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Journal : Jurnal Teknik Informatika (JUTIF)

SENTIMENT ANALYSIS AND ENTITY DETECTION ON NEWS HEADLINES TO SUPPORT INVESTMENT DECISIONS Adhi, Ajar Parama; Umuri, Khairil; Triyono, Gandung
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.3434

Abstract

Accurate investment decisions are often influenced by information available in the media. News headlines, as part of information media, can provide an initial picture of market sentiment and ongoing trends. This research examines the importance of making appropriate investment decisions with a focus on sentiment analysis and entity detection in news headlines as supporting tools. Through machine learning-based sentiment analysis and Named Entity Recognition (NER) techniques, this study identifies opinions and entities such as company names, stock indices, and industry sectors in news headlines. This research compares three machine learning algorithms, namely SVM, Naive Bayes, and Random Forest using cross-validation. The result shows that the best algorithm is SVM with weighted average F1-score of 76,68%. Furthermore, hyperparameter optimization is performed using Optuna for the SVM algorithm, which is an innovation in the context of sentiment analysis on news headlines in Indonesia. The result shows an increase in weighted average F1-score to 78,14%. For NER, a rule-based method is used by utilizing the Jaro-Winkler string similarity function. The combination of sentiment analysis and NER is then presented in the form of a dashboard using Google Looker Studio tools, with data from sentiment analysis and NER results being processed periodically and automatically using Google Workflows. This research makes a significant contribution by expanding the scope of analysis from just one or a few issuers to all entities published on news portals thanks to NER support, making the results relevant to support investment decisions that are responsive to dynamic market changes.
Co-Authors A Sakir, A Sakir Abd Jamal, Abd Adhi, Ajar Parama Afandi ZT, Fitrah Al Amiri, Dhiauddin Al Ghifary, Ahmad Kamal Amri Amri Amri Amri, Khoirul Anzira, Raudhatul Auliani, Auliani Azharsyah Ibrahim Bin Ahmad, Aiyub Darwanis Darwanis Dewi Suryani DM, Burhanis Sulthan Eddy Gunawan, Eddy Edy Miswar, Edy Fadhil, Rahmat Faisal Faisal Fajri, Muhammad Iqbal Farid Farid Farid, Farid Farma, Junia Fatiya, Ina Fauzah, Nurmela Fitrah Khairi Fonna, Rizki Putri Nurita Fuad, Zaki Ginting, Ledy Mahara Halim, Hendra Hamdani, Ahmad Haris Riyaldi, Muhammad Hasnanti Putri, Windi Hawa, Aqlima Putri Humaira, Radhia Ihsan, Mhd Ikhsan Ilka Sandela Irawati, Wirdah Jalaluddin Jalaluddin Kamal, Fakhri Kanchawongpaisan, Sipnarog Kesuma, T. Meldi Klongrua, Silanee Kusuma, Teuku Meldi Lubis, Hana Salsabila M. Shabri Abd. Majid Makfirah, Fajar Maulina, Putri Muftahuddin Muftahuddin, Muftahuddin Muhammad Haris Riyaldi, Muhammad Haris Muhammad Syahrizal, Teuku Muharman Lubis Mukhlis Mukhlis Mukhlis Yunus Muliadi, Muhammad Yani Mulyadi Adam, Mulyadi Munadia, Milda Nabawi, Rifky Chalik Nabila, Nisa Nabilah Nabilah Najla Najla, Najla Nirlina, Eka Nisva, Raisa Ullya Nizam, Ahmad Nurlina, Eka Nurma Sari, Nurma Othman, Razali Bin Pratama, Agus Putri Mentari, Putri Raihana, Rana Ramida, Ramida Ramli, Fahmi Irwan Rani, Dzacky Muharram Rashid, Muhammad Hafiz Abd. Ridhwana, Zaidan Shadiq Ridwan Nurdin Sakir, A Salpina, Parjah Saputra, Irwan Sari, Meutia Dwi Novita Sartiyah Sartiyah Sartiyah, Sartiyah Sentosa, Dewi Suryani Sharmila Silvia, Vivi Siregar, Fachrul A Siregar, M. Ridha Siregar, Muhammad Rendhie Sitepu, Novi Indriyani Srinita, Srinita Susanna Syahriyal Syahriyal, Syahriyal Syahrizal, Teuku Muhammad Syakila, Nadia Talbani Farlian Taufiq Carnegie Dawood Teuku Meldi Kesuma, Teuku Meldi Triyono, Gandung Wirda, Nurul Zikran, Ghrina ZT, Fitrah Afandi Zuhri, Al