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All Journal Sebatik JATI (Jurnal Mahasiswa Teknik Informatika)
Abuzar Gafari
Magister Teknik Informatika, Universitas Putra Indonesia YPTK Padang
Computer Science & IT

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An Analysis of Public Satisfaction with Government Services: A Multi-Method Approach Using PCA, K-Means Clustering, and Linear Regression Abuzar Gafari; Sarjon Defit; Rini Sovia
Sebatik Vol. 30 No. 1 (2026): June 2026
Publisher : STMIK Widya Cipta Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46984/sebatik.v30i1.2742

Abstract

Flawless performance evaluation results across all service dimensions may potentially obscure the identification of areas for improvement and diminish objectivity in decision-making. This study aims to identify the specific service attributes influencing public satisfaction and to segment respondents based on their satisfaction levels at the Office of the Ministry of Religious Affairs in Payakumbuh City. The research integrates Principal Component Analysis (PCA), K-means clustering, and linear regression. PCA was employed to reduce data dimensionality and establish principal components; K-means clustering was utilized to group respondents based on perceptual similarities regarding service quality; and linear regression was applied to identify the most significant factors influencing public satisfaction within each segment. The data were sourced from the Public Service Survey Information System (SISULAP) application of the Payakumbuh Ministry of Religious Affairs, spanning June 2024 to October 2025, with a total of 1,950 respondents. The findings reveal that service process and efficiency are the primary factors influencing all respondent segments, with the low-satisfaction segment identified as the top priority for service improvement. The regression models demonstrate robust performance across all segments. These findings provide an empirical foundation for data-driven policymaking to enhance public service quality.
PENERAPAN METODE FUZZY LOGIC MAMDANI PADA SISTEM PAKAR DETEKSI DINI KESEHATAN MENTAL (DASS-42) Tsalsabila Jilhan Haura; Devi Maryuni; Abuzar Gafari; Rini Sovia
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 1 (2026): JATI Vol. 10 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i1.16730

Abstract

Kesehatan mental merupakan aspek penting yang memengaruhi kemampuan individu dalam berpikir, merasakan, serta berperilaku. Namun, tingkat kesadaran masyarakat terhadap gejala gangguan mental masih rendah, sehingga diperlukan metode deteksi dini yang mudah diakses. Penelitian ini bertujuan mengembangkan sistem pakar untuk mengidentifikasi tingkat kesehatan mental menggunakan metode Fuzzy Logic Mamdani berdasarkan instrumen Depression, Anxiety, Stress Scales (DASS-42). Instrumen ini terdiri dari 42 item pertanyaan yang dikelompokkan menjadi tiga variabel utama, yaitu Depresi, Kecemasan dan Stres masing-masing dengan lima kategori tingkat keparahan normal, ringan, sedang, parah dan sangat parah. Proses fuzzyfikasi dilakukan menggunakan fungsi keanggotaan segitiga dan trapesium, dilanjutkan dengan penerapan rule base yang disusun berdasarkan pengetahuan pakar serta defuzzifikasi metode centroid untuk menghasilkan nilai crisp sebagai output tingkat kesehatan mental. Hasil pengujian pada sampel data menunjukkan bahwa nilai Depresi 18, Kecemasan 12 dan Stres 20 menghasilkan output crisp Z = 40 sehingga dikategorikan sebagai tingkat mental Sedang. Temuan ini menunjukkan bahwa metode fuzzy logic mampu mengolah data psikologis yang bersifat subjektif dan tidak pasti secara efektif, sehingga sistem pakar dapat digunakan sebagai alat bantu deteksi dini sebelum dilakukan pemeriksaan lanjutan oleh profesional.
Co-Authors Devi Maryuni Sarjon Defit Sovia, Rini Tsalsabila Jilhan Haura