Professional Academy Digital Talent -Data Science Program (DSQ) Review with Sentiment Analysis (Discord group discussion)
“Sentiment analysis is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. “ -Wikipedia-
The Digital Talent Scholarship (DTS) program as part of the Ministry of Communication and Informatics program and national priority programs, is the first step in optimizing the use of ICT, including in building a resilient Indonesian digital economy. Fulfilling the needs of Indonesia’s digital talents requires the active participation of universities throughout Indonesia as well as industry players, both local and global, to strengthen the DTS program. The diversity of stakeholders in the DTS program not only gives color to the curriculum offered, but also provides valuable opportunities for participants to explore as much as possible from the best in their fields.
One of the DTS 2021 programs is the Professional Academy Digital Talent Scholarship (DTS PRO), which aims to improve the capabilities of skilled workforce in the ICT field that are in accordance with Industry needs.
The DTS PRO program improves and prepares for the transfer of Indonesian HR competencies by providing online training to people working to create a more adaptive and productive Indonesian workforce. DTS PRO also aims to improve the quality of human resource competitiveness in the field of ICT. DTS PRO participants will study independently online. Participants can adjust their study time independently according to a predetermined time duration. DTS PRO program activities include Self-Paced Learning, Live Sessions / Webinars, Practice Labs, Class Groups, and Evaluation. Furthermore, at the post-training stage: Certification or Advanced Training Program and training to complete a project in a limited time.
Overall, the DTS PRO 2021 program is organized as follows:
Academy Category : Professional Academy
Training Partner : DQLab
Training Theme : Data Scientist (DSQ)
Total Participants : 1000
Access to Learning: DQLab Academy Application
Class Group : Discord Application
Data was collected at 13 April 2021
Sentiment Analysis -Discord group discussion
After almost 30 days of training with amazing mentorship program, I would like to share my objective personal opinion with sentiment analysis to review the DTS PRO 2021-DSQ program based on participants chat group section at Discord.
Sentiment analysis is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, measure and study effective states and subjective information.
Based on Dasrhboard Sentiment Analysis, I categorized the sentiment information into each group of topics:
dsq1 : R Fundamental for Data Science
dsq2 : Fundamental SQL
dsq3: Statistics using R for Data Science
dsq4: Data Visualization in Data Science Using R
dsq5: Data Science in Marketing
dsq6: Loan Analysis for UMKM Sector
The information was gathered with informal chat group class where participants discussed each other to solve the module application. There are several difficulties to obtain valid information, since the message were presented in informal pattern. It could lead into biased sentiment analysis result. According to the sentiment analysis result, overall message are categorized into Neutral (59.34 %), Positive (25.66 %) and Negative (15%). For more detailed analysis, Dashboard could filter the information based on each topic discussion.
The information also contain with full message that categorized as Positive or Negative messages which could use as feedback or suggestion from the participant. We also could analyze the rush hour which the committee of event should pay more attention with server capacity to handle a lot of participant usage and maintain the application during that hours.
Recommendation
- Since the source of data come from the informal messages activities, there are too many unnecessary words that could lead into biased Sentiment result. It represent with higher number of Neutral percentage output. The input messages should be converted into the formal context.
- Messages at Discord group chat are dominated with Question and Answer about module topic training that participant need to finish before the deadline.
- Positive sentiment are present the good education environment between participants in the group to help each other problems.
- Negative sentiment are present with the technical problem during the module training activity, where the DQLab academy web page application could not be accessed for several times. We assumed that because the over capacity of usage form the participants.
- Committee of event could use pay more attention with specific time where the load of participants are maximum. They could use this hour to maximize the capacity of server to maintain the application.
Closing Remark
At the end, I would like to express my gratitude for this amazing opportunity to learn new knowledge and skills. I do believe that this opportunity would become valuable assets for my work and my career.
This publication is produced for educational or information only, if there are any mistake in data, judgement, or methodology that I used to produce this publication.
- * Please consider to contact the writer using contact information at Profile. I would like to discuss and sharing more about the topic. Thank you.
Best Regards,
Andriyan Saputra
