PREDIKSI JARAK TEMPUH KAPAL MOTOR SANGIANG MENGGUNAKAN SUPERVISED MACHINE LEARNING

Afrioni Roma Rio, Berton Maruli Siahaan
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Abstract

As a maritime nation with thousands of islands and a vast sea area, sea transportation is the most effective transportation used by the people of Indonesia. A motorboat is one type of maritime transportation that is used to move people or commodities. In this article, we will discuss predicting the daily mileage of one of the motorboats, the Sangiang, which travels from Bitung to Ternate. Three independent variables, Anchor Time (minutes), Speed (knots/hour), and Sailing Time (minutes), are used in supervised machine learning techniques to estimate the daily mileage (mile). Of the various methods evaluated, the multiple regression model was found to be the most accurate at forecasting the Sangiang motorboat’s daily mileage.
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使用有监督的机器学习预测电动机的温度
作为一个拥有数千个岛屿和广阔海域的海洋国家,海上运输是印尼人民使用的最有效的交通方式。摩托艇是一种用于运送人员或货物的海上运输工具。在本文中,我们将讨论预测其中一艘从必通到特尔纳特的摩托艇Sangiang的日行驶里程。三个独立变量,锚定时间(分钟),速度(节/小时)和航行时间(分钟),用于监督机器学习技术来估计每日里程(英里)。结果表明,多元回归模型对三江汽艇日行驶里程的预测最为准确。
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ANALISA KERENTANAN WEBSITE FMIPA UNSRAT BERDASARKAN OPEN WEB APPLICATION SECURITY PROJECT TOP 10 FRAMEWORK APLIKASI PEMBELAJARAN SEJARAH PAHLAWAN INDONESIA DI WILAYAH SUMATERA (STUDI KASUS SDN 2 SUMBEREJO) SISTEM PENDUKUNG KEPUTUSAN UNTUK SELEKSI CALON PETUGAS SENSUS DI BADAN PUSAT STATISTIK KOTAMOBAGU MENGGUNAKAN TOPSIS SISTEM INFORMASI PENGGAJIAN KARYAWAN PADA TOKO BUKU DAN PERCETAKAN ABDI KARYA KABANJAHE BERBASIS WEB PREDIKSI JARAK TEMPUH KAPAL MOTOR SANGIANG MENGGUNAKAN SUPERVISED MACHINE LEARNING
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