Article Per Year (5 Year)
p-Index From 2021 - 2026
2.908
P-Index
This Author published in this journals
All Journal Teknika Sinkron : Jurnal dan Penelitian Teknik Informatika Bina Insani ICT Journal Jurnal Pilar Nusa Mandiri Information System for Educators and Professionals : Journal of Information System Techno Nusa Mandiri : Journal of Computing and Information Technology J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) JISICOM (Journal of Information System, Infomatics and Computing) EVOLUSI : Jurnal Sains dan Manajemen REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer IJISTECH J-SAKTI (Jurnal Sains Komputer dan Informatika) INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System J-Icon : Jurnal Komputer dan Informatika
Heny Sumarno, Heny
Universitas Bina Sarana Informatika
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Social Sciences Other

Published : 26 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 26 Documents
Search

 1   2   3 
Penerapan Metode Profile Matching pada Pemilihan Guru Terbaik SMK Madani S, Susliansyah; Wijayanti, Annisa Dwi; Sumarno, Heny; Priyono, Hendro; Maulida, Linda
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 1 (2020): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i1.197

Abstract

Depok Madani Vocational School is a Vocational High School consisting of 2 majors namely Light Vehicle Engineering (TKR) and Computer and Network Engineering (TKJ) with 20 teachers as instructors from class X to class XII. The selection of the best teachers is done once a month to motivate the teacher in conducting teaching and learning activities. Schools in making decisions are often influenced by subjectivity and are done manually. Resulting in social jealousy among teachers and inaccurate decision results. Therefore, in assessing the best teachers a decision support system is needed in order to obtain accurate results. Decision Support System methods used in this study is Profile Matching. The method determines the value of weights on each criterion, which is to be present on time, responsibility, dress neatly and politely, participate and contribute, be active and productive, and help fellow teachers, which is followed by a ranking process. The result of the comparison of the two methods above is to produce the same chosen alternative, so that both methods can be applied to help the school's decision making.
Pengelompokkan Data Pembelian Tinta Dengan Menggunakan Metode K-Means Susliansyah, Susliansyah; Sumarno, Heny; Priyono, Hendro; Hikmah, Noer
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i2.156

Abstract

PT. Mayer Indah Indonesia is engaged in the production of goods, where the most important part to prepare the needs for production needs is the purchasing department, but in the purchasing section it is difficult to determine which items must be bought a lot, are and few in meeting the demand requirements of each part because of the needs goods for production are very unpredictable, eventually causing some goods demand not to be fulfilled because the goods are out of stock. To solve the problems experienced by the purchasing part, datamining using clustering algorithm is k-means method, where the initial stages determine the centroid randomly and do the first iteration calculation and determine the new centroid from the first iteration, then the second iteration calculation is done, because the results of the first and second iterations in the smallest layout of the three groups, the calculation stops. The results obtained by using the ink purchase data seen from the three attributes of incoming goods, items purchased and stock of goods, making it easier and help the purchasing department in classifying items that must be purchased a lot, medium and little.
USE OF UI/X ON WEBSITE RECOMMENDATION OF LAPTOP SPECIFICATIONS WITH K-MEANS ALGORITHM Susliansyah, Susliansyah; Sumarno, Heny; Priyono, Hendro; Maulida, Linda; Indriyani, Fintri
J-Icon : Jurnal Komputer dan Informatika Vol 13 No 1 (2025): March 2025
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v13i1.20552

Abstract

The process of choosing a laptop that suits their needs is often a challenge for consumers because of the variety of specifications and features offered. Many consumers find it difficult to make the right choice, especially because the information available is often not well structured. In addition, each individual's needs vary, ranging from use for daily productivity to special needs such as gaming or graphic design. Therefore, this study aims to develop a prototype design of a laptop recommendation system using the K-Means clustering algorithm, which is able to group laptop specification data into certain clusters based on the similarity of features. A total of 25 laptop specification data were used in this analysis, with the main parameters being RAM capacity and SSD capacity. The data was processed using the data mining method, and the K-Means algorithm was applied to perform grouping. The optimal number of clusters is determined using the elbow method to ensure accurate and relevant results. The results of the grouping show that laptops can be classified into specific groups that represent consumer needs, such as use for daily productivity or high-load work. The prototype design of this system was created using Figma to visualize an intuitive and easy-to-use user interface (UI). With this prototype design, it is hoped that it can be a reference in the development of a system that makes it easier for consumers to choose a laptop that suits their preferences and needs.
EMPLOYEE PAYROLL INFORMATION SYSTEM (CASE STUDY: PT SURYAMEGA JAYA STEEL) Panjaitan, Herlina; Afni, Nurul; Sumarno, Heny; Maulana, Yana Iqbal; Komarudin, Rachman
Journal of Information System, Informatics and Computing Vol 7 No 2 (2023): JISICOM (December 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v7i2.1256

