JSAI Journal Repository - Open Science for Global Impact

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Optimizing Outcome-Based Education Curriculum Design Using Generative AI DeepSeek: Case Study of D3 Computer Engineering Study Program

H. A. Mooduto

22 Oct 2025

Generative AI DeepSeek Outcome-Based Education +5

Optimizing Outcome-Based Education Curriculum Design Using Generative AI DeepSeek: Case Study of D3 Computer Engineering Study Program

H. A. Mooduto

22 October 2025

Abstract

Background: The development of generative artificial intelligence (Generative AI) opens new opportunities for optimizing higher education curriculum design. DeepSeek as a generative AI offers complex analysis capabilities to develop Outcome-Based Education (OBE) curriculum integrated with the Indonesian National Qualification Framework (KKNI) and industry needs.
Objective: This study aims to develop a comprehensive model for utilizing Generative AI DeepSeek in the OBE curriculum design process for D3 Computer Engineering Study Program.
Methods: The research employs mixed-methods approach with sequential explanatory design. A structured prompt engineering framework was developed using [ROLE] + [CONTEXT] + [TASK] + [CONSTRAINTS] + [FORMAT] approach. Technical implementation followed iterative refinement process through three phases: preparation, AI implementation, and validation. Data were collected from 20 stakeholders through FGDs and validated by 5 curriculum experts.
Results: Generative AI DeepSeek successfully optimized the curriculum design process by reducing development time from 17 days to 3 days (82% efficiency improvement). The AI generated 10 learning outcomes with 95% accuracy, 5 industry-relevant graduate profiles (90% accuracy), 110-credit curriculum structure (92% accuracy), and comprehensive curriculum maps. Expert validation showed overall 92% accuracy in regulatory compliance and industry needs alignment. Chain-of-thought prompting demonstrated 94% success rate for complex tasks, while constraint-based prompting achieved 96% success for structural design.
Conclusion: The utilization of Generative AI DeepSeek with structured prompt engineering framework proves highly effective in optimizing OBE curriculum design process. This model produces comprehensive, systematic outputs that comply with national standards and industry 4.0 requirements while significantly improving efficiency and quality assurance in curriculum development.

Keywords

Generative AI DeepSeek Outcome-Based Education Curriculum Design KKNI Computer Engineering Prompt Engineering Higher Education

Perancangan dan Implementasi Sistem Portal Bimbingan Tugas Akhir

H. A. Mooduto

15 Oct 2025

Academic Information System Final Project Guidance Portal Digital Document Management +1

Perancangan dan Implementasi Sistem Portal Bimbingan Tugas Akhir

H. A. Mooduto

15 October 2025

Abstract

Abstrak
Portal Bimbingan Tugas Akhir merupakan sistem informasi berbasis web yang dirancang untuk memfasilitasi proses bimbingan tugas akhir antara mahasiswa, dosen pembimbing, dan administrator. Sistem ini mengintegrasikan manajemen pengguna, upload dokumen, review, dan komunikasi dalam satu platform terpusat menggunakan teknologi PHP, MySQL, dan Bootstrap. Hasil implementasi menunjukkan sistem mampu meningkatkan efisiensi proses bimbingan sebesar 40% dengan mengurangi waktu koordinasi dan memusatkan komunikasi. Sistem ini telah diuji dengan 100 pengguna simulasi dan menunjukkan performa yang stabil dengan response time di bawah 2 detik untuk mayoritas operasi. Keamanan sistem dijamin melalui implementasi prepared statements, password hashing, dan validasi input yang ketat.

Abstract
The Final Project Guidance Portal is a web-based information system designed to facilitate the final project guidance process among students, supervising lecturers, and administrators. The system integrates user management, document upload, review, and communication into a centralized platform using PHP, MySQL, and Bootstrap technologies. Implementation results show the system can improve the efficiency of the guidance process by 40% by reducing coordination time and centralizing communication. The system has been tested with 100 simulated users and shows stable performance with response times under 2 seconds for most operations. System security is ensured through the implementation of prepared statements, password hashing, and strict input validation.

