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All Journal JURIKOM (Jurnal Riset Komputer) JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Qomaruddin, M
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Implementasi Website Penilaian Kinerja Paramedis pada Rumah Sakit Palasara, Nicodias; Anggraeni, Diah Ayu; Qomaruddin, M
JURIKOM (Jurnal Riset Komputer) Vol 7, No 3 (2020): Juni 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (542.15 KB) | DOI: 10.30865/jurikom.v7i3.2168

Abstract

Performance appraisal that still uses manual calculations and paper media, will use a lot of paper and archiving stacked files and often there are errors or unclear writing so that they do not get the right assessment results on target. As one of the means of public health service providers are required to improve the quality and professionalism in terms of health services, one of which is in the scope of health workers such as paramedics. Overcoming this, a significant increase in the number of paramedics in hospitals must be in line with good management by human resources officers, in order to improve the quality of health services. Then the implementation of the paramedic performance appraisal website at the hospital is one good solution to make it easier to overcome the problem. In this study created a website to support the paramedic performance evaluation. In making a website using the waterfall method, whose function can accelerate the results and quality of the website. Computerized performance appraisal systems run better and more efficiently than manual systems and can minimize paper usage and data accuracy
Penerapan Data Mining Classification untuk Data Blogger Menggunakan Metode Naïve Bayes Anggraini, Recha Abriana; Widagdo, Galih; Budi, Arief Setya; Qomaruddin, M
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 7, No 1 (2019)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (539.381 KB) | DOI: 10.26418/justin.v7i1.30211

Abstract

Jumlah pengguna situs blogger yang semakin meningkat  menyebabkan perlu dilakukan pengklasifikasian data untuk mengetahui pengguna tersebut masuk dalam kategori pengguna blogger professional atau bukan. Sebagai referensi terkait penelitian ini adalah penelitian yang sudah dilakukan oleh peneliti sebelumnya. Teknik pengklasifikasian pemodelan deskriptif dan prediktif dengan algoritma data mining yaitu menggunakan metode naïve bayes. Untuk mengelola data digunakan software rapid miner studio 6.0, dataset blogger diperoleh dari website UCI Machine learning Repository, Perhitungan performance vector menunjukkan akurasi klasifikasi metode Naive bayes diperoleh sebesar 86.67%.  Sedangkan class precision dan class recall untuk prediksi yes menunjukkan tingkat precision sebesar 91.30% dan untuk prediksino sebesar 71.43%. Hasil klasifikasi dari data blogger dengan metode naïve bayes membagi 2 kelas klasifikasi PB yaitu class yes dan class no. Untuk nilai class yes yaitu 0.680 dan nilai class no yaitu 0.320. Dari hasil pengolahan data dapat diketahui bahwa tingkat akurasi pengklasifikasian data blogger mencapai 86.67%.
Co-Authors Anggraeni, Diah Ayu Anggraini, Recha Abriana Budi, Arief Setya Nicodias Palasara widagdo, Galih