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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Format : Jurnal Imiah Teknik Informatika Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Bina Insani ICT Journal Informatics for Educators and Professional : Journal of Informatics JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Komtika (Komputasi dan Informatika) JSiI (Jurnal Sistem Informasi) JOURNAL INFORMATICS, SCIENCE & TECHNOLOGY INTI Nusa Mandiri JIKA (Jurnal Informatika) Jurnal Sistem Informasi Bulletin of Computer Science Research Journal of Students‘ Research in Computer Science (JSRCS) Jurnal Pengabdian Kepada Masyarakat PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Socius: Social Sciences Research Journal Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Komtika (Komputasi dan Informatika)
Henny Leidiyana
Universitas Bina Sarana Informatika
Religion Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Nursing Public Health Social Sciences Veterinary Other

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Journal : INTI Nusa Mandiri

 1 
ENSEMBLE STACKING DALAM ANALISA SENTIMEN REAKSI VETERAN MILITER AS TERHADAP PENGAMBILALIHAN AFGHANISTAN OLEH TALIBAN Henny Leidiyana
INTI Nusa Mandiri Vol 18 No 1 (2023): INTI Periode Agustus 2023
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v18i1.4175

Abstract

Abstrak— Sentiment analysis can be used to glean information about user opinions and identify social or political trends. There have been many studies on sentiment analysis using machine learning or lexicon-based methods that have been quite impressive. However, machine learning models often have difficulty generalizing to new data due to various reasons, such as overfitting and limited training data. These models are also prone to bias and variance, which negatively affect the accuracy of their predictions. This study discusses the application of the ensemble stacking method in sentiment analysis with the topic of the takeover of Afghanistan by the Taliban. By monitoring social media, the author uses a dataset in the form of comments on YouTube news channels related to the topic raised. Several studies have shown how the ensemble stacking method predicts better than the single model. The research was carried out by creating a sentiment classification model with logistic regression machine learning algorithms, SVM, KNN, and CART then the ensemble stacking classifier formed by the base learner of the four algorithms. As a result, for a single classifier, the highest average accuracy is the logistic regression algorithm of 74.6 percent. The four algorithms are compiled and predicted by logistic regression, and the stacking ensemble classifier that is applied produces better accuracy than the stand-alone classifier, which is 75.3 percent
MENGUKUR KEPUASAN MAHASISWA DALAM MENGGUNAKAN APLIKASI MUSIC STREAMING MENGGUNAKAN METODE AHP Rakhmah, Syifa Nur; Leidiyana, Henny
INTI Nusa Mandiri Vol. 19 No. 1 (2024): INTI Periode Agustus 2024
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i1.5577

Abstract

Online streaming applications are currently very popular among the public, especially students. Because of this user interest, the author wanted to conduct research. This research uses the AHP method to measure students' level of satisfaction with the use of music streaming applications. The research evaluation criteria included quality, service, price and payment. Questionnaires are used to determine student preferences and assessment of related criteria. The collected data was analyzed using the AHP method and the application priorities were compared. These findings will help developers and users improve quality and user experience. The research was conducted using the Analytical Hierarchy Process (AHP) methodology on students in the Bekasi City area with a population of 7058 people and obtained a sample size of 379 respondents using the Slovin formula. The research results show that Spotify is the most popular music streaming application among users, especially students. Followed by applications such as Joox and YouTube.
Co-Authors Agustiena Merdekawati, Agustiena Ahmad Yusuf Al Ghazali Ali Rachman, Ali Andrie Kurniawan Angga Aditya Permana Anugrah, Arya Deval Saladin Ridwan Dewi Ayu Nur Wulandari Fajar Santoso Farida Cinda R. S Simatupang Gustina, Rina Hariyanto, Risvan Dwi Hary Priantoro Imam Budiawan Iqbal Fadjarudin Luci Kanti Rahayu Meisyha, Rineke Muhammad Adil Muhammad Faisal Muhammad Ghudafa Taufiq Akbar Nandang Iriadi Nila Hardi Omar Pahlevi Purnamawati Purnamawati Rio Sudarsono Riska Aryanti Simanungkalit, Jumantho Simanungkalit, Jumantho Siti Nurajizah Syifa Nur Rakhmah, Syifa Nur Titik Misriati Waryono Yopi Handrianto, Yopi