Abstract

The payroll system is a series of business activities that aim to complete all payments for services that have been made by employees. Payroll is a process within an organization/agency that is prone to problems. Data processing that is still done manually can result in slow preparation of salary reports which results in delays in payment of salaries to employees plus if there is an error in calculating the salary it becomes inaccurate. In this study, the author tries to design a web-based payroll system at PT Suryamega Jaya Steel, which until now has not been computerized. This web-based system was written to simplify the payroll transaction process so that salary calculations are more accurate and employees can print payslips. The author designed a web-based payroll information system using the PHP programming language. The method used in designing the software for this payroll application is in the form of the waterfall method, data collection techniques, observation, and interviews. The design of this information system is the best solution to solve the problems that exist in this company. A computerized system is better than a manual system because a computerized system can run more safely than the system used before.
Rancangan Aplikasi Algoritma C4.5 pada Stunting Balita Menggunakan Bahasa Phyton Susliansyah Susliansyah; Sigit Yugi Wargiyo; Heny Sumarno; Hendro Priyono; Linda Maulida
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 9 No. 1 (2025): Volume 9 Nomor 1 Januari 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v9i1.14426

Abstract

Stunting pada balita merupakan salah satu masalah kesehatan serius di Indonesia, yang memengaruhi pertumbuhan fisik dan kognitif anak. Dalam upaya memahami dan memprediksi faktor-faktor risiko yang berkaitan dengan stunting pada balita, digunakan teknologi data mining. Penelitian ini bertujuan mengembangkan aplikasi berbasis algoritma C4.5 untuk memprediksi status gizi balita, menggunakan bahasa pemrograman Python dan aplikasi Orange. Data yang berasal dari dataset "Stunting Toddler Detection" di Kaggle, dengan fokus pada variabel umur, tinggi badan, dan status gizi. Data tersebut digunakan sebagai bahan analisis, dengan tahapan preprocessing, integrasi data, hingga penerapan algoritma C4.5. Metode penelitian melibatkan pengolahan data menggunakan Python untuk analisis awal, sementara Orange dimanfaatkan untuk membangun pohon keputusan dan evaluasi model. Hasil pengujian menunjukkan algoritma C4.5 menghasilkan akurasi sebesar 36% di Orange dan 40% di Python, dengan faktor utama yang memengaruhi status gizi balita adalah tinggi badan. Aplikasi yang dikembangkan juga dilengkapi antarmuka visual untuk mempermudah tenaga kesehatan dan pemangku kebijakan dalam menganalisis risiko stunting.
Penerapan Klastering pada Data Mining dalam Menentukan Status Gizi Anak Balita dengan Menggunakan Algoritma K-Medoids Susliansyah Susliansyah; Heny Sumarno; Hendro Priyono; Linda Maulida; Fintri Indriyani
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 10 No. 1 (2026): Volume 10 Nomor 1 Januari 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v10i1.15710

Abstract

Status gizi balita merupakan indikator penting yang mencerminkan kesehatan dan perkembangan anak. Penilaian gizi biasanya dilakukan melalui pengukuran berat badan, tinggi badan, serta perhitungan Indeks Massa Tubuh (IMT). Namun, proses klasifikasi secara manual seringkali membutuhkan waktu dan berisiko menimbulkan ketidaktepatan, sehingga diperlukan metode yang lebih efisien. Penelitian ini menggunakan pendekatan data mining dengan algoritma k-medoids untuk mengelompokkan status gizi balita. Algoritma ini bekerja dengan menentukan medoid sebagai pusat kelompok yang mewakili karakteristik balita berdasarkan tinggi, berat, dan IMT. Balita lain kemudian diklasifikasikan sesuai jarak terdekat dengan medoid tersebut. Hasil penelitian menunjukkan bahwa penerapan k-medoids mampu mengelompokkan balita ke dalam kategori normal, kurang gizi, dan obesitas secara lebih sistematis. Temuan ini diharapkan dapat membantu tenaga kesehatan dalam mengidentifikasi balita yang membutuhkan tindakan secara khusus, sehingga mendukung tumbuh kembang anak secara optimal.
Co-Authors Aditia Dwinanto Deleaniara. M, Chyntia Marianna Dinda Ayu Muthia Dyah Wulandari Fadillah, Khoirul Fintri Indriyani Hendro Priyon Hendro Priyono Hikmah, Noer I Gusti Bagus Wiksuana Indra Riyana Rahadjeng Linda Maulida Maulida , Linda Maulida, Linda Nisan Nisan Nur Lutfiyana Nur, Muarif Zamzam Nurul Afni Panjaitan, Herlina Petrus Christo Priyono, Hendro Rachman Komarudin S Susliansyah Sigit Yugi Wargiyo Susliansyah, Susliansyah WAHYUDI, DIKI Widi Atmaja Wijayanti, Annisa Dwi Yahdi Kusnadi Yana Iqbal Maulana