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All Journal Prosiding Seminar Nasional Ilmu Teknik EdLib Journal (Education and Library Journal)
Elin Tamaya
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Library & Information Science Other

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Analisis Sentimen Publik Terhadap Kebijakan Efisiensi Anggaran Menggunakan Naive Bayes, dan SVM Elin Tamaya; Sharipuddin Sharipuddin; Nurhadi Nurhadi
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.170

Abstract

Budget efficiency is an important issue in state financial management because it is directly related to government spending priorities and their impact on public service programs. Discussions about budget efficiency policies are widespread on social media platform X, generating diverse public responses, thus necessitating an automated approach to understand public opinion trends more quickly and objectively. This research aims to analyze the sentiment of Indonesian people toward budget efficiency policies and compare the performance of the Naïve Bayes and Support Vector Machine (SVM) algorithms in classifying sentiment. The research data used 10,909 Indonesian-language tweets sourced from a public dataset, which were then processed thru the preprocessing stages including cleaning, case folding, normalization, tokenization, stopword removal, and stemming. Sentiment labeling is performed automatically using the Indonesian Sentiment Lexicon (InSet) approach to categorize data into positive, negative, and neutral sentiments. Feature extraction was performed using Term Frequency–Inverse Document Frequency (TF-IDF), and then the data was divided into training and testing sets with an 80:20 ratio. Model performance evaluation was conducted using a confusion matrix and the metrics of accuracy, precision, recall, and F1-score. The research results show that sentiment distribution is dominated by negative sentiment at 56.78%, followed by positive sentiment at 37.40%, and neutral sentiment at 5.83%. In the classification stage, SVM performed best with an accuracy of 86%, while Naïve Bayes achieved an accuracy of 74%. These findings indicate that SVM is more optimal for sentiment classification on social media text data and can be utilized to more effectively support the analysis of public response to budget efficiency policies.
Transformasi Digital Manajemen Kinerja Pustakawan Berbasis Digital Performance Hub Di Perguruan Tinggi Andri Mardianto; Elin Tamaya; Pratiwi Devitasari; R. M. Syahrial
Education Library Vol. 3 No. 2 (2026): Education and Library Journal
Publisher : UPT Perpustakaan Universitas Jambi

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Abstract

Performance management for librarians in higher education institutions mustcontinuously adapt to evolving regulatory frameworks and institutionalaccountability demands. Based on an initial needs assessment conducted througha problem identification questionnaire involving 12 respondents, several areasrequiring improvement were identified. These include disparities in understandingthe formulation of Employee Performance Targets (Sasaran Kinerja Pegawai/SKP),clarity of work directives, and the absence of standardized procedures fordocumenting work evidence. This study seeks to optimize performance governancethrough the development of an innovative platform entitled the DigitalPerformance Hub at the Academic Support Unit (UPA) Library of Universitas Jambi.Employing a small-scale action research design, this innovation integrates five keydevelopment components: strengthening peer communication forums, compilingan interactive Librarian Performance Dictionary based on Regulation of theMinister for Administrative and Bureaucratic Reform No. 55 of 2022, establishinga structured digital archive repository, refining daily reporting standards througha review of Standard Operating Procedures (SOPs), and providing a dedicatedconsultation channel via Google Sites. The implementation results demonstrate amarked improvement in independence, accountability, and collaborativeengagement in preparing valid and high-quality performance documentation. Userfeedback confirms that the system is highly beneficial, practical, and facilitatesefficient document retrieval, while also offering constructive recommendations forfuture enhancements in data visualization and system integration. This integratedmodel serves as a viable and replicable blueprint for library administrators at otherhigher education institutions aiming to advance toward a more comprehensivedigital transformation.
Co-Authors Andri Mardianto Nurhadi Nurhadi Pratiwi Devitasari R. M. Syahrial Sharipuddin, Sharipuddin