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All Journal Jurnal Teknik Sipil Cendekia (JTSC) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Sanskara Akuntansi dan Keuangan
Probokusumo, Probokusumo
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering

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Organization Performance Analysis by PM3 Maturity Level in Service Area Field Study PT. GBSI Karyadi, Karyadi; Rokhmah, Alfiya; Probokusumo, Probokusumo
Sanskara Akuntansi dan Keuangan Vol. 4 No. 01 (2025): Sanskara Akuntansi dan Keuangan (SAK)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/sak.v4i01.636

Abstract

PT. GBSI is a company that operates in the security services business (outsourcing) and serves its customers based on work contracts per certain period (project), it’s classified in Project Based Organization (PBO) category. Project Management Maturity Model (PM3) is a tool widely used to measure project management performance by looking more broadly at 10 knowledge areas in project management. This research aims to perform an analysis by PM3 maturity level in PT. GBSI. PM3 is used to measure PBO performance in the construction, IT, biotechnology sectors, and currently, it has begun used in service sector, education, and public administration, but there has been no research using PM3 in the provider of security services sector. This research tries to use qualitative approach through interview, document analysis, focus group discussion in diagnosing conditions at PT. GBSI, and use PM3 assessment analysis. The assessment results show the average maturity level achievement in all areas for project management organization is 30% from target maturity level 2. The assessment result can identify the maturity level in the organization and therefore identify development needs in 10 knowledge areas PM3, also provide alternative human processes, technostructure, and human resource interventions to cover the gap maturity level for organizational development.
KAJIAN LITERATUR KOMPARATIF EFEKTIVITAS INHIBITOR HIJAU BERBASIS EKSTRAK TANAMAN DALAM PENGENDALIAN KOROSI BAJA KARBON Murtiana Sari, Endah; Rahmat, Rahmat; Nur Laksana, Rifo; Probokusumo, Probokusumo
JURNAL TEKNIK SIPIL CENDEKIA (JTSC) Vol 7 No 1 (2026): Februari
Publisher : Departement of Civil Engineering, Universitas Winaya Mukti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51988/jtsc.v7i1.431

Abstract

Corrosion is a metal degradation process caused by chemical or electrochemical reactions between metals and their surrounding environment. This phenomenon leads to significant technical, economic, and environmental losses in various industrial sectors. The use of synthetic corrosion inhibitors that may cause environmental hazards has encouraged the development of environmentally friendly corrosion inhibitors known as green inhibitors derived from natural materials. This study aims to analyze the effectiveness of plant-based extracts as corrosion inhibitors for steel through a comparative literature review approach. The research was conducted using a systematic literature review by analyzing 30 scientific articles published between 2015 and 2024 obtained from databases such as Scopus, ScienceDirect, and Google Scholar. The analysis focused on several parameters including types of natural materials, active compounds, adsorption mechanisms, inhibition efficiency, and optimum concentration. The results show that mangosteen peel (Garcinia mangostana), papaya peel (Carica papaya), and banana peel (Musa paradisiaca) have significant potential as green corrosion inhibitors with inhibition efficiencies reaching 93–95%, 78–83%, and 65–72% respectively. Active compounds such as tannins, flavonoids, pectin, and alkaloids contribute to the formation of a protective adsorption layer on the steel surface that reduces corrosion rate. These findings indicate that natural materials have strong potential as environmentally friendly and sustainable corrosion inhibitors for future industrial applications.
Parameter Optimization of Battery Energy Storage System Considering Degradation Using Reinforcement Learning Muhammad Dzaky Ashidqi; Windasari, Silviana; Rahmat, Rahmat; Probokusumo, Probokusumo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 15 No 1: Februari 2026
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v15i1.24882

Abstract

Accurate and sustainable operation of battery energy storage systems (BESS) is critical for supporting renewable energy integration, ensuring both short-term reliability and long-term asset preservation. This study proposed a reinforcement learning (RL)-based scheduling framework designed to minimize power mismatch while mitigating degradation in lithium-ion batteries. The framework dynamically adapted to fluctuations in photovoltaic generation and residential load, enabling real-time decision-making. The performance was evaluated over a 30-day horizon using three indicators: average power mismatch, cumulative capacity loss, and system stability index (SSI). Results demonstrated that the proposed method achieved near-perfect load balance with an average mismatch of only 0.002 kW, while cumulative degradation remained limited to 0.22% and SSI was maintained at 0.96, reflecting high operational stability. The estimated daily degradation rate of 0.0073% corresponded to an annual capacity loss of approximately 2.7%, significantly lower than the 5–6% typically observed in uncontrolled cycling scenarios. Comparative analysis with simulated annealing (SA) and multi-objective genetic algorithm (MOGA) highlighted the balanced performance of the RL method. While MOGA eliminated mismatch at the expense of excessive degradation (0.60%) and simulated annealing reduced degradation but suffers from high mismatch (0.012 kW), the RL framework delivered the most balanced trade-off across all metrics. These findings confirm the potential of RL as a practical and sustainable strategy for PV–BESS integration, providing both technical resilience and extended battery lifetime.
Co-Authors Karyadi Karyadi Muhammad Dzaky Ashidqi Nur Laksana, Rifo Rahmat Rahmat Rokhmah, Alfiya Sari, Endah Murtiana Silviana Windasari