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All Journal Proceeding of International Conference on Global Innovation and Trends in Economy
Hendra Achmadi
Faculty of Economics and Business, Universitas Pelita Harapan, Tangerang
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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WOM and SENTIMENT Analysis Has Positive Influence to Positive or Negative Emotion from Class 11 or 12 in Jakarta and Surrounding Area Hendra Achmadi
Proceeding of International Conference on Global Innovation and Trend in Economics Vol. 4 (2022): Proceeding of The 4th International Conference on Global Innovation and Trends in Eco
Publisher : Fakultas Ekonomi Dan Bisnis Universitas Pelita Harapan

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Abstract

College selection is one of the decision-making processes in life that must be passed by high school students, the influence of WOM (Word of Mouth) and SENTIMEN Analysis originating from social media Twitter does it affect positive and negative emotions that arise when students This high school student listens to college offers from marketing. The influence of WOM in this study is from two sources, namely the influence of parents and the second is the influence of friends. Meanwhile, the SENTIMEN analysis was taken from 105 universities' social media twitter, while the emotional factor was taken from the PANAS scale. Primary data retrieval to 105 respondents from 11th and 12th grade high school students by using Google forms, while secondary data SENTIMEN analysis uses python program to 105 universities with 100 tweets so that the tweet data taken is 10500 tweets, and by using natural language processing then positive, neutral and negative sentiments can be distinguished. Then data processing using PLS-SEM. And from the results of data processing, it was found that WOM and SENTIMEN had a positive effect on positive emotion of R2 by 15.3% and negative emotion by R2 of 17.4%. SENTIMEN analysis had no effect on positive emotion and negative emotion.
Analysis of Pasar Rakyat Micro Enterprises using Business Intelligent and Data Mining in Jakarta During the Covid-19 Pandemic Hendra Achmadi
Proceeding of International Conference on Global Innovation and Trend in Economics Vol. 4 (2022): Proceeding of The 4th International Conference on Global Innovation and Trends in Eco
Publisher : Fakultas Ekonomi Dan Bisnis Universitas Pelita Harapan

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Abstract

This study aims to determine the segmentation of the seller at Pasar Jatinegara , and from the data the micro entrepreneur at Pasar Jatinegara mostly is fashion garmen and also home appliances and the rest is a food and bererage, and sales total for a month 55% is below five hundreds rupiahs and 39 % is from range five hundreds until one million a day, and its conclude the Micro Entrepreneurship and most of the seler from the interview has been there for more than 10 years, so these seller is a lower income trap, because they cannot increase skill to increase the revenue or income. As we thought that Indonesia has Go-pay and OVO and Dana, but the reality the seller haven’t have account bank, and never have loan at Bank and do not have a social media, and mostly communicate with sms and most of the seller 32 % is woman dan 68 % is man by using The Business Intelligent. In order to be clear about the segmentation among these seller, then Data mining with machine learning can do that and by using the machine learning with clustering method on the respondent's profile using k-means, in within cluster sum of squares by cluster is 76 %, and it can be seen that the respondent's profile which will increase the intention to use mobile payment is that the total sales are at most under 500 thousand, then the most education in clusters 1 and 3 is at the level of SMA is about 63 percent and the rest are elementary school graduates, and the network that is most widely used is Indosat and the number of suppliers is 1-3 and the number of customers is between 2-10 customers and the last gender is mostly male.
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