PREDICTING THE CHARACTERISTICS OF DRIVER’S LICENSE APPLICANTS AT SATPAS POLRESTA MANOKWARI USING HIERARCHICAL MULTIPLE REGRESSION
DOI:
https://doi.org/10.30656/jsii.v11i2.9056Abstract
This research aims to predict the characteristics of driver's license (SIM) applicants at the SATPAS (Driver’s License Issuance Unit) Polresta Manokwari using Hierarchical Multiple Regression analysis. The study explores six key variables: gender, age, occupation, city, type of driver's license, and type of application, as predictors of applicant characteristics. The analysis was conducted using SPSS version 29, with data collected from the population of driver's license applicants since 2023. Three models were tested, with Model 3 being identified as the best predictor, explaining 7% of the variance in applicant characteristics (R² = 0.070). This model incorporates the variables of age, occupation, city, and type of application, while gender and driver's license class were found to have no significant individual impact. The partial t-test results show that age, occupation, city, and type of application significantly influence applicant characteristics, with negative regression coefficients indicating that an increase in these variables leads to a decrease in the predicted characteristics of SIM applicants. The study highlights practical implications for SATPAS, suggesting that service processes could be improved by considering demographic factors such as age and occupation in order to optimize resource allocation and reduce service complexity. However, the study has several limitations. The use of secondary data limits the completeness and accuracy of the analysis, and the limited number of variables results in a narrow interpretation of the factors influencing SIM applicants. Additionally, the model explains only a small portion of the variance in applicant characteristics, suggesting that other unmeasured factors, such as education level or driving experience, may play a more significant role. Furthermore, the findings are not generalizable to other regions, as local conditions may impact license application patterns. Future research should address these limitations by collecting primary data, expanding the range of variables, employing more sophisticated analytical methods, and exploring other regions. This would provide a more comprehensive understanding of the factors affecting driver's license applicants and contribute to enhancing the quality of SIM issuance services in Indonesia.
Keywords: Driver's License, Prediction, Hierarchical Multiple Regression, Applicant Characteristics
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References
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H. Purnamasari, M. Bintang Ramadhan, H. Syaban Bashar, and D. Noviyanti, “Kualitas Pelayanan Publik dalam Pembuatan Surat Izin Mengemudi Kendaraan Motor (SIM C) di Polres Karawang,†J. Polit. Indones., vol. 5, no. 2, pp. 64–74, 2020.
E. Handrian, “Pelayanan Pembuatan Surat Izin Mengemudi Golongan C ( Sim C ) Pada Sat Lantas Polresta Pekanbaru,†Publika, vol. 5, no. 1, pp. 137–155, 2019.
U. A. Wibowo and S. M. Widada, “Efektivitas Usia 17 Tahun Pada SIM C Guna Mengurangi Kecelakaan Lalu Lintas Surakarta,†J. Univ. Sebel. Maret, vol. 1, no. 2, pp. 99–120, 2013.
A. Maryati, T. Arbain, and M. R. Syafari, “Kualitas Pelayanan Pembuatan Surat Izin Mengemudi (Sim C) Di Kantor Satuan Lalu Lintas Kepolisian Resort Hulu Sungai Utara,†J. Adm. Publik dan Pembang., vol. 5, no. 1, pp. 1–13, 2023.
D. Ratnasari and L. Y. Hendrati, “Hubungan Kepemilikan SIM C dengan Kejadian Kecelakaan Lalu Lintas pada pelajar SMA di Wonokromo Kota Surabaya,†Media Gizi Kesmas, vol. 12, no. 1, pp. 112–117, 2023.
S. Tamara and H. Sasana, “Analisis Dampak Ekonomi Dan Sosial Akibat Kemacetan Lalu Lintas Di Jalan Raya Bogor-Jakarta,†J. Ris. Ekon. Pembang., vol. 2, no. 2, 2017.
korlantas polri, “JUMLAH DATA KENDARAAN POLDA PAPUA BARAT,†rc.korlantas.polri.go.id, 2024. [Online]. Available: http://rc.korlantas.polri.go.id:8900/eri2017/laprekappolres.php?kdpolda=24&poldanya=PAPUA BARAT.