Keywords

Academic Information System Final Project Guidance Portal Digital Document Management Web Application Security

Sistem Presensi Face Recognition: Implementasi Lengkap dengan PHP dan OpenCV Python

H. A. Mooduto

14 Oct 2025

face recognition attendance system OpenCV +2

Sistem Presensi Face Recognition: Implementasi Lengkap dengan PHP dan OpenCV Python

H. A. Mooduto

14 October 2025

Abstract

Conventional attendance systems have limitations in terms of security, efficiency, and accuracy. This research develops a digital attendance system using face recognition technology that integrates PHP for backend and OpenCV Python for face processing. The methods used include Haar Cascade for face detection and Local Binary Patterns Histograms (LBPH) for recognition. The system implements a three-layer architecture with web frontend, PHP backend, and Python AI processing. Test results show recognition accuracy of 89% with false acceptance rate (FAR) of 4.2% and false rejection rate (FRR) of 7.8%. The average processing time is 3.2 seconds per attendance. The system successfully integrates web technology with computer vision to create an accurate, efficient, and secure attendance solution.

Keywords

face recognition attendance system OpenCV LBPH web application

ANALISIS KOMPREHENSIF DNS POISONING DAN STRATEGI MITIGASI DENGAN PENDEKATAN HYBRID DNSSEC DAN DNS OVER HTTPS

H. A. Mooduto

08 Oct 2025

DNS Poisoning Cybersecurity DNSSEC +2

ANALISIS KOMPREHENSIF DNS POISONING DAN STRATEGI MITIGASI DENGAN PENDEKATAN HYBRID DNSSEC DAN DNS OVER HTTPS

H. A. Mooduto

08 October 2025

Abstract

This study aims to analyze the effectiveness of DNS Poisoning techniques and their mitigation methods in the context of increasing cyber security threats, focusing on the evaluation of DNSSEC implementation and modern encryption protocols. The research used a systematic literature review of empirical studies and recent security reports from the 2018-2023 period. The study revealed that up to 33% of tested public DNS resolver servers remain vulnerable to cache poisoning variations, contributing to more than 50% of phishing incidents. Analysis shows that 95% of successful DNS Poisoning attacks are caused by a combination of weaknesses in parameter randomization and lax configurations. The in-depth discussion confirms that although DNSSEC is a robust cryptographic solution, its adoption rate of below 25% globally remains a major inhibiting factor. This research concludes that a hybrid approach combining DNSSEC, DNS over HTTPS (DoH), and proactive traffic monitoring is the most effective defense strategy to significantly mitigate DNS Poisoning risks.

Keywords

DNS Poisoning Cybersecurity DNSSEC Cache Poisoning DNS over HTTPS

Pemanfaatan Prompt Engineering Terstruktur untuk Analisis Kerentanan dan Rekomendasi Perbaikan Kode Aplikasi Web

H. A. Mooduto

06 Oct 2025

Prompt Engineering Web Application Security Large Language Model +2

Pemanfaatan Prompt Engineering Terstruktur untuk Analisis Kerentanan dan Rekomendasi Perbaikan Kode Aplikasi Web

H. A. Mooduto

06 October 2025

Abstract

Web application security remains a critical challenge in software development. Manual security audits are time-consuming and costly, while traditional Static Application Security Testing (SAST) tools often yield false positives and negatives. The code processing capabilities of Large Language Models (LLMs) offer a potential solution, but their effectiveness is highly dependent on the quality of the prompts provided. This experimental study applied a set of structured prompt engineering techniques to analyze security vulnerabilities in open-source code samples containing known vulnerabilities. The LLM model used was GPT-4. The procedure consisted of three stages: (1) Context Initialization, (2) Multi-Layer Analysis (general code review, specific vulnerability pattern recognition, and dependency check), and (3) Remediation Recommendation Generation. The designed prompt engineering techniques successfully identified the majority of known vulnerabilities, including Cross-Site Scripting (XSS), SQL Injection (SQLi), and Insecure Deserialization. The model also generated specific and implementable code repair recommendations, such as the use of prepared statements and output sanitization functions. The results indicate that a structured prompt engineering approach can be an effective assistive tool for initial security audits, capable of reducing the analytical burden on developers. However, this approach has limitations, including the potential for false positives, an absolute dependence on prompt quality, and the model's tendency to hallucinate on highly complex code. This study underscores the need for a standardized prompt framework for cybersecurity.

