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All Journal IKRA-ITH Informatika : Jurnal Komputer dan Informatika Journal of Information Systems and Informatics Journal of Innovation and Future Technology (IFTECH) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer TIN: TERAPAN INFORMATIKA NUSANTARA Academia Open Jurnal Teknik Informatika (JUTIF) JOINTER : Journal of Informatics Engineering Journal La Multiapp Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Indonesian Journal of Innovation Studies Ismart Edu: Jurnal Pendidikan Teknologi Informasi Jurnal Minfo Polgan (JMP) Jurnal Locus Penelitian dan Pengabdian Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Sains Informatika Terapan (JSIT) Innovative: Journal Of Social Science Research Jurnal Penelitian Teknologi Informasi dan Sains The Indonesian Journal of Computer Science Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi FIMERKOM: Journal of Information Systems and Technology
Kristofel Santa
Universitas Negeri Manado
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Journal : Academia Open

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Support Vector Machine Algorithm for Classifying Public Satisfaction Index: Algoritma Mesin Vektor Dukungan untuk Klasifikasi Indeks Kepuasan Publik Moningkey, Efraim Ronald Stefanus; Harisondak, Della Deviani; Santa, Kristofel
Academia Open Vol. 10 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.12697

Abstract

General Background: Evaluating public satisfaction with government services is vital to ensuring transparency and continuous improvement in public administration. Specific Background: At the Investment and One-Stop Integrated Services Office (DPMPTSP) of Minahasa Regency, satisfaction assessment has been limited by manual data processing and a lack of integrated systems, leading to inefficiencies in monitoring and classification. Knowledge Gap: Existing approaches to measuring the Public Satisfaction Index (IKM) have not effectively utilized machine learning to automate classification and provide real-time recommendations. Aims: This study aims to implement the Support Vector Machine (SVM) algorithm to classify public satisfaction levels and support service evaluation at DPMPTSP Minahasa. Results: Using 182 testing datasets, the system successfully categorized satisfaction into four levels—very satisfied, satisfied, less satisfied, and dissatisfied—with the majority of respondents classified as satisfied. The developed web-based system also provided actionable recommendations for each satisfaction level. Novelty: This study presents an integrated and automated framework that applies SVM to the public service domain, enabling efficient, accurate, and real-time evaluation. Implications: The findings demonstrate that machine learning can enhance public service management by facilitating data-driven decision-making and promoting service quality improvements. Highlight : The SVM algorithm effectively classifies public satisfaction levels into four categories. The web-based system improves efficiency and accuracy in service evaluation. Recommendations from the system support continuous service quality improvement. Keywords : Public Satisfaction Index, Support Vector Machine, Classification, Service Quality, DPMPTSP Minahasa
Co-Authors Aldo Napu Alfiansyah Hasibuan Alfiansyah Hasibuan Andi R. Widyastuti Arbie, Arif Tegar Elgifari Atuna, Annisa Salsabilah Audy Aldrin Kenap Bojoh, Cristy E. P. Daeng, Mushendra Dani Orlando Daniel Riano Kaparang Detuage, Rivni Djami Olii Dotulong, Gratia Whaitney Injili Ezra Matthew Warouw Runturamby Ferdinan I. Sangkop Filisia R. Terok Gladly Caren Rorimpandey Glenn Maramis Harisondak, Della Deviani Hasibuan, Alfiansyah Inda, Inda Irene Realyta Halldy Trosi Tangkawarow Julio Tabea Kambey, Waraney Maurits Kawuwung, Prillya Chrisanta Esthefania Kowaas, Jonathan Krina Crisila T. Mawuntu Kumajas, Sondy C. Kumajas, Sondy Campvid Maramis, Glenn David Paulus Martina Lorensa Moningkey, Efraim Moningkey, Efraim R. S. Moningkey, Efraim Ronald Stefanus Muhammad Lukmansyah Sulaiman Nanda, Agus Estepen Nasib Marbun Ngalo, Semuel Fendy Ningsi, Indi Rahayu Olivia Kembuan Pagala, J. Rifaldo Palandeng, Fanuel Juventino Panambunan, Stiven Pandoh, Kevin Mclaren parabelem tinno dolf rompas Pateh, Qnardo Delon Peggy Veronica Togas Pesik, Luisa Maria Quido Conferti Kainde Rahanubun, Basilius Mario Vikranta Ranti, Marthasya Chantika Putri Ratu, Regina Gloria Rumayar, Eroldy Rumengan, Maria Rina Rumondor, Geralda Lucia Saknohsiwy, Lorida Julensa Holiba Sondakh, Inggried Rillya Sondy C. Kumajas Tagah, Christenia Tendean, Chelsea Aprilia Tinambunan, Medi Hermanto Tiwi, Heri Susan Tular, Feonri Vivi Peggie Rantung Wagey, Imanuel Hiskia Wahyuni, Reski Waraney Maurits Kambey Wijayanti, Wilma Wowor, Hanna Elisabeth