A Prototype-Based Monitoring System for Customer Installment Fine Payments at PT. PLN (Persero) ULP Arso

The advancement of information technology has encouraged public service institutions, including PT. PLN (Persero), to adopt web-based systems to improve operational efficiency. At ULP Arso, the current monitoring of customer installment fine payments is managed manually using physical documents and basic spreadsheets. This method is prone to data entry errors, information redundancy, and delayed updates, which hinder timely decision-making and customer service. To address these issues, this study aims to design and develop a web-based monitoring system that facilitates real-time data access and simplifies tracking of installment payments. The research employed the prototyping development model, emphasizing iterative design involving early user feedback and continuous refinement. Data were collected through interviews, direct observations, and documentation at ULP Arso. The resulting prototype includes modules for user registration, login, customer and admin dashboards, bill management, and financial reporting. Functional testing using the blackbox approach demonstrated that all features operated according to specifications, and the system responded reliably across various usage scenarios. The study contributes by offering a practical solution that digitizes manual processes, thereby improving data accuracy and streamlining administrative tasks. From a practical perspective, the system supports data-driven decisions and enhances transparency and accountability in the customer billing process, aligning with the broader goal of improving public service quality in the electricity sector.

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Publication Details

Journal
Jurnal Ilmiah Sistem Informasi
Published
2025-08-10
DOI
https://doi.org/10.51903/ak4sch17
Primary Topic
IoT-based Control Systems
Type
article
Field-Weighted Citation Impact
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article

A Prototype-Based Monitoring System for Customer Installment Fine Payments at PT. PLN (Persero) ULP Arso

Patmawati Hasan, Ajenkris Yanto Kungkung, Noberti Chandra Putra Tambay
Jurnal Ilmiah Sistem Informasi
IoT-based Control Systems
article

A Prototype-Based Monitoring System for Customer Installment Fine Payments at PT. PLN (Persero) ULP Arso

Patmawati Hasan, Ajenkris Yanto Kungkung, Noberti Chandra Putra Tambay
article en

Abstract

The advancement of information technology has encouraged public service institutions, including PT. PLN (Persero), to adopt web-based systems to improve operational efficiency. At ULP Arso, the current monitoring of customer installment fine payments is managed manually using physical documents and basic spreadsheets. This method is prone to data entry errors, information redundancy, and delayed updates, which hinder timely decision-making and customer service. To address these issues, this study aims to design and develop a web-based monitoring system that facilitates real-time data access and simplifies tracking of installment payments. The research employed the prototyping development model, emphasizing iterative design involving early user feedback and continuous refinement. Data were collected through interviews, direct observations, and documentation at ULP Arso. The resulting prototype includes modules for user registration, login, customer and admin dashboards, bill management, and financial reporting. Functional testing using the blackbox approach demonstrated that all features operated according to specifications, and the system responded reliably across various usage scenarios. The study contributes by offering a practical solution that digitizes manual processes, thereby improving data accuracy and streamlining administrative tasks. From a practical perspective, the system supports data-driven decisions and enhances transparency and accountability in the customer billing process, aligning with the broader goal of improving public service quality in the electricity sector.

Jurnal Ilmiah Sistem InformasiVol. 4(3)
Sepuluh Nopember Institute of Technology (ID)
Openalex Percentile: Top 78%
IoT-based Control Systems
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