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All Journal Informatika Journal of Computer Science and Information Systems (JCoInS) Journal of Student Development Informatics Management (JoSDIM) Journal of Student Development Information System (JoSDIS)
Masrizal Masrizal
Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Labuhanbatu
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Library & Information Science Other

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Perancangan Pembelajaran Media Animasi (Studi Kasus SD Negeri 22 Rantau Utara) Dengan Menggunakan Adobe Flash Devi lestari Hutagalung; Masrizal Masrizal; Irmayanti Irmayanti
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6030

Abstract

Dalam era digital seperti sekarang adalah zaman yang maju. Dalam kemajuan tersebut didukung oleh teknologi yang berkembang pesat. Komputer dapat digunakan sebagai sarana pembelajaran yang menarik dan interaktif, sehingga dapat meningkatkan minat dan antusias peserta didik. Media pembelajaran berbasis komputer dapat menyajikan materi pembelajaran secara visual dan audio yang lebih menarik dan mudah dipahami. Selain itu, media pembelajaran berbasis komputer juga dapat memberikan umpan balik secara langsung kepada peserta didik, sehingga dapat membantu siswa untuk memahami materi pembelajaran dengan lebih baik ,  tempat penelitian SDN 22 Rantau Utara merupakan salah satu sekolah Dasar Negeri di daerah Pulo Padang yang beralamat di Pasir Tinggi, kecamatan rantau utara kabupaten labuhanbatu sumatra utara. SDN 22 Rantau Utara. Penelitian ini menggunakan Adobe Flash sebagai aplikasi perancangan animasi pengenalan huruf dan angka.
Implementasi Data Mining Untuk Klustering Stunting Gizi Pada Balita Dipuskesmas Sigambal Meggunakan Metode K-Medoids Dan K-Means Melisa Melisa; Syaiful Zuhri Harahap; Masrizal Masrizal
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6159

Abstract

The aim of this study was to identify and understand the different characteristics of toddlers in the context of factors that contribute to nutritional stunting. By using the clustering method, this study aims to group toddlers into several groups based on the similarity of their characteristics, so that more targeted interventions can be designed in dealing with stunting problems. Through this approach, it is hoped that significant patterns and risk factors can be found that distinguish stunted toddlers from toddlers who grow normally, and provide insights that can be used by policy makers and health practitioners to improve the quality of life of children. The method used in this study involves the application of two clustering techniques, namely K-Means and K-Medoids to Group sample data of 116 toddlers. The clustering process is carried out by measuring the distance between the toddler data and the centroid or medoid to determine which group is most suitable. The Data were analyzed to find patterns identifying unique characteristics of each cluster, reflecting differences in nutritional stunting-related risk factors.This process helps in differentiating groups of toddlers who are prone to stunting from those who are not, so that the analysis can be focused on the groups most in need of intervention. The results of clustering analysis showed that as many as 48 toddlers entered the C1 cluster, while the other 68 toddlers entered the C2 cluster. Each cluster describes two groups of toddlers with different characteristics in the context of nutritional stunting risk factors. The findings provide deep insight into the significant differences between the two groups, allowing researchers to identify specific patterns and risk factors. This information is then used to design more specific and effective interventions in addressing nutritional stunting in toddlers, taking into account the unique characteristics of each cluster that has been identified.
Simulasi Kinerja Karyawan di Kantor Pertanahan Labuhanbatu Menggunakan Algoritma C4.5 Khodijah Nasution; Masrizal Masrizal; Syaiful Zuhri Harahap
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6160

Abstract

Employee performance analysis using the C4.5 algorithm in data mining aims to identify and classify employees based on their performance. The analysis process includes several stages, namely data analysis, preprocessing, model design in data mining, and method evaluation. From 47 sample data analyzed, the results show that 40 employees have good characters, while 7 employees have bad characters. Good employee characters are characterized by punctuality and high discipline in carrying out their duties. Conversely, bad employee characters are characterized by unpunctuality and low discipline, which have a negative impact on productivity and efficiency in the workplace. The results of this classification help identify areas that require more attention and intervention to improve overall employee performance. Model evaluation is carried out using two widgets, namely Test and Score and Confusion Matrix. The evaluation results of these two widgets show perfect accuracy of 100%. Meanwhile, the Confusion Matrix widget shows that all predictions are in accordance with the actual data without any errors in classification. These results confirm that the C4.5 algorithm is very effective and accurate in classifying employee performance. The perfection of the evaluation results shows that the C4.5 algorithm is very suitable for use as a classification model in employee performance analysis. The 100% accuracy of both widgets indicates that this algorithm is not only able to predict correctly but also consistently in various evaluation tools.
Penerapan Data Mining Untuk Evaluasi Data Penjualan Menggunakan Metode Clustering Dan Agoritma Hirarki Divisive Studi Kasus Toko Sembako Pujo Ade Eka Febriyanti; Syaiful Zuhri Harahap; Masrizal Masrizal
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6161

Abstract

The larger a company, the longer the company stands, the more companies have branches, of course, the greater the data owned. These data can be consumer data, purchase data, sales data, payroll data, and many other data. All data will usually be stored in a database. But many companies, even the Information Technology (IT) division, do not realize how valuable the pile of old data generated by the company in transactions and activities. Data mining is the study of methods for generating knowledge or finding patterns for processing data. So it's not just information, it's knowledge. Data Mining has several methods including clustering. Clustering is a well-known and widely used method in data mining. The main purpose of this clustering method is to Group a number of data/objects into clusters (groups) so that the cluster will contain the same data as each group. In this study, Divisive hierarchy algorithm is used to form clusters. From the pattern obtained is expected to provide knowledge for the company Media World Pekanbaru as a supporting tool to take policy.
Analisis Kinerja Sistem Informasi SMK Swasta Pemda Yuni Saputri; Marnis Nasution; Masrizal Masrizal
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6120

Abstract

This research aims to analyze the performance of the information system used in local government private vocational schools, which plays an important role in supporting the smooth operation of schools, including the teaching and learning process, administration and financial management. The research method used is benchmarking, which involves collecting data through interviews, observations and questionnaires. The research results show that the existing information system still has several weaknesses, such as lack of integration between systems, inaccurate data reporting, and low efficiency in data processing. Based on these findings, this research provides recommendations for improving the information system in local government private vocational schools to make it more effective and efficient in supporting school activities.
Co-Authors Ade Eka Febriyanti Adelia Nitami Aprilia Andrini Munthe Auliya Wardah Bilah Siregar Devi lestari Hutagalung Ibnu Rasyid Munthe Irmayanti Irmayanti Khodijah Nasution Lenni Pefrianti Marnis Nasution Melisa Melisa Ngolu Hotdiana Simanullang Syaiful Zuhri Harahap Yuni Saputri