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Erwin, Alva
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Computer Science & IT

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The Decision Support System for Product Purchasing Kafin, Kafin; Galinium, Maulahikmah; Erwin, Alva
Journal of Applied Information, Communication and Technology Vol. 2 No. 1 (2015)
Publisher : Swiss German University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33555/ejaict.v2i1.86

Abstract

In the development of the technology, the variety of notebook has become diverse. It can be differed by its rice, model, type, and functionality, such as weight, screen size, processor, hard disk, memory (RAM), and graphic card. All of that diversity has become the consideration by the one who looking for a notebook. There has a problem where the buyer is so confused in deciding which notebook that is suitable with their needs. Decision support system is considered as one of the solutions to handle that kind of problem. Fuzzy Tahani Algorithm that uses the relative and qualitative natural language as the user input criteria is believed to be able to help the notebook buyer in making the decision. The result is shown that the decision support system for purchasing multi criteria product such as notebook, based on the user input criteria with the Fuzzy Tahani algorithm, is able to help the user to get the alternative product that can be recommended to them.
Study About The Usage of Twitter and The Relationship with TV Show in Indonesia Badjened, Noura Hassan; Erwin, Alva; Eng, Kho I
Journal of Applied Information, Communication and Technology Vol. 3 No. 1 (2016)
Publisher : Swiss German University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The uses of social media every year has been explodes due to more new social media have invented, including their new function. Twitter has become a well-known social media, as it allow user to share short text message called tweets that can be contain of text or URL, twitter can be used as broadcasting media since every user can create about any topics they desire. And some topics contain TV program conversation, realizing this huge opportunity. Many TV station have the official Twitter account to reach their viewers by giving information and creating Hastag to group up the conversation. So the TV station can get indirectly feedback.
Study of Automotive Brands Popularity in Indonesia Using Twitter Data Efendi, Stevent; Erwin, Alva; Eng, Kho I
Journal of Applied Information, Communication and Technology Vol. 3 No. 1 (2016)
Publisher : Swiss German University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33555/ejaict.v3i1.91

Abstract

Social media has been a widespread phenomenon in the recent years. People shared a lot of thought in social media, and these data posted on the internet could be used for study and researches. As one of the fastest growing social network, Twitter is a particularly popular social media to be studied because it allows researchers to access their data. This research will look the correlation between Twitter chatter of a brand and the sales of brands in Indonesia. Factors such as sentiment and tweet rate are expected to be able to predict the popularity of a brand. Being one of the biggest industries in Indonesia, automotive industry is an interesting subject to study. A wide range of people buys vehicles, and even gather as communities based on their car or motorcycle brand preference. The Twitter results of sentiment analysis and tweet rate will be compared with real world sales results published by GAIKINDO and AISI.
Developing a Scalable and Accurate Job Recommendation System with Distributed Cluster System using Machine Learning Algorithm Dicky, Timothy; Erwin, Alva; Ipung, Heru Purnomo
Journal of Applied Information, Communication and Technology Vol. 7 No. 2 (2020)
Publisher : Swiss German University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33555/jaict.v7i2.108

Abstract

The purpose of this research is to develop a job recommender system based on the Hadoop MapReduce framework to achieve scalability of the system when it processes big data. Also, a machine learning algorithm is implemented inside the job recommender to produce an accurate job recommendation. The project begins by collecting sample data to build an accurate job recommender system with a centralized program architecture. Then a job recommender with a distributed system program architecture is implemented using Hadoop MapReduce which then deployed to a Hadoop cluster. After the implementation, both systems are tested using a large number of applicants and job data, with the time required for the program to compute the data is recorded to be analyzed. Based on the experiments, we conclude that the recommender produces the most accurate result when the cosine similarity measure is used inside the algorithm. Also, the centralized job recommender system is able to process the data faster compared to the distributed cluster job recommender system. But as the size of the data grows, the centralized system eventually will lack the capacity to process the data, while the distributed cluster job recommender is able to scale according to the size of the data.
Development of API Middleware and Mobile Application for a Job marketplace by Using RESTful API and Mobile Development Framework Wahyudi, Evan Tirta; Erwin, Alva; Lim, Charles
Journal of Applied Information, Communication and Technology Vol. 7 No. 2 (2020)
Publisher : Swiss German University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33555/jaict.v7i2.110

Abstract

The research is conducted based on the nationwide goals of Indonesia proposed in the Nawacita document, where one of the big goals is to improve the human resource greatly. Providing a good medium such as a job marketplace can be part of improving the human resource. Since most of Indonesian citizen nowadays has easy access to internet, which can ease their way of using a job marketplace application. Creating a job marketplace application may minimize a number of unemployment in Indonesia. Addition to that, through a focus group discussion, it has been discovered that respondents find job marketplace such as JobStreet and Indeed jobs does not satisfy respondents’ UI and UX view towards the application. The objective of this research is to create a job marketplace mobile application that is useful and easy to use for users. The prototype mobile application is developed using react native, and a middleware that is developed using Express JS is made alongside to bridge data to the mobile application. To assess the prototype mobile application, two evaluation method is used which is User Experience Questionnaire (UEQ) and Questionnaire User Interface Satisfaction (QUIS). 6 respondents were allowed to examine prototype application, and answer the questionnaire. The result of the evaluation both shows positive results from both questionnaires.
Co-Authors Badjened, Noura Hassan Dicky, Timothy Efendi, Stevent I Eng, Kho Ipung, Heru Purnomo Kafin, Kafin Lim, Charles Maulahikmah Galinium Wahyudi, Evan Tirta