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Pascal: Journal of Computer Science and Informatics
Published by Cv. Devi Tara Innovations
ISSN : -     EISSN : 30475074     DOI : -
Core Subject : Science, Education, Social, Engineering,
Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Library & Information Science Social Sciences
Pascal: Journal of Computer Science and Informatics is a national scientific journal that publishes research articles in the field of Computer Science and Informatics which include: Computer Engineering, Information Engineering, Computer Science, Information Systems, Information Technology, Software Engineering, Computer Systems, Computer Networks, Application of Information Technology and Other Fields of Computer Science and Informatics that have not been listed
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 44 Documents
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Development and Performance Evaluation of an IoT-Based Smart Irrigation System for Real-Time Soil Moisture Monitoring and Automatic Irrigation Siti Rubiah; Tasya Halizha Lubis; Haryoko Ichsan Prabowo; Dina Lorensa Sinaga; Sony Bahagia Sinaga
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 02 (2026): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

Manual irrigation management often results in watering practices that do not reflect actual soil moisture conditions, leading to inefficient water use and reduced crop productivity. This study aims to design and implement an Internet of Things (IoT)-based Smart Irrigation System capable of monitoring soil moisture in real time while automatically controlling the irrigation process. The research employed a Research and Development (R&D) method using a prototyping approach, including requirement identification, system design, hardware and software implementation, system integration, and performance testing. The proposed system was developed using an ESP32 microcontroller, a capacitive soil moisture sensor, a relay module, a water pump, and an internet-based monitoring dashboard. System performance was evaluated through sensor readings, real-time data monitoring, automatic pump control, response time measurement, and operational stability testing. The results demonstrate that the proposed system successfully monitors soil moisture, transmits data to the dashboard in real time, and automatically controls the irrigation pump based on predefined soil moisture thresholds. The implementation of a threshold with hysteresis mechanism improves pump stability by reducing frequent switching caused by sensor fluctuations. Furthermore, the system exhibits a relatively fast response time and stable operation throughout the testing period. These findings indicate that IoT technology provides an effective solution for developing efficient, practical, and scalable smart irrigation systems suitable for small- and medium-scale agricultural applications.
A Comparative Analysis of the Efficiency of Blockchain Consensus Algorithms: Proof of Work, Proof of Stake, Delegated Proof of Stake, and Practical Byzantine Fault Tolerance Desman Karya Jaya Zega; Laurensius So Putra Jaya Halawa; Siaman Lase; Melissa Putri Hutabarat
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 02 (2026): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

The rapid development of blockchain technology has accelerated the adoption of distributed systems across various sectors, including financial services, supply chain management, the Internet of Things (IoT), and digital government. Consensus algorithms play a fundamental role in blockchain by ensuring transaction validity and data consistency without relying on a centralized authority. Since each consensus mechanism exhibits different characteristics, a comparative analysis is required to identify its strengths and limitations. This study aims to analyze and compare the efficiency of four major blockchain consensus algorithms, namely Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), and Practical Byzantine Fault Tolerance (PBFT). The research employed a comparative literature study by collecting, selecting, and analyzing relevant scientific publications. The comparison was conducted based on transaction throughput, energy efficiency, communication complexity, transaction finality, network characteristics, and fault tolerance. The results indicate that no single consensus algorithm provides optimal performance across all evaluation parameters. PoW offers high security and decentralization but suffers from high energy consumption and low throughput. PoS provides a balanced trade-off among energy efficiency, security, and scalability, while DPoS improves transaction capacity through a delegated validator mechanism. PBFT achieves high throughput and instant transaction finality but is more suitable for permissioned blockchain environments with a limited number of participating nodes. This study proposes a comparative analysis framework that can serve as a reference for selecting an appropriate consensus algorithm based on blockchain implementation requirements.
Decision Support System for Selecting Business and Industrial Partners (DUDI) for Industrial Internship Placement Using the Simple Additive Weighting (SAW) Method at SMK Negeri 1 Barus Utara Kristian Siregar; Riswan Limbong; RL. Harmadi Tamba; Monang Juanda Tua Sihombing
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 02 (2026): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

Vocational High Schools (SMKs) play a strategic role in producing graduates who are competent, skilled, and prepared to meet the demands of the industrial workforce. One of the core programs designed to achieve this objective is the Industrial Internship Program (Praktik Kerja Industri/Prakerin), which enables students to apply the theoretical knowledge acquired in the classroom to real workplace environments. However, selecting appropriate Business and Industrial Partners (Dunia Usaha dan Dunia Industri—DUDI) remains a challenging task due to the involvement of multiple evaluation criteria, including curriculum compatibility, industrial facilities, accessibility, accommodation costs, and partner reputation. At SMK Negeri 1 Barus Utara, the selection process is still conducted manually, making it susceptible to subjectivity and inconsistency. This study proposes a Decision Support System (DSS) employing the Simple Additive Weighting (SAW) method to objectively rank potential DUDI partners based on predefined evaluation criteria and their corresponding weights. The research adopts a quantitative approach within the Multi-Criteria Decision Making (MCDM) framework. Five assessment criteria were established through interviews with internship coordinators, and five DUDI partners were evaluated as alternatives. The findings indicate that PT Sibolga Citra Komputindo achieved the highest preference score (0.7700), making it the most suitable internship partner. The implementation of the SAW method demonstrates its effectiveness in producing objective, transparent, and measurable recommendations, thereby improving the quality of internship management and supporting informed decision-making in vocational education.
Decision Support System for Permanent Lecturer Recruitment at STMIK Mulia Darma Using the Simple Additive Weighting (SAW) Method Muhammad Halmi Dar; Deci Irmayani; Elvitrianim Purba; Muhammad Sayuthi; Indra Sidabutar
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 02 (2026): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

Selecting qualified academic personnel is critical for higher education institutions to maintain academic excellence and accreditation standards. At STMIK Mulia Darma, the recruitment process for permanent lecturers historically faced challenges related to multi-criteria evaluation complexity, administrative delays, and potential subjective bias when handled manually. This study aims to develop and implement a web-based Decision Support System (DSS) utilizing the Simple Additive Weighting (SAW) method to streamline and objective candidate screening. The evaluation incorporates five key criteria: Educational Background C1, Microteaching Score C2, Publication and Research Record C3, Interview Performance C4, and Expected Salary C5. Through matrix normalization and weighted aggregation, the system calculates final preference scores to rank applicants. In empirical trials, Candidate A3 achieved the highest preference score V3 = 0.940, demonstrating the method's effectiveness in balancing academic competencies against cost parameters. System testing via Black-Box Testing yielded a 100% functional success rate, while algorithmic accuracy verification confirmed 100% alignment between automated system outputs and manual calculations. Ultimately, the developed system effectively minimizes subjective bias, enhances decision-making efficiency, and provides a reliable framework for faculty recruitment at STMIK Mulia Darma.

Page 5 of 5 | Total Record : 44

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