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All Journal Jurnal Teknologi Informatika dan Komputer Transformasi
Astrid Novita Putri, Astrid Novita
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Computer Science & IT Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mathematics

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Implementation of A Geographically Integrated On-Demand Computer Service System Using the KNN Method Wardana, Hafiq Ibnu; Putri, Astrid Novita
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2680

Abstract

The rapid development of information and communication technology has driven significant changes in various fields, including the service sector. Internet-based digital services provide quick and easy access to all needs, such as ordering transportation, food, or even services. On-demand services are services based on customer demand (Anjani & Sujarwo, 2023). This research aims to develop a web-based on-demand computer service system integrated with geographic location using the K-Nearest Neighbor (KNN) algorithm. Difficult access for customers with limited mobility, the lack of location-based partner distribution, and the manual partner search process remain major challenges in conventional computer service. The system was developed using Laravel as the backend framework and MySQL as the database processor, using the KNN method to measure the closest distance between the user's location and the partner based on latitude and longitude coordinates. The results show that the system can automatically provide information in the form of recommendations for the nearest technician partner, which can increase service time efficiency and make it easier for consumers to access professional computer service. A user-friendly interface and a simple ordering process can enhance user experience. This study recommends further system development by integrating digital payment methods and conducting more detailed classification accuracy testing to improve the quality of the service system's recommendations.
PREDIKSI PENYEBARAN TUBERKULOSIS DI INDONESIA MENGGUNAKAN SINGLE MOVING AVERAGE Wardhani, Anindya Khrisna; Putri, Astrid Novita; Sari, Nur Latifah Dwi Mutiara
TRANSFORMASI Vol 19, No 2 (2023): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v19i2.386

Abstract

Penelitian ini bertujuan untuk meramalkan penyebaran Tuberkulosis (TB) di Indonesia menggunakan metode Single Moving Average (SMA) dengan tiga variasi ordo: 10, 5, dan 3, berdasarkan data jumlah penderita TB dari tahun 2000 hingga 2022. Hasil prediksi menunjukkan bahwa SMA berordo 3 memberikan kinerja terbaik dengan Mean Squared Error (MSE) sebesar 45,315, Root Mean Squared Error (RMSE) sebesar 952, dan Mean Absolute Deviation (MAD) sebesar 287,542. Model ini lebih sensitif terhadap perubahan dalam data, memberikan prediksi yang lebih akurat dibandingkan dengan ordo 5 dan 10. Kesimpulan menyoroti bahwa penggunaan SMA berordo 3 dapat memberikan informasi yang lebih akurat tentang tren penyebaran TB di Indonesia. Rekomendasi penelitian lebih lanjut mencakup eksplorasi metode analisis prediktif lainnya dan mempertimbangkan faktor-faktor tambahan yang dapat memengaruhi penyebaran TB, seperti faktor lingkungan dan kebijakan kesehatan.
Co-Authors Nur Latifah Dwi Mutiara Sari Wardana, Hafiq Ibnu Wardhani, Anindya Khrisna