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All Journal Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Ilmiah Teknik Informatika dan Komunikasi Satya Informatika Jurnal Elektronika dan Teknik Informatika Terapan
Billy Hendrik
Universitas Putra Indonesia “YPTK” Padang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science Social Sciences Other

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Evaluasi Performa Deteksi Penyakit Diabetes Dengan Fuzzy C-Means Dan K-Means Clustering Roy Efendi Subarja; Billy Hendrik
Jurnal Elektronika dan Teknik Informatika Terapan Vol. 1 No. 3 (2023): September: Jurnal Elektronika dan Teknik Informatika Terapan ( JENTIK )
Publisher : Politeknik Kampar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59061/jentik.v1i3.376

Abstract

The increasing prevalence of diabetes has led to a growing need for accurate and efficient disease detection methods. This research focuses on evaluating the performance of diabetes detection using Fuzzy C-Means and K-Means clustering algorithms. The study aims to compare the effectiveness of these two clustering techniques in identifying diabetes cases based on relevant medical data. A dataset comprising various health parameters and diagnostic indicators was utilized for experimentation. The Fuzzy C-Means and K-Means algorithms were implemented to cluster the dataset, and their detection performance was assessed using metrics such as sensitivity, specificity, accuracy, and F1-score. The results indicate that both clustering methods exhibit promising potential for diabetes detection, with variations in their performance based on different evaluation criteria. This research contributes to a deeper understanding of the applicability of clustering algorithms in diabetes detection and provides insights into their strengths and limitations. Further optimization and validation of these algorithms could lead to enhanced diagnostic accuracy and early intervention in diabetes management.
PENILAIAN KINERJA PEGAWAI BMT INDRAGIRI MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) Doni Karseno; Billy Hendrik
JURNAL SATYA INFORMATIKA Vol. 8 No. 02 (2023): SATYA INFORMATIKA
Publisher : FAKULTAS TEKNIK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59134/jsk.v8i2.534

Abstract

Sistem penilaian kinerja Pegawai adalah sebuah sistem yang digunakan untuk menilai kinerja terbaik para pegawainya. Lembaga atau institusi melakukan penilaian kinerja terbaik terhadap pegawainya untuk mengevaluasi, memverikasi,memotivasi untuk meningkatkan kinerjanya. Hasil dari kinerja ini untuk mengetahui atau membantu pengambilan keputusan yang mana hasil dari keputusan ini berdampak kepada pegawai itu sendiri seperti promosi, demosi, pemberhentian, bonus dan juga potongan bagi pegawai. Didalam penilaian penelitian yang dilakukan menggunakan 6 kriteria : Kehadiran, Sikap/Atitude, Kerajinan, Kreatifitas,kualitas dan kuantitas menggunakan metode Simple Additive Weighting (SAW). Konsep dasar dari metode Simple Additive Weighting (SAW) adalah mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif pada semua atribut. Metode Simple Additive Weighting (SAW) dapat membantu pengambilan keputusan untuk menghasilkan nilai terbesar sebagai alternatif yang terbaik. Pada penelitian ini dilakukan pengujian terhadap 75 data responden. Dari pehitungan dan pengujian didaptkan akurasi data sejumlah 100%, yaitu banyak data yang sesuai dibagi dengan banyak data yang diuji dikalikan 100%.
EVALUASI TINGKAT AKURASI IMPLEMENTASI FUZZY INFERENCE SYSTEM UNTUK JUMLAH PERAMALAN PESERTA BPJS KESEHATAN Roy Efendi Subarja; Billy Hendrik
JURNAL SATYA INFORMATIKA Vol. 8 No. 02 (2023): SATYA INFORMATIKA
Publisher : FAKULTAS TEKNIK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59134/jsk.v8i2.538

Abstract

Penelitian ini membahas tentang evaluasi akurasi penerapan Fuzzy Inference System (FIS) dalam peramalan jumlah peserta BPJS Kesehatan. Metode FIS Sugeno digunakan untuk memprediksi jumlah peserta BPJS Kesehatan berdasarkan data historis. Artikel ini menjelaskan langkah-langkah dalam penerapan metode FIS, termasuk pembentukan himpunan fuzzy, aplikasi fungsi implikasi, dan defuzzifikasi. Hasil evaluasi menunjukkan bahwa metode FIS memiliki tingkat akurasi sebesar 94.17% dalam memprediksi jumlah peserta BPJS Kesehatan. Artikel ini memberikan kontribusi penting dalam meningkatkan efektivitas peramalan jumlah peserta BPJS Kesehatan dan dapat digunakan sebagai acuan dalam pengambilan keputusan terkait program kesehatan masyarakat.
Klasterisasi Faktor Orang Tua Dalam Memilih Sekolah Taman Kanak-Kanak Menggunakan Algoritma K-Means Clustering (Studi Kasus : TK Aek Litta) Diffri Solihin Siregar; Billy Hendrik
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 3 No. 3 (2023): November : Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Barenlitbangda Kabupaten Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v3i3.660

