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All Journal Jurnal Algoritma Jurnal PkM MIFTEK Jurnal Algoritma
Khaerunisa, Nisrina
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Humanities Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Social Sciences Other

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Analisis Sentimen Pengguna Twitter dalam Pemilihan Presiden (PILPRES) 2024 dengan Menggunakan Algoritma K-Means Amin, Abdusy Syakur; Kurniadi, Dede; Nurzaman, Muhammad Zein; Nurfadillah, Rifa Sri; Khoerunisa, Sarah; Khaerunisa, Nisrina; Ajiz, Rafi Nurkholiq; Jembar, Tegar Hanafi; Faisal, Ridwan Nur
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1596

Abstract

One form of upholding democracy carried out by the Unitary State of the Republic of Indonesia is through holding presidential elections or often known as presidential elections. which is held every five years to elect the next President. Apart from that, in this digital era, people are increasingly actively using social media to convey their views, opinions and sentiments regarding the presidential election. Ahead of the 2024 presidential election, many groups such as political parties, success teams, buzzers and supporters are using social media as a campaign medium to increase the popularity and electability of their prospective candidates. One of the social media that is widely used in political party promotion media is Twitter. Which is used by people to post various comments that can be positive or negative regarding the election. Sometimes, people also express hoax opinions before or during the election. Considering that comments on Twitter are currently difficult to categorize as positive or negative, sentiment analysis is needed to understand public attitudes towards the presidential election. This research aims to evaluate text documents and determine whether the documents have a positive or negative sentiment orientation. Apart from that, the method used is K-Means to cluster the data. The results of this weighting are in the form of positive and negative sentiment. Data taken from Twitter regarding the 2024 presidential election (pilpres) totaling 1015 tweet data.
Analisis Sentimen Pengguna Twitter dalam Pemilihan Presiden (PILPRES) 2024 dengan Menggunakan Algoritma K-Means Amin, Abdusy Syakur; Kurniadi, Dede; Nurzaman, Muhammad Zein; Nurfadillah, Rifa Sri; Khoerunisa, Sarah; Khaerunisa, Nisrina; Ajiz, Rafi Nurkholiq; Jembar, Tegar Hanafi; Faisal, Ridwan Nur
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1596

Abstract

One form of upholding democracy carried out by the Unitary State of the Republic of Indonesia is through holding presidential elections or often known as presidential elections. which is held every five years to elect the next President. Apart from that, in this digital era, people are increasingly actively using social media to convey their views, opinions and sentiments regarding the presidential election. Ahead of the 2024 presidential election, many groups such as political parties, success teams, buzzers and supporters are using social media as a campaign medium to increase the popularity and electability of their prospective candidates. One of the social media that is widely used in political party promotion media is Twitter. Which is used by people to post various comments that can be positive or negative regarding the election. Sometimes, people also express hoax opinions before or during the election. Considering that comments on Twitter are currently difficult to categorize as positive or negative, sentiment analysis is needed to understand public attitudes towards the presidential election. This research aims to evaluate text documents and determine whether the documents have a positive or negative sentiment orientation. Apart from that, the method used is K-Means to cluster the data. The results of this weighting are in the form of positive and negative sentiment. Data taken from Twitter regarding the 2024 presidential election (pilpres) totaling 1015 tweet data.
Pemberdayaan Masyarakat Dalam Bidang Linkungan, Ekonomi dan Kelembagaan Permana, Sulwan; Hadi, Muhamad Rizal Nurul; Suparman, Tegar Radiansyah; Sulastri, Dewi; Khaerunisa, Nisrina; Maulina, Wina Senja; Purnama, Alpin; Maulana, Mochamad Dilla; Giandhani, Mochammad Rizky; Nurahman, Zamzam; Munawar, Arby Muhyi; Firdausa, Muhamad Arga; Firzatullah, Belva Prana; Mubarok, Abil Miftahul; Maelani, Rega; Sukma, Ersa Hermalia; Aminah, Siti Nur; Fardiansyah, Bagas; Hilmayanti, Hilmayanti; Zaman, Muhammad Badru
Jurnal PkM MIFTEK Vol 4 No 1 (2023): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.4-1.1320

Abstract

At this time there are many problems faced by the community, especially in facing challenges in life in the future. Recent issues that are often faced regarding digitalization, environment, economy and institutions. The purpose of this KKN-Thematic is to empower the community in Wanamekar Village, Wanaraja District, especially hamlet 2 and hamlet 3 according to the field of cultivation. Digitalization is currently being driven by the government so that people are literate about the benefits and understand technology now, as was done by the Garut Institute of Technology KKN-Thematic participants in Wanamekar Village, Wanaraja District. The main problems in digital literacy start from people often misusing technology, difficult business development, ethics in social media. Apart from that, the issue of recognizing the environment by making biopore wells, socialization on making eco enzyme about processing organic waste into soap, applying visual displays about prohibitions and warnings, giving directions about online business for MSME business actors in Wanamekar Village, especially in hamlet 2 and hamlet 3. And National Computer-Based Assessment of elementary school students.
Co-Authors Abdusy Syakur Amin Ajiz, Rafi Nurkholiq Aminah, Siti Nur Dede Kurniadi Faisal, Ridwan Nur Fardiansyah, Bagas Firdausa, Muhamad Arga Firzatullah, Belva Prana Giandhani, Mochammad Rizky Hadi, Muhamad Rizal Nurul Hilmayanti, Hilmayanti Jembar, Tegar Hanafi Khoerunisa, Sarah Maelani, Rega Maulana, Mochamad Dilla Maulina, Wina Senja Mubarok, Abil Miftahul Munawar, Arby Muhyi Nurahman, Zamzam Nurfadillah, Rifa Sri Nurzaman, Muhammad Zein Purnama, Alpin Sukma, Ersa Hermalia Sulastri, Dewi Sulwan Permana Suparman, Tegar Radiansyah Zaman, Muhammad Badru