NURFAIDA, AWALIA (2021) APLIKASI PERSEDIAAN DAN PREDIKSI PENGADAAN BARANG KESEHATAN BERBASIS WEB (STUDI KASUS: PUSKESMAS KECAMATAN SAWAH BESAR). S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
The development of information systems and technology affects various fields, including health, namely Puskesmas. The Sawah Besar District Health Center has several work units, one of which is a stock management unit. The stock management unit still has problems managing data using Microsoft Excel so it is at risk of inputting errors and data is not integrated, thus hampering the process of accessing documents. The approval and prediction process for the procurement of health goods is also still done manually using physical documents. PHP programming language with Bootstrap Framework and MySQL running on Xampp which is used to develop applications. While the Naive Bayes method in PHP-ML is used to predict the procurement of health goods. Developed system with functions such as Procurement of Stock, Procurement of Procurement of Stock, Procurement of Stock Report. Expired Stock Dashboard, Health Goods Procurement Prediction and other functions assist system users in managing inventory data, stock approval process and prediction of health goods procurement. Key words: Health Goods Inventory, PHP-ML, Bootstrap Framework, Procurement prediction, Naive Bayes Perkembangan sistem informasi dan teknologi mempengaruhi berbagai bidang, diantaranya kesehatan yaitu Puskesmas. Puskesmas Kecamatan Sawah Besar memiliki beberapa unit kerja, salah satunya unit pengurus stok. Unit pengurus stok dalam melakukan tugasnya masih memiliki kendala diantaranya pengelolaan data masih menggunakan Microsoft Excel sehingga beresiko terhadap kesalahan penginputan dan data tidak terintegrasi, sehingga menghambat proses mengakses dokumen. Proses persetujuan dan prediksi pengadaan barang juga masih dilakukan secara manual menggunakan dokumen fisik. Bahasa pemrograman PHP dengan Bootstrap Framework serta MySQL yang dijalankan pada Xampp digunakan untuk mengembangkan aplikasi. Sedangkan metode Naive Bayes pada PHP-ML digunakan untuk prediksi pengadaan barang kesehatan. Sistem yang dikembangkan dengan fungsi-fungsi seperti Pengadaan Stok, Persetujuan Pengadaan Stok, Laporan Pengadaan Stok. Dashboard Stok Kadaluarsa, Prediksi Pengadaan Barang Kesehatan serta fungsi lainnya membantu pengguna sistem dalam melakukan proses pengelolaan data persediaan barang, proses persetujuan stok dan prediksi pengadaan barang. Kata kunci: Inventarisasi barang kesehatan, PHP-ML, Bootstrap Framework, Prediksi Pengadaan Barang, Naive Bayes
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