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All Journal Jurnal Informatika dan Rekayasa Perangkat Lunak ATRABIS: Jurnal Administrasi Bisnis (e-Journal) Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD MANAJEMEN Bulletin of Science Education Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Hukum Prioris Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Journal of Informatics, Electrical and Electronics Engineering AMMA : Jurnal Pengabdian Masyarakat JURNAL RUMPUN MANAJEMEN DAN EKONOMI MERDEKA: Jurnal Ilmiah Multidisiplin Journal of Economic and Bussiness Retail Ekliptika: Jurnal Inovasi Teknologi Berkelanjutan
Rudi Kurniawan
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Journal : Jurnal Informatika dan Rekayasa Perangkat Lunak

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Analisis Data Stok Alat Kesehatan menggunakan Metode Regresi Linier Berdasarkan Nilai RMSE Trian Nurmansyah; Rudi Kurniawan; Yudhistira Arie Wijaya
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10275

Abstract

Inventory of healthcare equipment, whether in hospital or clinic settings, represents a significant investment requiring substantial cost allocation. However, estimating these equipment needs often relies solely on the overall available stock, as monthly or yearly requirements tend to fluctuate. Consequently, this approach leads to an inability to meet all necessary equipment needs, resulting frequently in surplus inventory. Therefore, anticipating this issue requires predicting healthcare equipment stock at Klinik Pembina Sehat. This study aims to forecast equipment stock using the linear regression algorithm method. The selection of this algorithm is due to its suitability in handling the linear relationship between dependent and independent variables. Research findings demonstrate the developed model's ability to predict healthcare equipment stock with a reasonably high level of accuracy, with a Root Mean Square Error (RMSE) value of 93.359. This value signifies a relatively low prediction error, indicating the model's precision in estimating stock requirements. Thus, this research holds the potential to enhance operational efficiency in managing healthcare equipment stock within the clinic and serves as a foundation for further studies to improve stock planning processes in similar healthcare institutions.
Co-Authors Ajudin Antoni Zulius Arif Rinaldi Dikananda Budi Santoso Dadang Sudrajat Defrizal Defrizal Dian Prawitasari Diva Aulia Nurfitriani Fakhmi Zakaria Fatihanursari Dikananda Ferdi Saputra fikri firmansyah Fitriyana M. Rukin Herry Subagyo Hilda Novia Ramadani Ibnu Fajri Ida Farida iis Riyana Irham Zaini Mubarok Joko Supriyanto Julia Arum Mustikasari Kalimatus Saroh Kekieta Gustie Berizky LATIFAH Lisnawati Mahda, Muhammad Mamlu'atul Khoiru Nisa Martanto Maulana Ridwan Mochammad Imron Awalludin Muhammad Iqbaludin Muttaqien, Zaenal Nabila Salsa Azzahra Nafhan Khairuddin Fathin Novianti Indah Putri NUR HAMIDAH Nurul Fauziah Oktoriza, Linda Ayu Riri Narasati Ryan Hamonangan Saeful Amri Saeful Anwar Santi Nurjulaiha Setiyo Adi Wibowo Shinta Virgiana Suteja Syaiful Imanudin Tati Suprapti Tirta, M Sandy Trian Nurmansyah Tuti Nuriyati Umi Hayati Windi Herlita Vidila Yudhistira Arie Wijaya Yunia Eka Putri Zen Munawar Zulfa Hana Aqliyah