Garuda - Garba Rujukan Digital

Accuracy of K-Nearest Neighbors Algorithm Classification For Archiving Research Publications Muhamad Nur Gunawan; Titi Farhanah; Siti Ummi Masruroh; Ahmad Mukhlis Jundulloh; Nafdik Zaydan Raushanfikar; Rona Nisa Sofia Amriza
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3915

The Archives and Research Publication Information System plays an important role in managing academic research and scientific publications efficiently. With the increasing volume of research and publications carried out each year by university researchers, the Research Archives and Publications Information System is essential for organizing and processing these materials. However, managing large amounts of data poses challenges, including the need to accurately classify a researcher's field of study. To overcome these challenges, this research focuses on implementing the K-Nearest Neighbors classification algorithm in the Archives and Research Publications Information System application. This research aims to improve the accuracy of classification systems and facilitate better decision-making in the management of academic research. This research method is systematic involving data acquisition, pre-processing, algorithm implementation, and evaluation. The results of this research show that integrating Chi-Square feature selection significantly improves K-Nearest Neighbors performance, achieving 86% precision, 84.3% recall, 89.2% F1 Score, and 93.3% accuracy. This research contributes to increasing the efficiency of the Archives and Research Publication Information System in managing research and academic publications.

ANALISIS PENGARUH PLATFORM SOSIAL MEDIA TERHADAP PENYEBARAN INFORMASI BENCANA Amriza, Rona Nisa Sofia; Khairun Nisa Meiah Ngafidin
Jurnal Sistem Informasi Vol. 8 No. 2 (2021)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v8i2.3639

Abstrak- Sosial media menjadi platform yang sangat berperan dalam menyebarkan informasi, berita, dan memberikan informasi bencana secara cepat dan tepat. Banyak informasi berharga yang dapat diperoleh dalam platform ini. Penelitian ini menganalisis pengaruh platform sosial media terhadap intensi masyarakat untuk menyebarkan informasi bencana yang dipengaruhi oleh mediator personal yaitu altruisme dan efikasi diri. Penelitian ini mengobservasi penyebab seseorang memiliki intensi untuk menyebarkan informasi bencana. Structural Equation Modeling Partial Least Squares (SEM-PLS) digunakan untuk melakukan uji hipotesis. Dari penelitian ini kami menemukan bahwa mediator altruisme dan efikasi diri dalam platform sosial media berpengaruh secara signifikan terhadap intensi seseorang untuk menyebarkan informasi bencana. Kata Kunci: Sosial Media, Penyebaran Informasi, Penyebaran Informasi Bencana, Structural Equation Modeling, Partial Least Squares, SEM-PLS

Perancangan Enterprise Resource Planning Modul Sales Dengan Menggunakan Odoo pada PT XYZ Fitriana, Rian; Nurlaila, Ayu Annisa; Amriza, Rona Nisa Sofia
Prosiding Sains Nasional dan Teknologi Vol 11, No 1 (2021): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI 11 2021
Publisher : Fakultas Teknik Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/psnst.v1i1.5001

Perusahaan XYZ merupakan sebuah perusahaan manufaktur bergerak dibidang pengolahan makanan yang sangat berkembang di Indonesia dan berdiri pada tahun 1990. PT XYZ mencatat pertumbuhan laba dan penjualan di tengah pandemi COVID-19 pada tahun 2020 sebesar 10%, penjualan tersebut naik dari Rp.42,30 menjadi Rp.46,64 triliun, dapat diketahui dari data tersebut semakin naiknya permintaan konsumen terhadap perusahaan XYZ maka semakin banyak produk makanan yang harus tersedia, tetapi operasional penjualan antara team marketing dengan pelanggan masih menggunakan faktur, belum adanya sistem informasi yang terintegrasi antara pelanggan dengan team marketing. Untuk meningkatkan kinerja bisnis bagi pelanggan dan perusahaan, maka dibuatlah sebuah perancangan Enterprise Resource Planning (ERP) modul Sales dengan Odoo sebagai opensource software. Pengumpulan data terbagi dua yaitu data primer & data sekunder, data Primer dilakukan dengan cara observasi secara langsung di lapangan, sedangkan untuk data sekunder didapatkan pada jurnal yang telah dibuat pada penelitian sebelumnya. Hasil pada penelitian ini yaitu akan berdampak paka team marketing dalam memberikan pelayanan kepada pelanggan lebih efektif jika terjadi peningkatan penjualan yang sangat signifikan, selain itu dengan adanya sistem informasi terintegrasi antara pelanggan dengan team marketing memudahkan dalam penyebaran informasi secara realtime dalam pemberitahuan produk baru produk baru maupun harga serta informasi mengenai product cepat tersampaikan kepada customer.

