Author Guidelines

Author Guidelines & Manuscript Template

A. General Requirements

  • Originality & Exclusivity: Submitted manuscripts must be original work, have not been published previously in any journal, and are not currently under peer review or consideration in any other publication outlet.
  • Language Quality: Manuscripts must be written in clear, grammatically correct English or Indonesian.
  • Page Length: The article length must range between 8 to 15 pages, including references, tables, and figures.
  • Manuscript Structure: The structure must strictly adhere to the standard IMRAD format (Introduction, Method, Results and Discussion, Conclusion).
B. Manuscript Structure & Formatting Guidelines

Authors are required to prepare their manuscripts according to the following structural specifications:

1. Article Title

Length: Maximum 15–20 words; concise, informative, and reflecting the primary focus of the research.
Formatting: Font size 14pt, Bold, Center alignment.

2. Author Information

Full name(s) of author(s) without academic titles or degrees. Institutional affiliation (Department/Study Program, University/Institution, City, Country). Corresponding author must provide an active email address (institutional or student email domain preferred).

3. Abstract & Keywords

Bilingual Requirement: Written in both English and Indonesian.
Length & Format: 150–250 words presented as a single structured paragraph covering problem statement, objectives, methodology, key findings, and impact.
Keywords: 3–5 terms or phrases, separated by commas.

4. Introduction

Covers research background, research urgency/significance, domain challenges, state-of-the-art literature review (related works), and explicit research objectives.

5. Methodology

Detail data sources, data collection methods (primary/secondary), and system design/development stages. If applying a specific framework (e.g., AI Project Cycle, Waterfall, SDLC), clearly illustrate the workflow using a structural flowchart or diagram.

For Machine Learning / Deep Learning Research, detail the following 6 stages:
  1. Problem Scoping: Definition of problem domain and objectives.
  2. Data Acquisition: Dataset sources and acquisition strategy.
  3. Data Exploration: Data preprocessing, cleaning, and augmentation techniques.
  4. Modelling: Model architecture, hyperparameter configuration, and training protocols.
  5. Evaluation: Performance evaluation metrics (e.g., Accuracy, Precision, Recall, F1-Score).
  6. Deployment: System integration or real-world implementation plans.

6. Results and Discussion

Present experimental outcomes, testing metrics, accuracy curves, or evaluation matrices (Confusion Matrix, Classification Report). Provide in-depth critical analysis and benchmark comparisons. Tables & Figures must be high-resolution, numbered, and cited in text (e.g., Figure 1, Table 2).

7. Conclusion

Synthesize conclusions addressing the research objectives based on experimental findings. Summarize research limitations and provide actionable recommendations for future research.

8. References

Citation Style: Strictly follow IEEE Citation Style using bracketed numeric in-text citations (e.g., [1], [2]).
Source Quality: Primary sources from journal articles/proceedings in the last 10 years.
Tools: Use Reference Managers (Mendeley, Zotero, EndNote).

Please ensure your manuscript strictly follows these guidelines prior to submission. Submissions not conforming to these standards may be returned to authors for revision before peer review.