Abstract

School is a place where students are taught under the guidance of teachers. Schools have an important role in developing children's intellectual capacity because school is a place where children look for information and hone their skills. Choosing a school that suits your child's character is very important. Children need kindergarten education to develop their character and personality and to prepare themselves for entering elementary school. There are many things parents choose to do when choosing a school for their children, including: distance, facilities, curriculum, costs, etc. In this case, to find out the parents' factors in choosing a kindergarten school for their child, the author uses the K-Means algorithm to see the highest factors that make parents choose the Aek litta kindergarten school. K-Means separates data into groups according to how close each group is to a particular cluster. The results of the clustering process with 3 iterations stated that for cluster 1 there were 7 parents who had similar factors in choosing Aek Litta Kindergarten, for cluster 2 there were 3 parents with similar factors.
Implementasi Algoritma Apriori Pada Sistem Persediaan Stok Obat Akhiruddin Pulungan; Billy Hendrik
Jurnal Elektronika dan Teknik Informatika Terapan Vol. 1 No. 4 (2023): Desember: Jurnal Elektronika dan Teknik Informatika Terapan ( JENTIK )
Publisher : Politeknik Kampar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59061/jentik.v1i4.462

Abstract

As a fairly large institution, management and system development that needs to be designed from a manual basis to a digital basis is very necessary, of course, so that the use of Technology and Information can also be applied to minimize deficiencies and bring the expected profits in providing medicine stock at Islamic boarding school clinics. Due to geographic location, it is necessary to develop a system that can assist in handling the availability of drug stocks so that the process of distributing drugs to patients can run without problems. It is hoped that the use of the Apriori algorithm can help in supplying medicine stock at the Darul Mursyid Islamic boarding school.
Implementasi Blueprint Sistem Informasi Monitoring Pelanggaran Siswa di MAN 1 Padangsidimpuan dalam Bentuk Aplikasi Website Rizqi Nusabbih Hidayatullah Gaja; Billy Hendrik
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 3 No. 3 (2023): November : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Barenlitbangda Kabupaten Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v3i3.650

Abstract

This research intends to incorporate a blueprint design for a student violation information system that was developed in earlier research into a website-based application to record student violations at MAN 1 Padangsidimpuan. The needs analysis, system design, software development, testing, and implementation phases of the website application development process are all included in this study's waterfall methodology. The PHP programming language, the CodeIgniter framework, and the MySQL database were used to create this application. This study produced a web tool that MAN 1 Padangsidimpuan can utilize to more efficiently monitor student infractions. This program is anticipated to assist schools in managing student infractions, delivering transparency to both students and parents, and enhancing student conduct in the classroom.
Implementation Of The K-Means Clustering Algorithm For Grouping Heart Disease Risk Levels Sonia Indhira; Billy Hendrik
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 3 No. 3 (2023): November : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Barenlitbangda Kabupaten Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v3i3.677

Abstract

Heart disease is a condition where the heart cannot carry out its duties properly, this disease occurs when blood to the heart muscle stops or becomes blocked, causing serious damage to the heart. The KMeans algorithm can be used to cluster heart disease groups to find out if someone is affected heart disease or not. The clustering method with the k-means algorithm in this research shows a new insight, namely grouping the risk level of heart disease based on 3 clusters. Cluster 1 is a category age with a fairly low risk level for heart disease or Low, namely 355 out of 1025 age categories tested, then cluster 2 is the age category with a moderate risk level for heart disease, namely 208 out of 1025 age categories tested, and finally cluster 3 is an age category with a fairly high age category level or High, namely 462 of 1025 age categories tested.
Co-Authors Akhiruddin Pulungan Diffri Solihin Siregar Doni Karseno Rizqi Nusabbih Hidayatullah Gaja Roy Efendi Subarja Roy Efendi Subarja Sonia Indhira