K. Aribowo, “Pengaruh Pelayanan Satpas Terhadap Kepuasan Pemohon Sim Pada Polres Tanah Laut Di Kabupaten Tanah Laut,†J. Ilm. Ekon. Bisnis, vol. 3, no. 1, 2017.
A. Juwita, “Optimalisasi Sim Online Sebagai Strategi untuk Mewujudkan Pelayanan Prima pada Kantor Satpas Jember,†Airlangga Dev. J., vol. 2, no. 2, p. 84, 2018.
S. Adiguno, Y. Syahra, and M. Yetri, “Prediksi Peningkatan Omset Penjualan Menggunakan Metode Regresi Linier Berganda,†J. Sist. Inf. Triguna Dharma (JURSI TGD), vol. 1, no. 4, p. 275, 2022.
M. S. Omar, R. Ahmad, and C. S. Mustaffa, “The Moderating Effects of Compensation on Motivation and Performance: A Case Study of Fast-food Employees in Malaysia,†Asia-Pacific J. Innov. Hosp. Tour., vol. 10, no. 3, pp. 1–18, 2021.
P. Jain and P. Jain, “Trait emotional intelligence as predictor of psychological health in undergraduate medical students: A hierarchical multiple regression approach,†Indian J. Physiol. Pharmacol., vol. 67, no. 1, pp. 21–28, 2023.
R. Juita et al., “The effect of the perceived mobility and the provider reputation towards the usage continuance of the personal cloud storage,†in 2020 Fifth International Conference on Informatics and Computing (ICIC), 2020, pp. 1–6.
A. Putri, Y. Syafrialdi, and M. Mustakim, “Analisa Pengaruh Temperatur Terhadap Titik Embun, Jarak Pandang, Kecepatan Angin, Dan Curah Hujan Metode Regresi Linier Berganda,†Semin. Nas. Teknol. Inf. Komun. dan Ind., no. 9, pp. 227–234, 2017.
A. and Ross and V. L. Willson, “"Hierarchical Multiple Regression Analysis Using at Least Two Sets of Variables (In Two Blocks),†in Basic and Advanced Statistical Tests: Writing Results Sections and Creating Tables and Figures, Rotterdam: SensePublishers, 2017, pp. 61–74.
E. P. Prawirohartono, Memahami penelitian epidemiologi klinis secara mudah : analisis data dan menulis hasil penelitian. UGM PRESS, 2024.
I. Tawakkal, “Analisis Pengaruh Online Customer Review Terhadap Performa Penjualan Produk Pada Public E-Marketplace,†Institut Teknologi Sepuluh Nopember, 2018.
A. Nur, I. M. A. Pradnyana, M. Windu, and A. Kesiman, “Analisis Faktor-Faktor Yang Mempengaruhi Tingkat Pelayanan Polresta Denpasar Menggunakan Model,†vol. 8, pp. 224–237, 2019.
N. Wanma, D. I. Inan, and L. Y. Baisa, “Evaluasi User Experience Dan User Interface Aplikasi Laporkitong Dengan End User Computing Satisfaction something that is of great concern and determines the experience of using it for the people of,†Jutisi J. Ilm. Tek. Inform. dan Sist. Inf., vol. 13, no. 1, pp. 304–313, 2024.
N. Y. Subay, D. I. Inan, R. Juita, M. Sanglise, and D. R. Podajow, “Design And Evaluation of User Experience Using the Heuristic Evaluation Method: A Case of Papua University Website,†G-Tech J. Teknol. Terap., vol. 8, no. 2, pp. 1016–1029, 2024.
A. J. o. Turkson and J. E. ri. Otchey, “Hierarchical multiple regression modelling on predictors of behavior and sexual practices at Takoradi Polytechnic, Ghana,†Glob. J. Health Sci., vol. 7, no. 4, pp. 200–210, 2015.
H. F. Kennedy, “Efektivitas Pelayanan Satuan Administrasi Penerbitan SIM Terhadap Kepuasan Masyarakat di Satpas Polres Sidoarjo,†J. Ilmu Kepol., vol. 15, no. 2, pp. 103–128, 2021.
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