About Journal

Indonesian version:

Emerging Statistics and Data Science Journal (ESDS) dikelola oleh Jurusan Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Islam Indonesia. Tujuan ESDS diharapkan dapat sebagai wadah publikasi artikel ilmiah akademisi dan praktisi bidang kajian statistika dan terapannya. Dalam rangka menjaga kualitas dari artikel yang dipublikasikan oleh ESDS, kami menjalin kerjasama dengan dosen-dosen dari berbagai perguruan tinggi dalam negeri dan senantiasa melakukan evaluasi berkala. ESDS berkomitmen untuk menerbitkan 3 volume jurnal setiap tahunnya (Januari, Mei, Oktober).

English version:

Emerging Statistics and Data Science Journal (ESDS) by Statistics Department of Faculty of Mathematics and Natural Sciences Universitas Islam Indonesia as scientific articles publication media for statistics academics or practitioners. To ensure our quality, ESDS is establishing collaboration with lecturers from various universities and evaluating our journal periodically. ESDS is now committed to publishing 3 volumes of journal per year (January, May, October).

Focus and Scope

ESDS publishes scientific articles on statistics and its applications, and also in terms of big data and data science. The article can be a research result, a case study, or a literature review, with coverage:

  1. Statistical Methodology – Articles dealing with new and innovative data analysis techniques and methodologies include, but are not limited to: bootstrapping, classification techniques, design of experiments, parametric and nonparametric methods, functional data, fuzzy statistical analysis, nonlinear models, partial least squares, structural equation models, Bayesian analysis, survey sample analysis, and statistics computation.
  2. Applied Statistics in Business, Industry and Social Studies – Articles dealing with econometrics, demography, spatial analysis, time series analysis, longitudinal analysis, spatio-temporal analysis, quality control, and other subjects related to Applied Statistics in Business, Industry and Social Studies.
  3. Data Science – Articles dealing with big data, data exploration, data mining, data science, data visualisation, and machine learning.
  4. Another field which is related to statistics and the applications