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      Implementasi Modul Pemadaman Listrik dengan Peringatan Dini pada Executive Dashboard IKN

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      Date
      2026
      Jenis/Type
      Tugas Akhir
      Subtype
      Undergraduate Theses
      Author
      ANGGRAENI, AULIA
      Novianty, Inna
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      Abstract
      Ibu Kota Nusantara (IKN) dirancang sebagai kota cerdas yang membutuhkan sistem kelistrikan secara digital. Namun, Executive Dashboard IKN yang dikelola PLN Icon Plus belum memiliki modul pengelolaan data pemadaman listrik, sehingga pencatatan dan penyebaran informasi pemadaman masih dilakukan secara manual. Untuk mengatasi permasalahan tersebut, pada penelitian ini mengimplementasikan modul pemadaman listrik dengan fitur peringatan dini pada Executive Dashboard IKN menggunakan metodologi Agile Scrum, framework Laravel, basis data PostgreSQL, dan Bootstrap. Pengembangan dilaksanakan dalam empat sprint yang menghasilkan modul jenis padam, modul data pemadaman, fitur import Excel, serta sistem peringatan dini berupa pop-up website dan notifikasi email kepada subscriber. Pengujian Black Box Testing terhadap 86 skenario uji menghasilkan persentase keberhasilan 100%, sehingga sistem dinyatakan telah memenuhi kebutuhan fungsional dan non-fungsional PLN Icon Plus dan layak digunakan pada Executive Dashboard IKN.
       
      The Nusantara Capital City (IKN) is designed as a smart city requiring a digital electricity system. However, the IKN Executive Dashboard managed by PLN Icon Plus lacks a dedicated module for electricity outage data management, resulting in manual recording and dissemination of outage information. To address this issue, this study implements a power outage module with an early warning feature on the IKN Executive Dashboard using the Agile Scrum methodology, Laravel framework, PostgreSQL database, and Bootstrap. Development was carried out in four sprints, producing an outage type module, an outage data module, an Excel import feature, and an early warning system consisting of a public website pop-up and email notifications to subscribers. Black Box Testing across 86 test scenarios yielded a 100% pass rate, indicating that the system has fulfilled the functional and non-functional requirements set by PLN Icon Plus and is ready for use on the IKN Executive Dashboard.
       
      URI
      http://repository.ipb.ac.id/handle/123456789/175702
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      • UF - Software Engineering Technology [307]

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      Copyright © 2020 Library of IPB University
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      Contact Us | Send Feedback
      Indonesia DSpace Group 
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