Nowadays, machine translation has an important role in general communication. The need for machine translation system is higher in this era, resolving culture and nation boundary. Finding appropriate and optimal translation is not an easy task in language processing. Several machine translation systems already exist, but the quality of the translation is needed to be improved further. This paper discusses machine translation researches that involve Indonesian language to the other languages by systematic literature review. This paper exposes different approaches and tools for machine translation. The approaches also use various evaluation methods to measure performance. Moreover, this paper proposes several future works to improve the machine translation quality of Indonesian to other languages. The review results show that the attentionbased approach is being increasingly used to improve the performance of neural machine translation. The translation performance quality depends on the number of the corpus, well-behaved aligned corpus, and the technique used.
Nowadays, machine translation has important role in general communication. The need for machine translation system is higher in this era, resolving culture and nation boundary. Finding correct and optimal translation is not an easy task in language processing. Several machine translation system already exists, but the quality of the translation needed to be improved further. This paper discusses machine translation researches that involve Indonesian language to the other languages by systematic literature review. This paper exposes different approaches and tools for machine translation. The approaches also use various evaluation methods to measure the performance. Moreover, this paper proposes several future works to improve the machine translation quality of Indonesian to the other languages. The review results show that the attention-based approach is being increasingly used to improve the performance of neural machine translation. The translation performance quality depends on the number of the corpus, well-behaved aligned corpus, and the technique used.
In foreign exchange money trading, historical data are publicly available continuously. This historical data such as opening, highest, lowest, and closing rate are important variable to predict the future of rates movement. The available data is not only historical trading itself, but also from news release and expert analysis from expert trader. This kind of data contains text and number. This paper proposes in forecasting the rates by combining text and number data. The combination of text mining technique with several time series method i.e: simple moving average, weighted moving average and exponential moving average. Research period for this experiment is between 1st December 2018 and 31st January 2019. The currency pair are EUR – USD, USD-JPY and EUR – JPY. Forecasting results with some time series method were compared with combined time series forecasting method and naïve bayes classifier. The experiment results show that combined time series method with naïve bayes classifier delivered better accuracy level.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.