JOVI, MUHAMMAD AFIF (2024) PREDIKSI HARGA BAHAN PANGAN CABAI MERAH KERITING MENGGUNAKAN ALGORITMA RANDOM FOREST DENGAN VISUALISASI GRAFIK TABLEAU:STUDI KASUS PULAU SUMATERA. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
The Food Management Agency in Indonesia has developed a web dashboard map that displays comprehensive information about food in Indonesia. These dashboards are built using the Laravel and Tableau frameworks as data visualization tools. Through this dashboard, users can see information on food prices in the market, food availability in various regions, and food production locations in Indonesia. To improve predictability, food price prediction features using the Random Forest algorithm have been integrated. The Random Forest algorithm was chosen for its ability to process complex data and provide accurate predictions. The prediction implementation process includes data collection and preprocessing, model training, and testing and validation to ensure the accuracy of food price predictions. The development of this dashboard aims to monitor and manage food availability more effectively and efficiently, as well as assist Food Management Agencies in Indonesia in making better decisions related to managing food availability throughout the country In addition, the Business Process Map is also prepared to illustrate effective and efficient work relations in the organization. It consists of process maps, subprocess maps, and relationship maps, which help in optimizing internal governance and workflow. With the integration of web dashboard maps and Business Process Maps, as well as food price prediction features using Random Forest, Food Management Agencies in Indonesia have comprehensive tools to monitor food availability and prices, as well as optimize internal workflows. This study can be a reference for researchers and practitioners who are interested in developing web dashboard maps and Business Process Maps, especially in the context of managing food availability in Indonesia. Keywords: Instansi Pengelola Pangan Di Indonesia, Laravel, Tableau, Prediksi, Random Forest Instansi Pengelola Pangan Di Indonesia telah mengembangkan sebuah web dashboard peta yang menampilkan informasi komprehensif tentang pangan di Indonesia. Dashboard ini dibangun menggunakan framework Laravel dan Tableau sebagai alat visualisasi data. Melalui dashboard ini, pengguna dapat melihat informasi harga pangan di pasar, ketersediaan pangan di berbagai daerah, serta lokasi produksi pangan di Indonesia. Untuk meningkatkan kemampuan prediksi, fitur prediksi harga pangan menggunakan algoritma Random Forest telah diintegrasikan. Algoritma Random Forest dipilih karena kemampuannya dalam mengolah data kompleks dan memberikan prediksi yang akurat. Proses implementasi prediksi meliputi pengumpulan dan preprocessing data, pelatihan model, serta pengujian dan validasi untuk memastikan akurasi prediksi harga pangan. Pengembangan dashboard ini bertujuan untuk memantau dan mengelola ketersediaan pangan dengan lebih efektif dan efisien, serta membantu Instansi Pengelola Pangan Di Indonesia dalam mengambil keputusan yang lebih baik terkait pengelolaan ketersediaan pangan di seluruh negeri. Selain itu, Peta Proses Bisnis juga disusun untuk menggambarkan tata hubungan kerja yang efektif dan efisien dalam organisasi. Peta ini terdiri dari peta proses, peta subproses, dan peta relasi, yang membantu dalam mengoptimalkan tata kelola dan alur kerja internal. Dengan integrasi web dashboard peta dan Peta Proses Bisnis, serta fitur prediksi harga pangan menggunakan Random Forest, Instansi Pengelola Pangan Di Indonesia memiliki alat yang komprehensif untuk memantau ketersediaan dan harga pangan, serta mengoptimalkan alur kerja internal. Studi ini dapat menjadi referensi bagi peneliti dan praktisi yang tertarik dalam pengembangan web dashboard peta serta Peta Proses Bisnis, khususnya dalam konteks pengelolaan ketersediaan pangan di Indonesia. Kata Kunci : Instansi Pengelola Bahan Pangan Di Indonesia, Laravel, Tableau, Prediksi, Random Forest
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FIK/INFO. 24 132 |
| Call Number: | SIK/15/24/094 |
| NIM/NIDN Creators: | 41520010062 |
| Uncontrolled Keywords: | Instansi Pengelola Bahan Pangan Di Indonesia, Laravel, Tableau, Prediksi, Random Forest |
| Subjects: | 300 Social Science/Ilmu-ilmu Sosial > 380 Commerce, Communications, Transportation (Perdagangan, Komunikasi, Transportasi) > 381 Commerce, Trade/Perdagangan > 381.1 Retail Trade/Perdagangan Ritail, Pasar 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma 600 Technology/Teknologi > 630 Agriculture and Related Technologies/Pertanian dan Teknologi Terkait |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | khalimah |
| Date Deposited: | 10 Aug 2024 05:12 |
| Last Modified: | 10 Aug 2024 05:12 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/90143 |
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