Mohammad Masjkur Muggy David Cristian Ginzel Muhammad Nur Aidi mutiah, siti Nadira Nisa Alwani Nenden Rahayu Puspitasari Novitri Novitri Nugraha, Adhiyatma Nur Khamidah Nurul Fadhilah Pardomuan Robinson Sihombing Qalbi, Asyifah R, Arifuddin Rahmatun Nisa, Rahmatun Ramadhani, Dini Ratih Dwi Septiani Reka Agustia Astari Reni Amelia Retno Dwi Jayanti Rika Rachmawati Riska Asri Pertiwi Siregar, Indra Rivaldi Sofia Octaviana Tetinia Gulo Tiara, Yesan Umam Hidayaturrohman Uswatun Hasanah Utami Dyah Syafitri Vitona, Desi Waode, Yully Sofyah Wati, Wahyuni Kencana Weisha, Ghea Wigena, Aji Wijaya, Ferdian Bangkit Winda Chairani Mastuti Windi D.Y Putri Yulia Christina Yuniar Istiqomah Zaima Nurrusydah