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All Journal Jupiter Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Edukasi dan Penelitian Informatika (JEPIN) Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Sisfokom (Sistem Informasi dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JSiI (Jurnal Sistem Informasi) JISA (Jurnal Informatika dan Sains) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknologi Informasi dan Komunikasi IJCOSIN : Indonesian Journal of Community Service and Innovation
Rona Nisa Sofia Amriza
Universitas Telkom
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Social Sciences Other

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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

Abstract

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.
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

Abstract

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

Abstract

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.
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

Abstract

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.
The Classification of Anxiety, Depression, and Stress on Facebook Users Using the Support Vector Machine Wijiasih, Tsania Maulidia; Amriza, Rona Nisa Sofia; Prabowo, Dedy Agung
JISA(Jurnal Informatika dan Sains) Vol 5, No 1 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i1.1273

Abstract

Social media remains an essential platform for connecting people with friends, family, and the world around them. However, when events spread on social media are primarily negative, it will cause depression, anxiety, and stress that tend to increase. This study aims to classify depression, anxiety, and stress using the Support Vector Machine. The data in this study were obtained from active Facebook users using the Depression Anxiety Stress Scale (DASS 21) questionnaire. This study adopted the Knowledge Discover Database process. The result of this study is an evaluation of the performance of the Support Vector Machine classification of depression, anxiety, and stress. The accuracy of the Support Vector Machine in this study is 98.96%.
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 : Universitas Bumigora

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

Abstract

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.
Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Achmad Rizky Fambudianto Ahmad Mukhlis Jundulloh Artika Arista Citra Wiguna Darmansah Dedy Agung Prabowo Didi Supriyadi Dwi Januarita Dwi Januarita A.K Dwi Januarita Ardianing Kusuma Fadhilla, Cut Alna Fitriana, Rian Gunawan, Chichi Rizka Jonatan Maruli Butarbutar Khairun Nisa Meiah Ngafidin Logiandani Logiandani M Yoka Fathoni Maulana Wildan Rifaldi Mega Aprilia Fajriati Muhamad Nur Gunawan Nafdik Zaydan Raushanfikar Nurlaila, Ayu Annisa Nurul Fitriani Raihan Zidane Ramadhan Safhira Nanda Rahmadhani Sarah Astiti S.Kom., M.MT Sisilia Thya Safitri Siti Nur Amalia Siti Ummi Masruroh Titi Farhanah Wijiasih, Tsania Maulidia Wiwit Ratnasari Yogo Dwi Prasetyo