Article Per Year (5 Year)
p-Index From 2020 - 2025
1.116
P-Index
This Author published in this journals
All Journal KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Computer Networks, Architecture and High Performance Computing Jurnal Armada Informatika Jurnal Masyarakat Indonesia
Matias Julyus Fika Sirait
STMIK Budi Darma, Medan, Indonesia
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 9 Documents
Search

 1 
IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI PEMESANAN DRIVER GO-JEK ONLINE DENGAN MENGGUNAKAN METODE NAIVE BAYES (STUDI KASUS: PT. GO-JEK INDONESIA) Laia, Delisman; Buulolo, Efori; Sirait, Matias Julyus Fika
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v2i1.972

Abstract

PT. Go-Jek Indonesia is a service company. Go-jek online is a technology-based motorcycle taxi service that leads the transportation industry revolution. Predictions on ordering go-jek drivers using data mining algorithms are used to solve problems faced by the company PT. Go-Jek Indonesia to predict the level of ordering of online go-to drivers. In determining the crowded and lonely time. The proposed method is Naive Bayes. Naive Bayes algorithm aims to classify data in certain classes. The purpose of this study is to look at the prediction patterns of each of the attributes contained in the data set by using the naive algorithm and testing the training data on testing data to see whether the data pattern is good or not. what will be predicted is to collect the data of the previous driver ordering, which is based on the day, time for one month. The Naive Bayes algorithm is used to predict the ordering of online go-to-go drivers that will be experienced every day by seeing each order such as morning, afternoon and evening. The results of this study are to make it easier for the company to analyze the data of each go-jek driver booking in taking policies to ensure that both drivers and consumers or customers.Keywords: Go-jek Driver, Data Mining, Naive Bayes
IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI PEMESANAN DRIVER GO-JEK ONLINE DENGAN MENGGUNAKAN METODE NAIVE BAYES (STUDI KASUS: PT. GO-JEK INDONESIA) Laia, Delisman; Buulolo, Efori; Sirait, Matias Julyus Fika
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v2i1.972

Abstract

PT. Go-Jek Indonesia is a service company. Go-jek online is a technology-based motorcycle taxi service that leads the transportation industry revolution. Predictions on ordering go-jek drivers using data mining algorithms are used to solve problems faced by the company PT. Go-Jek Indonesia to predict the level of ordering of online go-to drivers. In determining the crowded and lonely time. The proposed method is Naive Bayes. Naive Bayes algorithm aims to classify data in certain classes. The purpose of this study is to look at the prediction patterns of each of the attributes contained in the data set by using the naive algorithm and testing the training data on testing data to see whether the data pattern is good or not. what will be predicted is to collect the data of the previous driver ordering, which is based on the day, time for one month. The Naive Bayes algorithm is used to predict the ordering of online go-to-go drivers that will be experienced every day by seeing each order such as morning, afternoon and evening. The results of this study are to make it easier for the company to analyze the data of each go-jek driver booking in taking policies to ensure that both drivers and consumers or customers.Keywords: Go-jek Driver, Data Mining, Naive Bayes
Penerapan Metode Analytical Hierarchy Procces (Ahp) Untuk Pengangkatan Karyawan Tetap Matias Julyus Fika Sirait
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 2 No. 2 (2020): Jatilima
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v2i2.42

