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Susilo, Darmawan
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Computer Science & IT

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Aplikasi Handling Problem Unit IT Infrastruktur Divisi Teknologi Dan Sistem Informasi Pada Bpd Sumsel Babel Berbasis Website Susilo, Darmawan; Faradillah; Di Kesuma, Hendra
Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Lubuklinggau Vol 5 No 2 (2023): Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya
Publisher : STMIK Bina Nusantara Jaya Lubuk Linggau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52303/jb.v5i2.109

Abstract

The Regional Development Bank (BPD) of South Sumatra and Bangka Belitung (Sumsel Babel) is a financial institution with a complex and important IT infrastructure system in its operations. The purpose of this research is to develop an application that can help in handling these problems. The method used in this research is the waterfall method which consists of requirements analysis, design, implementation, testing, and maintenance. The proposed solution design is a website-based problem handling application. This application will provide access to the IT Infrastructure Team to submit problem reports and monitor repair status in real-time. Additionally, this application will also be equipped with user management features, access rights management, and notification systems that will inform users of repair status. It is hoped that with this application, the efficiency and effectiveness of IT infrastructure problem handling can be better, thus speeding up response time in problem solving and increasing customer satisfaction. In conclusion, the use of website-based problem handling applications at the Regional Development Bank (BPD) of South Sumatra and Bangka Belitung (Sumsel Babel) can help improve the performance of the IT infrastructure unit of the Technology and Information Systems Division, thereby expected to better meet user needs.
The Implementasi PyCaret untuk Meningkatkan Akurasi Prediksi Penjualan di PT. Sinar Megartha Perkasa Susilo, Darmawan; Terttiaavini; Kumalinda, Tri; Sagita, Lestari
Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Vol 7 No 1 (2025): Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya
Publisher : STMIK Bina Nusantara Jaya Lubuk Linggau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52303/jb.v7i1.153

Abstract

Sinar Megartha Perkasa menghadapi tantangan dalam meningkatkan akurasi prediksi penjualan, yang sangat penting untuk mendukung perencanaan strategis dan pengambilan keputusan yang efektif. Penelitian ini bertujuan untuk menerapkan PyCaret, sebuah pustaka machine learning open-source berbasis Python yang dirancang dengan pendekatan low-code, guna mengembangkan model prediksi penjualan yang lebih tepat. Metodologi yang digunakan mencakup pengumpulan data penjualan historis, pra-pemrosesan data, dan penerapan algoritma regresi melalui PyCaret. Untuk mengevaluasi kinerja model, digunakan metrik seperti Mean Absolute Error (MAE) dan Root Mean Squared Error (RMSE). Hasil penelitian menunjukkan bahwa penggunaan PyCaret secara signifikan meningkatkan akurasi prediksi penjualan jika dibandingkan dengan metode tradisional, dengan penurunan yang signifikan pada nilai MAE dan RMSE. Penelitian ini memberikan solusi praktis untuk pengembangan model prediksi penjualan yang efisien, yang dapat diintegrasikan ke dalam sistem manajemen PT. Sinar Megartha Perkasa. Dengan adanya prediksi yang lebih akurat, perusahaan dapat membuat keputusan strategis berbasis data untuk mempertahankan keunggulan kompetitif di pasar.
Co-Authors Di Kesuma, Hendra Faradillah Kumalinda, Tri Sagita, Lestari Terttiaavini