{
    "success": true,
    "data": {
        "id": 1806257,
        "msgid": "unm-data-science-graduates-research-published-in-q1-international-ai-journal-1781610782",
        "date": "2026-06-16 17:33:00",
        "title": "UNM Data Science Graduate's Research Published in Q1 International AI Journal",
        "author": "Dwi Murdaningsih",
        "source": "REPUBLIKA",
        "tags": "",
        "topic": "Technology",
        "summary": "A graduate of Universitas Nusa Mandiri's Data Science programme has successfully published her final project research in a prestigious Q1 international journal on artificial intelligence. The study, which fine-tuned the IndoBERTa model for Indonesian digital news sentiment classification, achieved up to 98 percent accuracy. The achievement highlights the university's success in integrating academic learning, industry experience, and real-world research to produce globally competitive digital talent.",
        "content": "<p>Universitas Nusa Mandiri (UNM), a Digital Business Campus, has again\nachieved international recognition. This time, the proud accomplishment\ncomes from its Data Science Study Programme, following the success of\none of its graduates, Desi Masdin Dama, who published her final project\nresearch in the reputable Q1 international journal Artificial\nIntelligence and Applications. The scientific article, titled\n\u2018Fine-Tuning IndoBERTa for Indonesian Digital News Sentiment\nClassification\u2019, serves as evidence that student academic work does not\nmerely fulfil graduation requirements but can also make a tangible\ncontribution to the advancement of science and technology on a global\nscale. This publication simultaneously demonstrates the quality of\neducation and research continuously developed by Universitas Nusa\nMandiri in producing competitive digital talent ready to face the\nchallenges of the artificial intelligence (AI) era. Desi\u2019s research\nfocused on developing an IndoBERTa-based AI model to improve the\naccuracy of sentiment classification in Indonesian-language digital\nnews. The research arose from the need for a sentiment analysis model\nmore relevant to the characteristics of news language, which tends to be\nformal and complex, differing from the social media data widely used in\nsimilar studies. Together with a research team, Desi collected and\nannotated approximately 1,300 national news articles, then fine-tuned\nthe IndoBERTa model. The result was a model capable of achieving an\naccuracy rate of up to 98 percent, whilst overcoming the adaptation gap\nbetween social media data and digital news data. This success was also\nsupported by experience gained through the Internship Experience Program\n(IEP), a flagship programme of Universitas Nusa Mandiri with a scheme of\nthree years of study and one year of industry internship. During the\nprogramme, Desi interned as a Data Analyst for Business Development\nService at PT Sadhana Ekapraya Amitra. This industry experience\nstrengthened her data analysis capabilities, problem-solving skills, and\nunderstanding of data utilisation in business decision-making, which\nlater became important provisions for completing her research. \u2018The\ninternship programme provided real experience in processing and\nanalysing data to solve problems in the industrial world. That\nexperience greatly helped me when conducting research and developing\nartificial intelligence-based solutions,\u2019 said Desi. She added that\npublishing in a Q1 international journal was an invaluable experience in\nhoning research skills whilst broadening academic horizons at a global\nlevel. \u2018This research taught me that artificial intelligence technology\nmust be built based on real needs. We sought to present a solution that\ncan help understand public sentiment through digital news more\naccurately,\u2019 Desi stated. Interestingly, the research results did not\nstop at scientific publication. The developed model has been implemented\ninto a real-time news analysis system that has the potential to support\nthe development of Natural Language Processing (NLP) research in\nIndonesia. The Head of the Data Science Study Programme at Universitas\nNusa Mandiri, Tati Mardiana, appreciated the achievement as tangible\nproof of the success of a curriculum that integrates academic learning,\nindustry experience, and needs-based research. \u2018The publication of a\nfinal project in a Q1 journal shows that our Data Science students are\nnot only capable of completing their academic studies but also of\nproducing quality scientific work that makes a real contribution to the\nadvancement of science and technology. This also proves the\neffectiveness of the Internship Experience Program in preparing students\nto face global challenges,\u2019 said Tati in a press release received on\nTuesday (16\/6\/2026). According to Tati, through a learning scheme that\ncombines academic and industry experience, students are able to connect\ntheory with real practice, thereby producing relevant and impactful\ninnovations. \u2018As a Digital Business Campus, UNM remains committed to\nproviding a learning ecosystem that encourages the birth of superior,\ninnovative, and internationally competitive digital talent. Desi Masdin\nDama\u2019s achievement is proof that the integration of education, industry\nexperience, and research can produce graduates ready to bring\nIndonesia\u2019s work to compete on the world stage,\u2019 she said.<\/p>",
        "url": "https:\/\/jawawa.id\/newsitem\/unm-data-science-graduates-research-published-in-q1-international-ai-journal-1781610782",
        "image": ""
    },
    "sponsor": "Okusi Associates",
    "sponsor_url": "https:\/\/okusiassociates.com"
}