PERANCANGAN DAN PEMBANGUNAN SISTEM BACKEND APLIKASI MANAJEMEN PELATIHAN FISIK DI PPOP JAKARTA MENGGUNAKAN METODE SCRUM DAN ALGORITMA RULE-BASED ADAPTIVE INTENSITY RECOMMENDER (RAIR)

Alfarisi, Muhammad Salmaan (2025) PERANCANGAN DAN PEMBANGUNAN SISTEM BACKEND APLIKASI MANAJEMEN PELATIHAN FISIK DI PPOP JAKARTA MENGGUNAKAN METODE SCRUM DAN ALGORITMA RULE-BASED ADAPTIVE INTENSITY RECOMMENDER (RAIR). S1 thesis, Universitas Mercu Buana Jakarta - Menteng.

[img] Text
41521010042-Muhammad Salmaan Alfarisi-01 Cover - MUHAMMAD SALMAAN ALFARISI.pdf
Download (1MB)
[img] Text
41521010042-Muhammad Salmaan Alfarisi-02 Bab 1 - MUHAMMAD SALMAAN ALFARISI.pdf
Restricted to Registered users only
Download (445kB)
[img] Text
41521010042-Muhammad Salmaan Alfarisi-03 Bab 2 - MUHAMMAD SALMAAN ALFARISI.pdf
Restricted to Registered users only
Download (497kB)
[img] Text
41521010042-Muhammad Salmaan Alfarisi-04 Bab 3 - MUHAMMAD SALMAAN ALFARISI.pdf
Restricted to Registered users only
Download (2MB)
[img] Text
41521010042-Muhammad Salmaan Alfarisi-05 Bab 4 - MUHAMMAD SALMAAN ALFARISI.pdf
Restricted to Registered users only
Download (1MB)
[img] Text
41521010042-Muhammad Salmaan Alfarisi-06 Bab 5 - MUHAMMAD SALMAAN ALFARISI.pdf
Restricted to Registered users only
Download (424kB)
[img] Text
41521010042-Muhammad Salmaan Alfarisi-08 Daftar Pustaka - MUHAMMAD SALMAAN ALFARISI.pdf
Restricted to Registered users only
Download (338kB)
[img] Text
41521010042-Muhammad Salmaan Alfarisi-09 Lampiran - MUHAMMAD SALMAAN ALFARISI.pdf
Restricted to Registered users only
Download (1MB)

Abstract

Manajemen data merupakan komponen penting dalam pengelolaan informasi, terutama dalam pencatatan data atlet yang membutuhkan tingkat akurasi dan efisiensi tinggi. Saat ini, pelatih fisik atlet panahan di instansi PPOP masih menggunakan metode pencatatan manual, yang kurang efektif, memakan waktu, dan rentan terhadap kesalahan. Penelitian ini bertujuan untuk merancang sistem backend yang dapat mendukung aplikasi manajemen data atlet panahan sebagai solusi untuk meningkatkan efisiensi dan keakuratan pengelolaan data. Perancangan sistem menggunakan arsitektur Model-View-Controller (MVC) yang memisahkan komponen View, Controller, Model, dan Database, serta menerapkan metode pengembangan Scrum untuk memastikan proses pembangunan aplikasi yang adaptif dan iteratif. Selain itu, penelitian ini juga merancang dan mengimplementasikan algoritma Rule-Based Adaptive Intensity Recommender (RAIR), yang bekerja berdasarkan data heart rate (HR) target dan aktual. Algoritma ini menghitung selisih persentase HR (delta HR%) untuk memberikan rekomendasi intensitas latihan yang disesuaikan dengan jenis biomotorik tiap item latihan, seperti strength, endurance, strength-endurance, balance, dan flexibility. Hasil penelitian menunjukkan bahwa aplikasi manajemen pelatihan fisik yang dikembangkan dapat digunakan sesuai dengan kebutuhan pelatih. Algoritma RAIR yang diterapkan mampu memberikan rekomendasi intensitas latihan yang lebih personal dan terstruktur, serta berpotensi membantu pelatih dalam pengambilan keputusan latihan yang lebih tepat dan efisien. Data management is a critical component of information systems, particularly when handling athlete data that requires high levels of accuracy and efficiency. Currently, physical trainers for archery athletes at PPOP institutions still rely on manual methods for recording physical data, which are inefficient, time-consuming, and prone to error. This study aims to design a backend system to support an archery athlete data management application as a solution to improve both the efficiency and accuracy of data handling. The system design adopts the Model-View-Controller (MVC) architecture, emphasizing the separation of concerns among the View, Controller, Model, and Database components. The development process follows the Scrum methodology to ensure an adaptive and iterative approach to application development. Additionally, the study introduces the design and implementation of the Rule-Based Adaptive Intensity Recommender (RAIR) algorithm. This algorithm operates based on target and actual heart rate (HR) data, calculating the percentage difference in HR (delta HR%) to provide training intensity recommendations tailored to the biomotor type of each training item, such as strength, endurance, strength-endurance, balance, and flexibility. The results show that the physical training management application meets the needs of trainers. The implemented algorithm is capable of delivering more personalized and structured intensity recommendations, with strong potential to support trainers in making more accurate and efficient training decisions.

Item Type: Thesis (S1)
NIM/NIDN Creators: 41521010042
Uncontrolled Keywords: RAIR, heart rate, Scrum, Arsitektur MVC, biomotorik latihan, Rekomendasi intensitas, Laravel RAIR, heart rate, Scrum, MVC Architecture, exercise biomotoric, Intensity Recommendation, Laravel
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
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: YOSUA EBENEZER PARDEDE
Date Deposited: 04 Aug 2025 02:14
Last Modified: 04 Aug 2025 02:14
URI: http://repository.mercubuana.ac.id/id/eprint/96501

Actions (login required)

View Item View Item
UMB Repository is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.