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Optimalisasi Support Vector Machine (SVM) Berbasis Particle Swarm Optimization (PSO) Pada Analisis Sentimen Terhadap Official Account Ruang Guru di Twitter Rizqi Darmawan; Indra Indra; Asep Surahmat
Jurnal Kajian Ilmiah Vol. 22 No. 2 (2022): Mei 2022
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (295.926 KB) | DOI: 10.31599/jki.v22i2.1130

Abstract

The significant increase in the number of users has caused public opinion on the Ruang Guru application to be widely spread through social media, especially Twitter. From 15,000 twitter data taken with the keyword Ruang Guru, a total of 2,358 datasets were obtained through the process of handling duplicates. In this study, sentiment analysis was carried out using the Support Vector Machine (SVM) algorithm which was optimized with Particle Swarm Optimization (PSO) then tested using the 10-Fold Cross Validation method which resulted in the highest accuracy rate of 89.20%, while the Support Vector Machine algorithm (SVM) only produces the highest accuracy rate of 88.56%. There is an increase of 0.64% with Particle Swarm Optimization optimization. Sentiment analysis results are positive, with positive results as much as 1463 data or 62.04% and 895 or 37.96% negative sentiment. From the results of this study, it is expected to be a material consideration for Ruang Guru to improve the quality of the service sector found on social media, especially Twitter.
Junior Class Preparedness Classification Faces A National Exam Using C.45 Algorithm with A Particle Swarm Optimization Approach Asep Suherman; DIDI KURNAEDI; Sofian Lusa; Rizqi Darmawan
bit-Tech Vol. 2 No. 3 (2020): Pandemik ICT
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v2i3.133

Abstract

These studies are counter to a trend of falling students' graduation rates on the national exam. This is because of the way students prepare their readiness to face national tests is inaccurate. On this study the hybrid method c4 algorithm.5 and the swarm particle optimization to produce a class readiness of students with high and accurate accuracy. This research suggests that by using hybridmethodC4.5 andParticle Swarm Optimizationgenerates accuracy as 97.13 %, Precisionas 96,58 %, andRecallas 100 %. Then implemented through a web-based prototype application using programming javascriptlanguage.
Application of the SDLC Method and Laravel Framework in Developing a Web Draft Based Company Profile Information System Surahmat, Asep; Darmawan, Rizqi
Scientific Journal of Information System Vol. 2 No. 1 (2024): Scientific Journal of Information System
Publisher : Universitas Utpadaka Swastika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70429/sjis.v2i1.101

Abstract

The development of a web-based company profile information system has become a fundamental need for organizations to increase reachability and direct customer involvement in it. In this context, structured software development methods and efficient frameworks become essential in ensuring project success. This article discusses the application of the Software Development Method (SDLC) and the Laravel Framework in developing a web-based company profile information system. The case study was conducted at CV Radar Teknologi Computer, a technology company engaged in providing software solutions. The SDLC method is used as a systematic approach to managing the entire information system development life cycle, from requirements analysis to testing and implementation. The Laravel framework was chosen to facilitate the development process by providing a strong structure and a variety of built-in features. The implementation results show the effectiveness of using SDLC and Laravel in achieving project goals in a timely manner and according to the desired specifications.
Pengaruh Media Spinning Wheel Game Terhadap Pengetahuan Tentang Kesehatan Gigi Siswa/I Madrasah Ibtidaiyah Negeri 1 Kota Bengkulu Tahun 2020 Darmawan, Rizqi
Jurnal Promosi Kesehatan Poltekkes Bengkulu Vol 3 No 1 (2023)
Publisher : Poltekkes Kemenkes Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33088/jurnalprosehatkuu.v2i1.356

Abstract

This research was conducted because there was data from the Ministry of Health (KEMENKES) in 2018 which explained that Bengkulu Province was recorded to have more than 45% of the proportion of dental and mouth problems. Data recapitulation of Bengkulu City Health Office recorded that in 2018 dental caries problems were 2,700 people, and data on Dental and Oral Health Service Activities of elementary school age children in Bengkulu City were 1,132 visits from 20 Puskesmas spread in 9 subdistricts in Bengkulu City. This study aims to determine the effect of Spinning Wheel Game media on knowledge about dental health of students of the Madrasah Ibtidaiyah Negeri 1 Bengkulu City. This study uses a Pre Experimental One Group Pre Test and Post Test Design research design. Samples amounted to 33 students Madrasah Ibtidaiyah Negeri 1 Bengkulu City, sampling using Proportional Random Sampling techniques, research analysis using the Paired Sample T-test. The results of the study were obtained the average knowledge before 3,4242 and after 9,1212. Paired Sample T-test test results obtained p value = 0,000 <0.05 which shows effect after being given health education with the Spinning Wheel game about dental health of Madrasah Ibtidaiyah Negeri 1 Bengkulu City. Spinning wheel game media can be used as a reference in providing health education about dental health in elementary school children. Keywords: Dental Health, Spinning Wheel Game, Knowledge
Analisis Sentimen Berbasis Transformer: Persepsi Publik terhadap Nusantara pada Perayaan Kemerdekaan Indonesia yang Pertama Salma, Triana Dewi; Kurniawan, Muhammad Ferdi; Darmawan, Rizqi; Basri, Amat
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3535