Abstract

Employees are a determinant of the success of a company, therefore employees have a very important role in determining the progress of the company, the determination of permanent employees at the company is sometimes done not objectively, the assessment is done subjectively with unclear parameters, so that the results of the assessment are detrimental to employees who have the ability well. The criteria for determining permanent employees are performance, discipline, loyalty, experience, psychological tests, peer assessment. The results of the assessment of employees who participated in the employee selection named Jenter were employees who were selected as permanent employees with a value of 0.50.
SISTEM INFORMASI IZIN GEREJA PADA KEMENTERIAN AGAMA KOTA BINJAI DENGAN METODE PROTOTYPING Matias Julyus Fika Sirait; Rosinnyl Gultom
Jurnal Armada Informatika Vol 2 No 2 (2018): JURNAL ARMADA INFORMATIKA
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Gereja mempunyai peran penting dalam membangun relasi antara manusia dengan Tuhan. Peran tersebut dapat dilihat dari berbagai kegiatan gereja, dimana dalam pelaksanaanya membutuhkan pengelolaan informasi yang baik. Informasi tersebut antara lain pendataan gereja, pengurus gereja, izin mendirikan bangunan. Informasi yang telah disimpan oleh gereja akan dilaporkan kepada Kementerian Agama Kota Binjai agar dapat dicatat..Namun dalam proses pencatatan informasi gereja tersebut, Kementerian Agama mendapatkan beberapa masalah antara lain proses pencarian data yang memakan waktu lama serta pembuatan laporan yang cukup sulit dikarenakan data-data yang diperlukan harus dikumpulkan terlebih dahulu./Dalam penelitian ini, penulis melakukan analisis terhadap masalah-masalah yang ada pada Kementerian Agama Kota Binjai, Hasil analisis yang telah penulis lakukan akan menjadi acuan dalam pengembangan sebuah sistem informasi yang dapat membantu Kementerian Agama dalam menyelesaikan masalahnya. Hasil akhir dari penelitian ini adalah sebuah aplikasi sistem informasi berbasis web yang dapat digunakakan di Kementerian Agama Kota Binjai
Implementasi Penulisan Buku Referensi pada Mahasiswa/i Universitas Budi Darma Medan Sirait, Matias Julyus Fika; Rajagukguk, Denni M
Jurnal Masyarakat Indonesia (Jumas) Vol. 3 No. 02 (2024): Jurnal Masyarakat Indonesia (Jumas)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to evaluate the implementation of reference book writing for students of Budi Darma University Medan as an active learning method. Reference book writing is considered as a form of active learning that can improve students' material understanding, research skills, and academic writing. The research method used was a mixed approach, involving surveys, interviews, observations, and document analysis to collect data from students and lecturers involved. The results showed that reference book writing had a significant positive impact on students' material understanding, research skills, and academic writing ability. Most students reported improved understanding and skills after engaging in the project. However, there were some challenges, including difficulties in team coordination, high workload, and problems in editing the material. The discussion revealed that the reference book writing method was effective in deepening students' understanding of the material and improving their academic skills. Nonetheless, the challenges encountered point to the need for better project management strategies and consistent mentorship support. In conclusion, reference book writing as an active learning method proved effective in improving students' academic skills at Universitas Budi Darma Medan. To maximize the results, it is recommended that the university provide additional training, more intensive guidance, and effective project management guidelines. This research provides valuable insights into the implementation of active learning methods and provides recommendations for improvement in its application in higher education.
Gradient Magnitude Based Image Classification and Edge Detection for Pattern Recognition in Grayscale Images Simangunsong, Pandi Barita Nauli; Andriani, Tuti; Sirait, Matias Julyus Fika
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4611

Abstract

Image classification is a crucial technique in digital image processing, used in various applications such as object recognition, surveillance systems, and medical image analysis. This research explores the use of gradient magnitude-based edge detection and Robert's Cross methods in improving the classification accuracy of grayscale images. Edge detection is used to identify object boundaries, while gradient magnitude amplifies intensity differences, thus clarifying existing patterns. Through experiments conducted on grayscale images, the results show that this method is able to detect edges with significant accuracy. The gradient values obtained from the combination of Rx and Ry matrices give a strong indication of the presence of edges, which plays an important role in image classification. With an accuracy of 75%, the method proved to be effective, although there are still challenges in dealing with images with high noise or low contrast. The conclusion of this study shows that the combination of edge detection and gradient magnitude is a promising approach for image classification, providing results that can be applied in various domains, including medical and surveillance. Further research is recommended to optimize this approach and extend its application to more complex datasets.
Analisis Komputasi dan Efisiensi Pelatihan Model Deep Learning pada Skala Besar Bangunan Simangunsong, Pandi Barita Nauli; Tuti Andriani; Muhammad Amin; Pristiwanto; Sirait, Matias Julyus Fika
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 02 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i02.1499

