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Pemetaan Kondisi Lingkungan Tanam menggunakan K-Means Clustering Kholila, Ni'ma; Mujiono, M; Wahyudi, Dona
JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Vol. 1 No. 2 (2023): Juni 2023
Publisher : Cipta Media Harmoni

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (674.677 KB) | DOI: 10.53624/jsitik.v1i2.182

Abstract

Melalui pendekatan clustering, data rekam yang terdiri dari waktu tanam, ph, suhu air, suhu udara, dan nilai TDS dapat dimanfaatkan guna memetakan kondisi lingkungan tanam. Melalui pemetaan kondisi lingkungan tanam, petani mendapatkan informasi tambahan terkait kondisi lingkungan tanam milik petani. Melalui informasi tersebut, diharapkan petani dapat memberikan tindakan pertanian yang sesuai dengan kondisi lingkungan tanam, lebih efektif dan efisien. Pemetaan kondisi lingkungan tanam menggunakan k-means clustering algorithm dalam 3 (tiga) cluster. Masing-masing merupakan cluster kondisi lingkungan tanam yang kurang nutrisi dan kurang air, cukup nutrisi tetapi kurang air, serta cukup nutrisi dan cukup air. Cluster testing menggunakan elbow method menunjukkan bahwa jumlah cluster optimal dalam pengelompokan K-Means adalah 3 cluster dengan nilai inersia 199.065.
Pengembangan Sistem Informasi Presensi Berbasis Global Positioning Systems dan Location-Based Service Utomo, Prabowo Budi; Wahyudi, Dona; Mujiono, M
Jurnal Informatika Terpadu Vol 11 No 1 (2025): Maret, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i1.1563

Abstract

This study focuses on the development of an attendance system based on the Global Positioning System (GPS) and Location-Based Service (LBS) using the Extreme Programming (XP) approach. This system helps institutions and companies enhance the accuracy and efficiency of employee attendance recording, particularly for mobile workers such as field employees or operational staff. The implementation of this system aims to overcome the limitations of conventional attendance methods, which are prone to manipulation, such as proxy attendance or multiple fingerprint recognition usage, as well as difficulties in accessing attendance data for auditing and performance evaluation purposes. GPS technology determines the user's real-time location, while LBS enhances the accuracy and reliability of location data. This study chooses the XP methodology due to its flexibility and adaptability to changing requirements during development. Testing results indicate the system achieves a 91.4% success rate in recording attendance with accurate location validation. The system is compatible with various devices and operational conditions, offering high flexibility in its implementation. However, challenges remain regarding external factors such as geographical conditions, weather, and device quality, which may affect location accuracy. Overall, this system offers a transparent, accurate, and efficient attendance solution.