<![CDATA[Manual ship machinery surveys by technical supertenders in Indonesia cause 48-hour delays and 15% human errors, leading to higher downtime in archipelagic waters. This research aims to design a mobile application for real-time machinery condition surveys. Using Research and Development (R&D) with modified waterfall methodology and MIT App Inventor, the study targeted 15 supertenders and 5 maritime experts from Surabaya Polytechnic and MT. Pancaran Infinity tanker during 12-month sea practice. Instruments included AI2 Companion testing, Likert-scale validation, SPSS for Aiken's V (>0.8) and Cronbach's Alpha (>0.7), plus SWOT analysis. Results show the Planned Maintenance System prototype successfully records engine usage via Clock component, stores data offline with TinyDB, and delivers automatic notifications, reducing survey time by 50% and errors by 15%. In conclusion, the application enhances maintenance efficiency in limited connectivity areas, supporting national shipping sustainability.]]>
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