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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH J-COSCIS : Journal of Computer Science Community Service JURNAL KARYA ILMIAH MULTIDISIPLIN
Ade Irwanda, Ahmad
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Library & Information Science Social Sciences Other

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Analisis Sentimen pada Ulasan Kegiatan Seminar Nasional Sistem Informasi dan Teknologi Komputer 2023 menggunakan Natural Language Processing (NLP) Turnandes, Yogo; Ade Irwanda, Ahmad; Vebby
Jurnal Karya Ilmiah Multidisiplin (JURKIM) Vol. 4 No. 2 (2024): Jurnal Karya Ilmiah Multidisiplin (Jurkim)
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/jurkim.v4i2.22063

Abstract

This research aims to analyze the sentiment of participant reviews of the National Seminar on Information Systems and Computer Technology 2023 using Natural Language Processing (NLP). With the increasing use of social media and online platforms, sentiment analysis is becoming an important tool to manage and summarize information from diverse participant opinions. This research uses an NLP model adapted to the Indonesian language to provide more contextual and in-depth insights. The research process involved review data collection, data pre-processing, tokenization, stopword removal, stemming, and sentiment analysis using the Naive Bayes algorithm. The analysis results showed that 90% of the reviews were positive, with the most appreciated aspects including the quality of the seminar materials and the availability of facilities. Meanwhile, 10% of reviews were negative, mainly related to time management and interaction with speakers. These findings provide concrete guidance for organizers to focus on improving the less satisfactory aspects. Evaluation of the effectiveness of the NLP model showed that the technique was able to identify sentiment with higher accuracy than conventional methods, reinforcing the potential of NLP as an effective tool in local language-based sentiment analysis. This research contributes to the development of sentiment analysis methodology in the context of Indonesian language, as well as providing valuable references for further research in the field of sentiment analysis.
PELATIHAN PEMBUATAN KONTEN DIGITAL MARKETING MENGGUNAKAN APLIKASI CAPCUT DALAM MENINGKATKAN KOMPETENSI SISWA SMKN 6 PEKANBARU Abiyus, Wentisasrapita; Ade Irwanda, Ahmad; Afriana Munthe, Richa; Firmansyah
J-COSCIS : Journal of Computer Science Community Service Vol. 4 No. 2 (2024): J-COSCIS : Journal of Computer Science Community Service
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/jcoscis.v4i2.19134

Abstract

Digital marketing adalah bentuk promosi yang memanfaatkan teknologi digital. Salah satu dari digital marketing adalah sebuah Video yang merupakan salah satu metode yang paling efektif untuk berkomunikasi dan memberikan informasi. Pemanfaatan salah satu aplikasi pembuatan video yang ada pada Play Store diharapkan dapat memantu siswa-siswi untuk membranding dirinya dan mempromosikan sekolahnya. Tujuan Pengabdian kepada masyarakat ini mengenalkan salah satu aplikasi dari pembuatan video yaitu CapCut sebagai ajang sarana promosi inovatif. Siswa SMKN 6 Pekanbaru merupakan salah satu kelompok Masyarakat yang berpotensi untuk mengambangkan keterampilan dibidang ini. Tim pengabdian memberikan pelatihan kepada Siswa SMKN 6 Pekanbaru tentang Pemahaman mengenai pengenalan dasar-dasar konten digital, pengenalan aplikasi CapCut, Teknik pengeditan video, kreativitas dalam pembuatan konten, praktek mengedit video menggunakan CapCut dan diskusi. Sasaran dari inisiatif Pengabdian Kepada Masyarakat tahun ini adalah peserta pelatihan Siswa SMKN 6 Pekanbaru. Siswa harus dapat menggunakan dan mengoptimalkan sarana untuk memberikan kompetensi terhadap siswa itu sendiri dan meningkatkan promosi sekolah.
OPTIMALISASI STRATEGI PENERIMAAN MAHASISWA BARU MELALUI METODE REGRESI LINEAR Juliani, Fitri; Ade Irwanda, Ahmad
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4502

Abstract

New Student Admissions (PMB) is a strategic activity that plays an important role in determining the growth, sustainability, and competitiveness of a university. Lancang Kuning University (UNILAK) as one of the private universities in Riau Province faces the challenge of maintaining the stability of the number of applicants while increasing the effectiveness of its student admission strategy. This study aims to optimize the PMB strategy by applying a simple linear regression method to predict the number of new students based on historical admission data for the last five years, namely the period 2020/2021 to 2024/2025. The data used consists of the variables of the number of applicants (X) and the number of new students accepted (Y). The analysis results show a regression model of Y=509.94+0.716X with a correlation coefficient (r) of 0.91 and a coefficient of determination (R²) of 0.83, indicating a very strong positive relationship between the two variables. This model was used to predict the number of new students for the next three years, namely 2.561 students in 2025/2026, 2.609 students in 2026/2027, and 2.666 students in 2027/2028. These results show a stable increase of around two percent per year. Thus, the application of the simple linear regression method has proven to be effective in supporting data-based planning and strategic decision-making at Lancang Kuning University.
Co-Authors Abiyus, Wentisasrapita Afriana Munthe, Richa Firmansyah Juliani, Fitri Turnandes, Yogo Vebby