Accuracy of K-Nearest Neighbors Algorithm Classification For Archiving Research Publications Muhamad Nur Gunawan; Titi Farhanah; Siti Ummi Masruroh; Ahmad Mukhlis Jundulloh; Nafdik Zaydan Raushanfikar; Rona Nisa Sofia Amriza
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3915

The Archives and Research Publication Information System plays an important role in managing academic research and scientific publications efficiently. With the increasing volume of research and publications carried out each year by university researchers, the Research Archives and Publications Information System is essential for organizing and processing these materials. However, managing large amounts of data poses challenges, including the need to accurately classify a researcher's field of study. To overcome these challenges, this research focuses on implementing the K-Nearest Neighbors classification algorithm in the Archives and Research Publications Information System application. This research aims to improve the accuracy of classification systems and facilitate better decision-making in the management of academic research. This research method is systematic involving data acquisition, pre-processing, algorithm implementation, and evaluation. The results of this research show that integrating Chi-Square feature selection significantly improves K-Nearest Neighbors performance, achieving 86% precision, 84.3% recall, 89.2% F1 Score, and 93.3% accuracy. This research contributes to increasing the efficiency of the Archives and Research Publication Information System in managing research and academic publications.

Analisis Tren Luas Wilayah dan Produksi Kelapa Sawit di Provinsi Aceh: Studi Kuantitatif dan Prediktif Fadhilla, Cut Alna; Gunawan, Chichi Rizka; Sofia Amriza, Rona Nisa
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 1 (2025): April 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i1.23928

Palm oil is a strategic commodity that plays an important role in the economy of Aceh Province. This study aims to analyze the trend of changes in the area of oil palm plantations and their production results using quantitative data from recent years, as well as to predict palm oil production for the next five years. The methods used include descriptive statistical analysis to identify development patterns and predictive models based on time series forecasting to accurately estimate future trends. The results of the study show a significant increase in the area of land and oil palm production in several main districts, with Nagan Raya as the largest contributor. The prediction of harvest results for the next five years indicates a positive trend that can be used as a basis for planning the development of the plantation sector. These findings provide important information for policy makers and industry players in making strategic decisions to increase the productivity and sustainability of the oil palm business in Aceh Province. Keywords: Palm Oil Production, Area Analysis, Prediction Model

The Examination of the User Engagement Scale (UES) in Small Medium Enterprise Social Media Usage: A Survey-Based Quantitative Study Amriza, Rona Nisa Sofia; Khairun Nisa Meiah Ngafidin; Citra Wiguna
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.4926

Social networks have proven to be an essential marketing tool for the success of any product, service, or business. User participation affects the increase in revenue gain and creates long-term profit. The User Engagement Scale (UES) is one of the tools developed to measure user engagement and has been used in various digital domains. The UES intends to compute six dimensions of engagement: aesthetic appeal, perceived usability, focused attention, novelty, felt involvement, and endurability. This study investigates and verifies the three-factor structure of the UES. We used PCA to perform the analysis. The original data will be reanalyzed using UES, which consists of 220 valid responses. The result shows that the UES examination indicates good reliability in three factors. Factor 1 encompasses the feeling of involvement (FI), aesthetic appeal (AE), novelty (NO), and endurability (EN). Factor 2 aggregates the perceived usability (PU) elements. Factor 3 pertains to focused attention (FA) items. Our findings indicate that the User Engagement Scale is a valuable and suitable measurement tool for assessing user engagement in the context of social media within small and medium enterprises.

Accuracy of K-Nearest Neighbors Algorithm Classification For Archiving Research Publications Gunawan, Muhamad Nur; Farhanah, Titi; Masruroh, Siti Ummi; Jundulloh, Ahmad Mukhlis; Raushanfikar, Nafdik Zaydan; Amriza, Rona Nisa Sofia
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3915

The Archives and Research Publication Information System plays an important role in managing academic research and scientific publications efficiently. With the increasing volume of research and publications carried out each year by university researchers, the Research Archives and Publications Information System is essential for organizing and processing these materials. However, managing large amounts of data poses challenges, including the need to accurately classify a researcher's field of study. To overcome these challenges, this research focuses on implementing the K-Nearest Neighbors classification algorithm in the Archives and Research Publications Information System application. This research aims to improve the accuracy of classification systems and facilitate better decision-making in the management of academic research. This research method is systematic involving data acquisition, pre-processing, algorithm implementation, and evaluation. The results of this research show that integrating Chi-Square feature selection significantly improves K-Nearest Neighbors performance, achieving 86% precision, 84.3% recall, 89.2% F1 Score, and 93.3% accuracy. This research contributes to increasing the efficiency of the Archives and Research Publication Information System in managing research and academic publications.

The Impact of Personal, Environmental, and Information Platform Factors on Disaster Information Sharing on Twitter Amriza, Rona Nisa Sofia; Ngafidin, Khairun Nisa Meiah; Ratnasari, Wiwit
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8 No 2 (2022): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i2.2540

Twitter has become a major platform for disseminating disaster news, providing people with disaster information quickly and precisely. A lot of essential and valuable information can be obtained from this online platform. Twitter users might be able to help with warnings and submit specific and accurate information in a disaster situation. This research attempts to examine factors that affect disaster information-sharing behavior. Furthermore, this study aims to integrate personal, environmental, and information platform factors to gain more insight into the factors influencing Twitter users' willingness to share disaster information. The hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The result showed that Altruism, Self-efficacy, Community Identity, and Information Platforms significantly influence people's decisions to share disaster information on Twitter.

Title

Found 18 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 18 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 18 Documents
Search