About the journal
Jurnal Diferensial is an open-access journal published by Universitas Nusa Cendana in Indonesia, publishing in ENGLISH and INDONESIAN. It is listed in DOAJ according to the sources read. Declared review time at DOAJ: 21 weeks. Facts are reproduced as recorded at their sources with their capture dates; PublishLens indicators are available after sign-in.
Basic facts
- Publisher
- Universitas Nusa Cendana
- ISSN
- 2775-9644
- Country
- Indonesia
- Languages
- ENGLISH, INDONESIAN
- Access
- Open access
- Articles in DOAJ
- 90
- Declared review time
- 21 weeks
- Declared peer-review model
- peer_review
- Official website
- https://ejurnal.undana.ac.id/index.php/JD/
Index listings
- DOAJ · 2025-02-25
- Indexing
- DOAJ
- APC
- —
- Declared review time (DOAJ)
- 21 weeks — journal-declared only (not measured)
- Activity (OpenAlex)
- Active — latest works 2026
- PublishLens list status
- Shown after sign-in
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- Choose your university and rank below ↓
Methodology signals (dated facts from their sources)
Details of the evaluation under the published methodology are shown to signed-in users (free).
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Descriptive metadata from public sources (DOAJ, OpenAlex, PubMed) as of the capture date shown — contains no assessment or judgment.
Articles in DOAJ
90
Most recent article
6 months ago
Average review time (journal-declared via DOAJ)
21weeks
Works in OpenAlex
89
Last recorded publication year
2025
h-index
3
i10-index
0
From OpenAlex open data (CC0).
Editorial & policy10
- Last DOAJ review date
- 2025-02-25
- Added to DOAJ
- 2025-02-25
- Declared plagiarism screening
- Declared
- Other fees beyond APC
- Yes
- Editorial board
- Official page ↗
- Open references deposited at Crossref
- 0%
- ORCID iDs in current deposits
- 2%
- Enrolled in Crossref Similarity Check
- ✓
- Deposits licence metadata at Crossref
- ✓
- APC waiver policy
- View policy
- Peer-review policy
- View policy
Identity & continuity1
- Source type
- journal
Classification2
Subjects (DOAJ)
LCC codes
Subject areas
- Data Mining and Machine Learning Applications
- Data Mining and Machine Learning Applications
- Graph Labeling and Dimension Problems
- Graph Labeling and Dimension Problems
- Computer Science and Engineering
- Economic Growth and Fiscal Policies
- Computer Science and Engineering
- Economic Growth and Fiscal Policies
Show all subjects (50)
- Graph theory and applications
- Blockchain Technology in Education and Learning
- Mathematical and Theoretical Epidemiology and Ecology Models
- Mathematical and Theoretical Epidemiology and Ecology Models
- Graph theory and applications
- Management and Optimization Techniques
- Blockchain Technology in Education and Learning
- Management and Optimization Techniques
- Multimedia Learning Systems
- Multimedia Learning Systems
- Edcuational Technology Systems
- Fractional Differential Equations Solutions
- COVID-19 epidemiological studies
- COVID-19 epidemiological studies
- Fractional Differential Equations Solutions
- Edcuational Technology Systems
- Public Health and Nutrition
- Varied Academic Research Topics
- Varied Academic Research Topics
- Public Health and Nutrition
- SMEs Development and Digital Marketing
- Vibrio bacteria research studies
- Decision Support System Applications
- Educational Methods and Media Use
- Numerical methods for differential equations
- Mathematics Education and Pedagogy
- Educational Methods and Impacts
- SMEs Development and Digital Marketing
- Agricultural Research and Practices
- Vibrio bacteria research studies
- Decision Support System Applications
- Educational Methods and Media Use
- Mathematics Education and Pedagogy
- Numerical methods for differential equations
- Educational Methods and Impacts
- Agricultural Research and Practices
- Nonlinear Waves and Solitons
- Finite Group Theory Research
- Computational Drug Discovery Methods
- Finite Group Theory Research
- Computational Drug Discovery Methods
- Nonlinear Waves and Solitons
Keywords (DOAJ)
- numerical analysis
- analysis
- algebra
- discrete mathematics and combinatorics
- statistics and data science
- biomathematics
Community confirmations — what users saw in MJL or Scopus Sources; not platform verification and never part of any score.
The journal's record in other sources:Web of Science MJLDOAJ