Keywords

Prompt Engineering Web Application Security Large Language Model Static Code Analysis SQL Injection.

Optimasi Prompt Generative AI untuk Pengembangan Aplikasi Web Menggunakan DeepSeek

H. A. Mooduto

05 Oct 2025

Prompt Engineering Generative AI Pengembangan Web +2

Optimasi Prompt Generative AI untuk Pengembangan Aplikasi Web Menggunakan DeepSeek

H. A. Mooduto

05 October 2025

Abstract

This study aims to analyze and formulate effective prompt structures for the DeepSeek Large Language Model (LLM) to enhance efficiency and quality in web application development.
This research employs a Research and Development (R&D) approach with an experimental method. A series of common web development tasks (code generation, debugging, documentation, and architecture) were tested on DeepSeek. Each task was executed using varied prompts, including zero-shot, few-shot, and chain-of-thought prompting. Effectiveness was measured based on the functional accuracy of the code, completeness of output, and the number of iterations required for task completion. Structured and contextual prompts produced significantly superior outputs. The chain-of-thought technique proved most effective for complex tasks like architecture design and debugging, improving logic accuracy by up to 40% compared to zero-shot. Meanwhile, few-shot prompting was optimal for generating code with consistent style and standards. Providing clear project context (technology stack, API specifications, and constraints) reduced iteration needs by up to 60%. Utilizing DeepSeek Gen.AI for web development requires deliberate prompt strategies. A prompt formulation that includes the AI's role, detailed context, the expected output format, and critical thinking steps is a determining factor for success. These findings provide a practical framework for developers to leverage LLMs more productively.

Keywords

Prompt Engineering Generative AI Pengembangan Web DeepSeek Large Language Model

RANCANG BANGUN APLIKASI PENDAFTARAN ONLINE PENERIMAAN MAHASISWA BARU POLITEKNIK NEGERI PADANG JALUR SELEKSI MANDIRI

H. A. Mooduto

05 Oct 2025

Rancang Bangun Pendaftaran Online Joomla +4

RANCANG BANGUN APLIKASI PENDAFTARAN ONLINE PENERIMAAN MAHASISWA BARU POLITEKNIK NEGERI PADANG JALUR SELEKSI MANDIRI

H. A. Mooduto

05 October 2025

Abstract

Penerimaan Mahasiswa Baru (PMB) merupakan proses rutin tahunan yang vital di setiap perguruan tinggi. Di Politeknik Negeri Padang (PNP), salah satu jalur masuk adalah Jalur Seleksi Mandiri (SMPNP). Selama ini, proses pendaftaran yang manual dinilai kurang efektif, menyebabkan calon mahasiswa harus datang langsung ke kampus dan berpotensi menimbulkan antrian panjang. Penelitian ini bertujuan untuk merancang dan membangun aplikasi pendaftaran online guna mengatasi permasalahan tersebut. Metode penelitian yang digunakan meliputi studi literatur, analisis kebutuhan, perancangan sistem, dan implementasi. Aplikasi dirancang menggunakan CMS Joomla dengan komponen FacileForms untuk pembuatan formulir, PHP sebagai bahasa pemrograman, dan MySQL untuk manajemen basis data, yang berjalan pada sistem operasi server Linux CentOS. Aplikasi ini mengintegrasikan proses permintaan PIN, pembayaran biaya pendaftaran secara host-to-host dengan Bank Nagari Sumatera Barat, pengisian borang data diri dan pilihan program studi, hingga pencetakan Kartu Tanda Pendaftaran. Hasil dari penelitian ini adalah sebuah aplikasi web yang berfungsi penuh dan telah diimplementasikan pada https://pmb.pnp.ac.id. Aplikasi ini telah berhasil digunakan pada Penerimaan Mahasiswa Baru Tahun Akademik 2023/2024, yang memberikan kemudahan bagi calon mahasiswa, efisiensi bagi bagian akademik, dan akurasi pelaporan keuangan. Ke depan, pengembangan sistem berbasis mobile dan integrasi SMS Gateway untuk pengumuman kelulusan sangat disarankan.

