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All Journal Desimal: Jurnal Matematika Innovative: Journal Of Social Science Research
Zainuddin, Mochamad
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Humanities Computer Science & IT Education Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Analisis Efektivitas Perawatan Evaporator Plate Fresh Water Generator Type Aqua 125 HW Di Kapal MV CNC Jawa Dengan Metode Fishbone Diagram Rahman, Rizki Ardika; Imanto, Frenki; Zainuddin, Mochamad; Nugroho, Aziz; Robbi, Shofa Dai
Innovative: Journal Of Social Science Research Vol. 5 No. 2 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i2.18763

Abstract

The Fresh Water Generator (FWG) is a device on ships that converts seawater into freshwater through the processes of evaporation and condensation. FWG is essential for various purposes such as consumption, washing, and engine cooling. This study aims to address three main research questions: what maintenance methods are applied to the FWG evaporator plate, how does the FWG perform before and after maintenance, and how effective is the system after the maintenance is conducted.The research was carried out on the MV CNC Jawa by analyzing the effectiveness of maintenance on the FWG Type AQUA-125-HW evaporator plate through direct observation, interviews with ship crew, and analysis of logbook data. The evaluation used a fishbone diagram to identify the factors contributing to decreased maintenance effectiveness, including human resources, maintenance methods, materials, and machinery.The results show that both preventive and corrective maintenance—such as routine cleaning and the use of Ameroyal chemical agents—successfully improved heat transfer efficiency. Freshwater production increased from 5–8 tons/day to 13 tons/day, energy consumption decreased, and FWG operation became more stable. The evaluation concludes that proper maintenance strategies and crew training are essential in ensuring the reliability of the FWG and the overall operational efficiency of the vessel.
An MSI-Transformed Multiple Linear Regression Model for Early Warning of Seafarers' Safety Compliance in a Maritime IDSS Prototype Fachrudin, Achmad Dhany; Novitasari, Novitasari; Zainuddin, Mochamad; Azhar, Fieranda Firdaus; Santoso, Agus Dwi; Basuki, Nanang
Desimal: Jurnal Matematika Vol. 9 No. 2 (2026): Desimal
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/

Abstract

This study developed an MSI-transformed multiple linear regression model to estimate seafarers’ safety compliance from fatigue and occupational stress and implemented the resulting equation in a Python-based Maritime Intelligent Decision Support System prototype. Data were collected from 49 professional seafarers using a five-point Likert questionnaire measuring fatigue, occupational stress, and safety compliance. The ordinal responses were transformed into interval-based scores through the Method of Successive Intervals and analysed using ordinary least-squares regression. The overall model was statistically significant, F(2,46)=4.139, p=0.0222, with R2=0.153. Fatigue produced a negative but non-significant coefficient (β=−0.1020, p=0.489), while occupational stress also showed a negative coefficient (β=−0.2366, p=0.092). Thus, the predictors jointly accounted for a modest proportion of compliance variation, although neither showed an independently significant association at the 5% level. The estimated equation was embedded in the prototype to generate compliance scores and assign preliminary Safe, Alert, and Critical categories. Generative AI was restricted to translating deterministic outputs into concise mitigation narratives and did not calculate scores or determine categories. The study provides a transparent and reproducible workflow integrating ordinal-score transformation, interpretable regression, and computational decision support. The resulting architecture preserves traceability, supports human oversight, and demonstrates an exploratory early-warning framework for maritime safety compliance rather than a validated predictor of accidents or individual unsafe behaviour under current operational assessment conditions.
Co-Authors AGUS DWI SANTOSO Azhar, Fieranda Firdaus Aziz Nugroho Dhany Fachrudin, Achmad Imanto, Frenki Nanang Basuki Novitasari Novitasari Rahman, Rizki Ardika Robbi, Shofa Dai