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Journal : EMITTER International Journal of Engineering Technology

Unsupervised Twitter Sentiment Analysis on The Revision of Indonesian Code Law and the Anti-Corruption Law using Combination Method of Lexicon Based and Agglomerative Hierarchical Clustering Nur Restu Prayoga; Tresna Maulana Fahrudin; Made Kamisutara; Angga Rahagiyanto; Tahegga Primananda Alfath; Latipah; Slamet Winardi; Kunto Eko Susilo
EMITTER International Journal of Engineering Technology Vol 8 No 1 (2020)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v8i1.477

Abstract

The rejection on ratification of the revision of Indonesian Code Law or known as RKUHP and Corruption Law raises several opinions from various perspectives in social media. Twitter as one of many platforms affected, has more than 19.5 million users in Indonesia. Twitter is one of many social media in Indonesia where people can share their views, arguments, information, and opinions from all points of view. Since Twitter has a great diversity of users, it needs a system which is designed to determine the opinion tendency towards the problems or objects. The purpose of this study is to analyze the sentiment of Twitter users' tweets to reject the revision of the Law whether they have positive or negative sentiments using the Agglomerative Hierarchical Clustering method. The data that being used in this study were obtained from the results of crawling tweets based on hashtag (#) (#ReformasiDikorupsi). The next stage is pre-processing which consists of case folding, tokenizing, cleansing, sanitizing, and stemming. The extraction features Lexicon Based and Term Frequency (TF) which performs the process automatically. In the clustering stage, two clusters use three approaches; single linkage, complete linkage and average linkage. In the accuracy calculation phase, the writer uses the error ratio, confusion matrix, and silhouette coefficient. Therefore, the results are quite good. From 2408 tweets, the highest accuracy results are 61.6%.
Co-Authors Ach. Desmantri Rahmanto Achmad Zakki Falani Achmad Zakki Falani Adi Prawito Agus Sukoco Agus Sukoco Agus Sukoco Ahmadi, Burhanuddin Alamsah Alamsah Anas Turmudzi Angga Rahagiyanto Arasy Alimudin Ardhya Pandu Pratama Arimbawa, I Gede Ario Baskoro Artaya, Putu Arvianto, Dodik Awalludiyah Ambarwati Baktiono, Agus Cahyono, Adi Dwi Cholilul Chayati Delinda Dyta Puspitasari Deviyanti, IGA Sri Dwi Suhartini Dwi Suprapti Dwi Syahru Romadhon, Pradipta Eltyasar Putrajati Noman Eman Setiawan1 Fahrudin, Tresna Maulana Firdausy, Aldo Reynaldin Galuh Wahyudainto, Dimas Hopid, Hopid I Gede Arimbawa I Gede Arimbawa I Gede Arimbawa I Putu Artaya I.G.A Sri Deviyanti IGA Sri Deviyanti IGA. Sri Deviyanti Imam Safii Kunto Eko Susilo Latipah Latipah Latipah M. Ikhsan Setiawan M. Taufiqur Rohman Mariani Widia Putri Mochammad Rizaldy Much. afif masykur mughni Muchayan, Achmad Muhammad Hanif Muhammad Mustajib Muhammad Roesli Nur Restu Prayoga Pamudji, Prasanti Oktaviana Pranata, Adityya Eka Prastiwi Prastiwi Purworusmiardi, Tubagus Putra, Bhisma Fajar Kusuma Putu Artaya Ratoebandjoe, Winda Helenea Riyandi, Tyo Rysda Putra Ambariawan Sam Vicarya Widagdo Sengguruh Nilowardono Setiawan, Eman Setiawan, Muhammad Ikhsan Shobirin, Achmed Slamet Winardi Sri Wiwoho Mudjanarko, Sri Wiwoho Sulistyani Eka Lestari Tahegga Primananda Alfath Thoyibah, Nurut Tresna Maulana Faahrudin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Tubagus Purworusmiardi Tubagus Purworusmiardi Wiwik Handayani Wiwin Agus Kristiana Yuningsih Yuningsih