Keywords

Rancang Bangun Pendaftaran Online Joomla FacileForms PHP MySQL CentOS.

PENGEMBANGAN APLIKASI REPOSITORY JURNAL ILMIAH BERBASIS WEB DENGAN ARSITEKTUR THREE-TIER DAN ROLE-BASED ACCESS CONTROL

H. A. Mooduto

04 Oct 2025

Journal Repository Three-Tier Architecture RBAC +2

PENGEMBANGAN APLIKASI REPOSITORY JURNAL ILMIAH BERBASIS WEB DENGAN ARSITEKTUR THREE-TIER DAN ROLE-BASED ACCESS CONTROL

H. A. Mooduto

04 October 2025

Abstract

The development of web-based scientific journal repository systems is an urgent need in supporting knowledge dissemination in the digital era. This study aims to develop a scientific journal repository application with three-tier architecture and comprehensive role-based access control (RBAC) implementation. The development method uses a Research and Development (R&D) approach with a modified waterfall model. The system was developed using native PHP, MySQL, and Bootstrap 5 technologies by implementing cybersecurity principles and optimal user experience. The research results produced a repository application consisting of: (1) responsive frontend for journal publication; (2) backend with three different roles (admin, author, reviewer); (3) integrated review system; (4) secure user management; and (5) efficient search and pagination features. Testing showed the system successfully handled all use cases with 98.7% success rate, average response time of 1.2 seconds, and zero critical vulnerabilities. This application has been implemented in production at https://jsai.parewa.my.id and proven effective in supporting digital scientific journal publication processes.

Keywords

Journal Repository Three-Tier Architecture RBAC Native PHP Web Development

Pengembangan Kurikulum Berbasis Outcome-Based Education (OBE) Program Studi D3 Teknik Komputer: Integrasi KKNI Level 5, Kebutuhan Industri 4.0, dan Pemanfaatan Generative AI

H. A. Mooduto

04 Oct 2025

OBE Curriculum Vocational Education Computer Engineering +3

Pengembangan Kurikulum Berbasis Outcome-Based Education (OBE) Program Studi D3 Teknik Komputer: Integrasi KKNI Level 5, Kebutuhan Industri 4.0, dan Pemanfaatan Generative AI

H. A. Mooduto

04 October 2025

Abstract

Developing vocational education curricula responsive to Industry 4.0 dynamics is an urgent need. This study aims to design an Outcome-Based Education (OBE)-based curriculum for the D3-Computer Engineering Study Program that integrates the Indonesian National Qualification Framework (KKNI) Level 5, digital industry needs, and institutional vision. The research method uses Research and Development (R&D) with a modified ADDIE model. Data was collected through documentation studies, curriculum benchmarking, FGDs with industry stakeholders, and design simulation assisted by Generative AI DeepSeek. The results produced a comprehensive OBE curriculum model including: (1) strengthened vision-mission formulation; (2) five Program Educational Objectives (PEO); (3) five Graduate Profiles; (4) twelve Graduate Learning Outcomes (GLO); (5) forty Course Materials; and (6) an operational curriculum structure of 110 credits with 53.6% practical composition. The curriculum integrates Industry 4.0 competencies such as Internet of Things (IoT), embedded systems, cybersecurity, cloud computing, and technopreneurship. Correlation matrix analysis shows high consistency between components with an average TPP-GP correlation coefficient of 0.82. The use of Gen AI proved effective in accelerating the analysis process by 60% and ensuring consistency of vertical integration. This curriculum model is recommended for implementation in computer engineering vocational study programs with institutional context adjustments.

Keywords

OBE Curriculum Vocational Education Computer Engineering KKNI Industry 4.0 Generative AI