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All Journal Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT) Jurnal Sisfotek Global
Dody Dody
Institut Teknologi PLN
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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Web-Based Knowledge Management System Application to Improve Employee Activities Dody Dody; Nasril Sany; Pritasari Palupiningsih; Firmansyah Apryadhi
JURNAL SISFOTEK GLOBAL Vol 13, No 1 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i1.2756

Abstract

The need for information is very high in the current 4.0 era, every organization needs fast, accurate and detailed information. Currently there is documentation at the Indonesian Medical Council Secretariat regarding knowledge on how to handle employee problems which can help the employee's own performance so that it has an impact on secretariat activities that feel ineffective. Based on the results of the analysis that has been carried out, there is a lot of important knowledge at the Indonesian Medical Council Secretariat whose function is to support activities in Health Institutions. The methodology used in this research is to use Beccera Fernandez which was developed by Beccera and Sabherwal. The data collection methods used were observation, interviews, literature study, while the Knowledge Management System implementation used the Knowledge Management Process, and the KMS design used the Unified Modeling Language (UML) modeling. The programming languages used in building the system are PHP and MySQL. The concept of knowledge sharing among employees was applied as a result of a study conducted at the Indonesian Medical Council Secretariat. This is implemented on the website so that individual employee knowledge is not simply lost.
Simulation-Based Parameter Optimization Using Genetic Algorithm for Microalgae Bioethanol Production Samsurizal Samsurizal; Septianissa Azzahra; Kartika Tresya Mauriraya; Dody Dody; Yulisya Zuriatni; Istianto Budhi Rahardja
Journal of Electrical, Electronic, Information, and Communication Technology Vol 7, No 2 (2025): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.7.2.108704

Abstract

Bioethanol is a promising renewable energy source, and microalgae such as Chlorella vulgaris and Spirulina platensis offer high productivity potential. This work applies a Genetic Algorithm (GA) to optimize key environmental parameters—pH, light intensity, and temperature—within a simulation framework over a 100-day cultivation period. GA optimization resulted in a 25% increase in total ethanol yield, from baseline values of 51.00 to 63.66 g/L for Chlorella and 32.64 to 40.79 g/L for Spirulina. We benchmarked GA against Particle Swarm Optimization (PSO), Differential Evolution (DE), and Simulated Annealing (SA); GA consistently delivered superior convergence and final yields. The model incorporates phase‑dependent carbohydrate accumulation and realistic environmental disturbances, though biological complexities such as photoinhibition and nutrient limitations are acknowledged as future work. To enable meaningful convergence, the growth model was extended with mild photoinhibition and nutrient limitation terms, ensuring a more realistic fitness landscape. Findings support the viability of metaheuristic optimization in microalgae biofuel systems and indicate potential for intelligent control integration in photobioreactor operations.
Co-Authors Firmansyah Apryadhi Istianto Budhi Rahardja Kartika Tresya Mauriraya Nasril Sany Palupiningsih, Pritasari Samsurizal Samsurizal Septianissa Azzahra Yulisya Zuriatni