Abstract

The inaugural Indonesian Independence Day celebration in the new capital, Nusantara, marked a historic milestone. This study analyzes public sentiment toward this event using the IndoBERT model. Data was collected from Twitter during the celebration period and classified into positive, negative, and neutral sentiments. Three main approaches were employed: IndoBERT as a baseline, IndoBERT fine-tuned with IndoNLU data, and IndoBERT applied to TextBlob-labeled data. Results indicate that the TextBlob-IndoBERT model outperforms the others, effectively processing informal Indonesian text with high accuracy. These findings provide strategic insights for the government in understanding public perception regarding the development of Nusantara and demonstrate the potential of Transformer-based sentiment analysis for the Indonesian language. The study recommends further exploration of factors influencing sentiment and analysis on other social media platforms.
Analisis Sentimen Berbasis Transformer: Persepsi Publik terhadap Nusantara pada Perayaan Kemerdekaan Indonesia yang Pertama Salma, Triana Dewi; Kurniawan, Muhammad Ferdi; Darmawan, Rizqi; Basri, Amat
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3535

Abstract

The inaugural Indonesian Independence Day celebration in the new capital, Nusantara, marked a historic milestone. This study analyzes public sentiment toward this event using the IndoBERT model. Data was collected from Twitter during the celebration period and classified into positive, negative, and neutral sentiments. Three main approaches were employed: IndoBERT as a baseline, IndoBERT fine-tuned with IndoNLU data, and IndoBERT applied to TextBlob-labeled data. Results indicate that the TextBlob-IndoBERT model outperforms the others, effectively processing informal Indonesian text with high accuracy. These findings provide strategic insights for the government in understanding public perception regarding the development of Nusantara and demonstrate the potential of Transformer-based sentiment analysis for the Indonesian language. The study recommends further exploration of factors influencing sentiment and analysis on other social media platforms.
Optimalisasi Support Vector Machine (SVM) Berbasis Particle Swarm Optimization (PSO) Pada Analisis Sentimen Terhadap Official Account Ruang Guru Di Twitter Darmawan, Rizqi; Indra; Surahmat, Asep
Jurnal Kajian Ilmiah Vol. 22 No. 2 (2022): May 2022
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/g0dv0y21

Abstract

The significant increase in the number of users has caused public opinion on the Ruang Guru application to be widely spread through social media, especially Twitter. From 15,000 twitter data taken with the keyword Ruang Guru, a total of 2,358 datasets were obtained through the process of handling duplicates. In this study, sentiment analysis was carried out using the Support Vector Machine (SVM) algorithm which was optimized with Particle Swarm Optimization (PSO) then tested using the 10-Fold Cross Validation method which resulted in the highest accuracy rate of 89.20%, while the Support Vector Machine algorithm (SVM) only produces the highest accuracy rate of 88.56%. There is an increase of 0.64% with Particle Swarm Optimization optimization. Sentiment analysis results are positive, with positive results as much as 1463 data or 62.04% and 895 or 37.96% negative sentiment. From the results of this study, it is expected to be a material consideration for Ruang Guru to improve the quality of the service sector found on social media, especially Twitter.
PENGARUH ETIKA BERMEDIA SOSIAL TERHADAP INTERAKSI ONLINE DI SMK NEGERI 5 KOTA TANGERANG Darmawan, Rizqi; Antasari, Novira Dian
Jurnal Pengabdian Masyarakat Nasional Vol 5, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/pemanas.v5i1.33621

Abstract

Penggunaan media sosial yang tinggi di kalangan pelajar belum sepenuhnya diimbangi dengan pemahaman yang memadai mengenai etika digital. Rendahnya kesadaran terhadap etika bermedia sosial seringkali menyebabkan munculnya perilaku negatif, seperti penyebaran informasi palsu, ujaran kebencian, dan perundungan digital. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kesadaran dan pemahaman siswa mengenai pentingnya etika dalam berinteraksi di media sosial, serta mengevaluasi pengaruhnya terhadap pola interaksi online mereka. Kegiatan dilaksanakan di SMK Negeri 5 Kota Tangerang melalui pendekatan edukatif partisipatif, berupa pelatihan, diskusi kelompok, dan simulasi kasus. Siwa dan siswi kelas X dan XI terlibat sebagai peserta aktif. Evaluasi dilakukan dengan menggunakan pre-test dan post-test, observasi perilaku saat kegiatan berlangsung, serta wawancara dengan siswa dan guru. Hasil evaluasi menunjukkan adanya peningkatan pemahaman dan perubahan sikap positif terhadap penggunaan media sosial secara etis. Kegiatan ini juga berkontribusi dalam membentuk budaya digital yang bertanggung jawab di lingkungan sekolah. Program pengabdian ini efektif dalam meningkatkan kesadaran etika digital siswa dan mendorong terciptanya interaksi online yang sehat, sehingga dapat memberikan dampak sosial positif bagi komunitas sekolah secara keseluruhan.
ANALISIS CLUSTERING PERILAKU UNTUK MENENTUKAN PREFERENSI MEREK PRODUK IT PELANGGAN DI PT. XYZ Darmawan, Rizqi; Salma, Triana Dewi; Surahmat, Asep
Nusantara Hasana Journal Vol. 5 No. 2 (2025): Nusantara Hasana Journal, July 2025
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v5i2.1653

Abstract

This study discusses customer segmentation strategies based on purchasing behavior and brand preferences for information technology products at PT. XYZ. The main objective of this research is to identify customer purchasing patterns and classify them into several segments with different characteristics. The historical transaction data used includes attributes such as the brand of purchased products, purchase frequency within one year, and total transaction value. After the data cleaning and normalization process, a centroid-based clustering technique was applied to identify homogeneous groups in the database. The clustering results show three main clusters, each representing different consumer behaviors in terms of brand loyalty, price sensitivity, and spending level. The analysis indicates that customers with high transaction values tend to select specific brands and make purchases more frequently. These findings provide strategic insights for the company in designing more personalized marketing approaches, improving the effectiveness of product offerings, and strengthening relationships with customers in each segment.