Analisis Penerimaan Aplikasi Maintenance System Online (MSO) di Perusahaan Semen Dengan Menggunakan Pendekatan Technology Change Readiness Model

Adicaraka, Kokoh (2026) Analisis Penerimaan Aplikasi Maintenance System Online (MSO) di Perusahaan Semen Dengan Menggunakan Pendekatan Technology Change Readiness Model. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Transformasi digital pada fungsi pemeliharaan melalui aplikasi Maintenance System Online (MSO) ditujukan untuk meningkatkan ketepatan pencatatan, efektivitas pelaksanaan pekerjaan, dan kualitas pengambilan keputusan. MSO telah diterapkan di perusahaan semen, tetapi hanya sekitar 33% pengguna yang tercatat aktif. Penelitian ini menganalisis faktor-faktor yang memengaruhi penerimaan dan penggunaan aktual MSO pada tenaga pemeliharaan dengan menggunakan technology change readiness model yang terdiri dari Understanding of Change (U), Perceived Change Value (P), Implementation Knowledge (I), Self-Efficacy (S), dan Organizational Support (O), serta variabel Behavioral Intention (BI) dan Actual Use (AU). Penelitian menggunakan pendekatan kuantitatif eksplanatori dengan desain survei cross-sectional. Data diperoleh dari 265 responden dan dianalisis melalui statistik deskriptif, uji validitas dan reliabilitas, pengujian asumsi klasik, serta regresi linier. Seluruh 21 indikator dinyatakan valid, dengan Cronbach's Alpha konstruk berkisar antara 0,7732 dan 0,9033. Seluruh jalur yang diuji berpengaruh positif dan signifikan pada p < 0,001. Understanding of Change memengaruhi Perceived Change Value (beta = 0,479), Perceived Change Value memengaruhi Implementation Knowledge (beta = 0,442), dan Implementation Knowledge memengaruhi Self-Efficacy (beta = 0,534). Self-Efficacy dan Organizational Support secara bersama-sama menjelaskan 24,4% variasi BI, dengan Organizational Support sebagai prediktor dominan (beta = 0,463). Selanjutnya, BI dan Organizational Support menjelaskan 37,9% variasi AU; pengaruh Organizational Support (beta = 0,367) sedikit lebih kuat daripada BI (beta = 0,355). Temuan menunjukkan bahwa kompetensi dan niat pengguna perlu didukung oleh penguatan organisasional yang konsisten. Rekomendasi utama meliputi monitoring utilisasi per unit, umpan balik supervisor, integrasi MSO ke dalam prosedur dan indikator kinerja, pelatihan berbasis tugas, pendampingan lapangan, serta evaluasi kualitas sistem dan kondisi kerja.
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Digital transformation in the maintenance function through the Maintenance System Online (MSO) application is aimed at improving the accuracy of recording, effectiveness of work implementation, and quality of decision-making. MSO has been implemented at the cement company; however, only approximately 33% of registered users are active. This study analyzes the factors that influence the acceptance and actual use of MSO in maintenance personnel using a technology change readiness model consisting of Understanding of Change (U), Perceived Change Value (P), Implementation Knowledge (I), Self-Efficacy (S), and Organizational Support (O), as well as the variables Behavioral Intention (BI) and Actual Use (AU). The study used a quantitative explanatory approach with a cross-sectional survey design. Data were obtained from 265 respondents and analyzed through descriptive statistics, validity and reliability tests, classical assumption tests, and linear regression. All 21 indicators were declared valid, with Cronbach's Alpha constructs ranging between 0.7732 and 0.9033. All tested paths had a positive and significant effect at p < 0.001. Understanding of Change influences Perceived Change Value (beta = 0.479), Perceived Change Value Influences Implementation Knowledge (beta = 0.442), and Implementation Knowledge influences Self-Efficacy (beta = 0.534). Self-Efficacy and Organizational Support together explain 24.4% of the variation in BI, with Organizational Support as the dominant predictor (beta = 0.463). Furthermore, BI and Organizational Support explain 37.9% of the variation in AU; the influence of Organizational Support (beta = 0.367) is slightly stronger than BI (beta = 0.355). The findings indicate that user competency and intention need to be supported by consistent organizational reinforcement. Key recommendations include unit utilization monitoring, supervisor feedback, integration of MSO into procedures and performance indicators, task-based training, field mentoring, and evaluation of system quality and working conditions.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Maintenance System Online, Technology Change Readiness Model, Penerimaan Teknologi, Behavioral Intention, Actual Use, Regresi Linier Berganda, Technology Acceptance, Multiple Linear Regression
Subjects:	T Technology > T Technology (General) > T57.74 Linear programming
Divisions:	Faculty of Business and Management Technology > Management Technology > 61101-(S2) Master Thesis
Depositing User:	Kokoh Adicaraka
Date Deposited:	30 Jul 2026 01:05
Last Modified:	30 Jul 2026 01:05
URI:	http://repository.its.ac.id/id/eprint/138588

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