Abstract

Penerapan deep learning pada sistem bangunan pintar telah menunjukkan potensi besar dalam meningkatkan efisiensi energi melalui prediksi beban, deteksi okupansi, dan pengendalian sistem HVAC. Namun, pelatihan model dalam skala besar menghadapi tantangan serius terkait kebutuhan data besar dan beban komputasi tinggi. Penelitian ini bertujuan menganalisis efektivitas dan efisiensi pelatihan model deep learning pada skala besar bangunan, serta mengevaluasi peran transfer learning sebagai strategi pengurangan beban pelatihan. Penelitian menggunakan arsitektur MLP, LSTM, dan CNN, serta pendekatan feature extraction dan fine-tuning dalam transfer learning. Evaluasi dilakukan terhadap akurasi, F1-score, RMSE, serta metrik efisiensi seperti waktu pelatihan, penggunaan memori, dan jumlah parameter. Hasil menunjukkan bahwa MLP memberikan performa terbaik untuk klasifikasi okupansi, sementara LSTM unggul dalam prediksi energi. Transfer learning terbukti efektif dalam mempertahankan akurasi dengan efisiensi pelatihan yang lebih tinggi. Model ringan seperti MLP + Transfer Learning (FE) mengurangi konsumsi memori hingga 35% dibanding pelatihan penuh, tanpa penurunan akurasi signifikan. Penelitian ini menyimpulkan bahwa kombinasi pemilihan arsitektur yang tepat dan strategi pelatihan efisien sangat penting dalam implementasi praktis model deep learning pada bangunan pintar berskala besar.
Penggunaan Mendeley dalam Penulisan Karya Tulis Ilmiah bagi Komunitas Akademik Simangunsong, Pandi Barita Nauli; Siagian, Novriadi Antonius; Sirait, Matias Julyus Fika; Maulidina; Pristiwanto
Jurnal Masyarakat Indonesia (Jumas) Vol. 4 No. 02 (2025): Jurnal Masyarakat Indonesia (Jumas)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jumas.v4i02.265

Abstract

Pelatihan Penggunaan Mendeley dalam Penulisan Karya Tulis Ilmiah bagi Komunitas Akademik dilaksanakan di Sekolah Tinggi Ilmu Kesehatan Darmo dengan tujuan untuk meningkatkan kompetensi dosen dalam mengelola referensi secara efisien dan sesuai standar akademik. Mendeley sebagai aplikasi manajemen referensi dipilih karena kemampuannya dalam menyusun sitasi dan daftar pustaka secara otomatis serta integrasinya dengan berbagai platform penulisan ilmiah. Pelatihan ini mencakup materi instalasi, pembuatan akun, penggunaan Mendeley secara manual, dan pemanfaatan fitur Web Importer. Metode pelatihan bersifat partisipatif dan berbasis praktik langsung. Hasil evaluasi menunjukkan bahwa 92% peserta merasa pelatihan ini sangat bermanfaat dan 89% tertarik untuk mengikuti pelatihan lanjutan. Selain itu, peserta mengusulkan agar kegiatan ini dijadikan program rutin untuk mendukung peningkatan mutu publikasi ilmiah dosen. Pelatihan ini terbukti efektif dalam membekali dosen dengan keterampilan teknis yang relevan dan mendorong terbentuknya budaya penulisan ilmiah yang profesional dan terstandar di lingkungan perguruan tinggi.
Gradient Magnitude Based Image Classification and Edge Detection for Pattern Recognition in Grayscale Images Simangunsong, Pandi Barita Nauli; Andriani, Tuti; Sirait, Matias Julyus Fika
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4611

Abstract

Image classification is a crucial technique in digital image processing, used in various applications such as object recognition, surveillance systems, and medical image analysis. This research explores the use of gradient magnitude-based edge detection and Robert's Cross methods in improving the classification accuracy of grayscale images. Edge detection is used to identify object boundaries, while gradient magnitude amplifies intensity differences, thus clarifying existing patterns. Through experiments conducted on grayscale images, the results show that this method is able to detect edges with significant accuracy. The gradient values obtained from the combination of Rx and Ry matrices give a strong indication of the presence of edges, which plays an important role in image classification. With an accuracy of 75%, the method proved to be effective, although there are still challenges in dealing with images with high noise or low contrast. The conclusion of this study shows that the combination of edge detection and gradient magnitude is a promising approach for image classification, providing results that can be applied in various domains, including medical and surveillance. Further research is recommended to optimize this approach and extend its application to more complex datasets.
Co-Authors Denni M Rajagukguk Efori Buulolo Laia, Delisman Laia, Delisman Maulidina Muhammad Amin Pristiwanto Rosinnyl Gultom Siagian, Novriadi Antonius Simangunsong, Pandi Barita Nauli Tuti Andriani Tuti Andriani