Journal of Telematics and Informatics
Journal of Telematics and Informatics (e-ISSN: 2303-3703, p-ISSN: 2303-3711) is an interdisciplinary journal of original research and writing in the wide areas of telematics and informatics. The journal encompasses a variety of topics, including but not limited to: The technology of sending, receiving and storing information via telecommunication devices in conjunction with affecting control on remote objects; The integrated use of telecommunications and informatics; Global positioning system technology integrated with computers and mobile communications technology; The use of telematic systems within road vehicles, in which case the term vehicle telematics may be used; The structure, algorithms, behavior, and interactions of natural and artificial systems that store, process, access and communicate information; Develops its own conceptual and theoretical foundations and utilizes foundations developed in other fields; and The social, economic, political and cultural impacts and challenges of information technologies (advertising and the internet, alternative community networks, e-commerce, e-finance, e–governance, globalization and security, green computing, ICT for sustainable development, ICT in healthcare and education, management and policymaking, mobile and wireless communications, peer-to-peer learning, regulation of digital technologies, social networking, special user groups, the 2.0 paradigm, the WWW, etc).
The journal is a collaborative venture between Universitas Islam Sultan Agung (UNISSULA), Universitas Ahmad Dahlan (UAD) and Institute of Advanced Engineering and Science (IAES) Indonesia Section.
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Efficiency Analysis of Tanker Ship Fuel Usage by Applying Exhaust Gas Boyler and Turbo Generator Power Plant
Soemedyo Soemedyo;
Muhammad Haddin;
Agus Adhi Nugroho
Journal of Telematics and Informatics Vol 6, No 3: September 2018
Publisher : Universitas Islam Sultan Agung
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DOI: 10.12928/jti.v6i3.
Efforts to save fuel consumption on tankers is absolutely necessary because in shipping it always faces waves and currents that inhibit the speed of the ship so that the shipping time is longer. If this happens, the fuel consumption of the ship will increase and waste will occur.This study aims to analyze fuel savings on tankers as oil supply vessels to meet domestic fuel needs. Savings are carried out by utilizing the heat energy of the exhaust gas of the propulsion main engine as a steam generator in the exhaust gas boiler (EGB). The steam production process takes place when the ship is in a sailing condition where the main engine has reached the maximum rotation. Exhaust gas boilers work with 16.5 bar pressure steam used as turbo generators to replace auxiliary engines to work as electricity generators as long as ships are on the cruise. In order to ensure the condition of the steam production system remains normal at work pressure so that the turbo generator working system remains stable for that exhaust gas boiler is equipped with automatic equipment both in the filling water supply system and ignition auxiliary boiler ignition system. Thus, as long as the ship is in shipping all the electricity needs are charged to the turbo generator, so practically with the application of this system resulting in savings in fuel consumption of MFO / MDO type vessels reaching 11.2% on each cruise. Keywords: Tanker ship, exhaust gas boiler, turbo generator, fuel efficiency
Sentiment Analysis of Indonesian Figure using Support Vector Machine
Suharyo Herwasto;
Imam Much Ibnu Subroto;
Badieah Assegaf
Journal of Telematics and Informatics Vol 6, No 3: September 2018
Publisher : Universitas Islam Sultan Agung
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DOI: 10.12928/jti.v6i3.230-237
On the political year 2018 will be mutually popping reverberated figures for Indonesian presidential candidate 2019. The figures recognition process generally are now using social media, so it would appear the opinions of social media users. Opinions that appeared not only contain positive and negative polarity, but also contain a sentence of subjective and objective. By using a machine learning algorithm, namely Support Vector Machine, made sentiment analysis. The results of the analysis of this sentiment more optimally use the kernel Linear with the F-Measure of Polarity 68%, 68%, 63%, and the F-Measure Subjectivity 73%, 77%, 75% for each figure Anies Baswedan, Joko Widodo, and Prabowo Subianto.