AMNAR, SHAHIBUL (2026) RANCANG BANGUN SISTEM INFORMASI PENJUALAN DAN MANAJEMEN STOK KANTIN SEKOLAH BERBASIS LARAVEL DENGAN PENERAPAN MACHINE LEARNING. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
School canteens are essential facilities for students and staff, yet many still rely on manual management systems, leading to operational inefficiencies such as transaction errors, long queues, and inaccurate stock records. These manual processes often result in stockouts or overstocking due to the lack of secara langsung monitoring and berbasis data planning. This research aims to design and build a Sales and Inventory Management Information System based on the Laravel framework, integrated with the Random Forest Machine Learning algorithm. The study utilizes the Research and Development (R&D) method with a Waterfall development model, encompassing requirements analysis, system design, implementation, and testing. The system features a Point of Sales (POS) module to accelerate transactions and an automated inventory module that updates stock levels in secara langsung using MySQL. Furthermore, the Random Forest algorithm is implemented to analyze historical sales data and predict future stock requirements with a Mean Absolute Percentage Error (MAPE) of 7.9%. The outcome is a comprehensive system that enhances transaction efficiency, minimizes inventory risks, and supports berbasis data decision-making for canteen management. Keywords: Sales Information System, Inventory Management, Laravel, Machine Learning, Random Forest. Kantin sekolah memiliki peran penting dalam menyediakan kebutuhan konsumsi bagi siswa dan staf, namun pengelolaannya sering kali masih dilakukan secara manual sehingga menimbulkan berbagai inefisiensi seperti antrean panjang, kesalahan perhitungan, dan keterlambatan rekapitulasi data. Selain itu, ketidakteraturan dalam pencatatan stok sering menyebabkan masalah kehabisan stok (stockout) atau penumpukan barang (overstock) karena tidak adanya pemantauan secara secara langsung. Penelitian ini bertujuan untuk merancang dan membangun Sistem Informasi Penjualan dan Manajemen Stok berbasis kerangka kerja Laravel yang terintegrasi dengan Machine Learning. Algoritma Random Forest diterapkan untuk menganalisis data penjualan historis dan memprediksi kebutuhan stok di masa depan guna mendukung pengambilan keputusan pengadaan barang yang lebih akurat. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan alur pengembangan sistem model Waterfall, meliputi analisis kebutuhan, perancangan, implementasi, dan pengujian. Hasil dari penelitian ini adalah sebuah sistem yang mampu mempercepat proses transaksi melalui Point of Sales (POS), mengelola stok secara otomatis, serta memberikan prediksi stok dengan tingkat kesalahan (Mean Absolute Percentage Error/MAPE) sebesar 7,9%. Kata kunci: Sistem Informasi Penjualan, Manajemen Stok, Laravel, Machine Learning, Random Forest.
| Item Type: | Thesis (S1) |
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| NIM/NIDN Creators: | 41522010034 |
| Uncontrolled Keywords: | Sistem Informasi Penjualan, Manajemen Stok, Laravel, Machine Learning, Random Forest. |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.3 Artificial Intelligence/Kecerdasan Buatan > 006.31 Machine Learning/Pembelajaran Mesin |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | khalimah |
| Date Deposited: | 06 Aug 2026 07:20 |
| Last Modified: | 06 Aug 2026 07:20 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/103173 |
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