Article Per Year (5 Year)
p-Index From 2020 - 2025
1.259
P-Index
This Author published in this journals
All Journal Scientific Journal of Informatics Journal of Soft Computing Exploration Jurnal Pengabdian kepada Masyarakat Indonesia (JPKMI) Journal of Information System Exploration and Research Recursive Journal of Informatics Journal of Advances in Information Systems and Technology
Efrilianda, Devi Ajeng
Unknown Affiliation
Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Library & Information Science Nursing Physics Public Health

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
Business Process re-engineering to support the sustainability of the construction industry and sales commodities in large scale transaction during Covid 19 with integrating ERP and Quotation System Budiman, Kholiq; Subhan, Subhan; Efrilianda, Devi Ajeng
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.27969

Abstract

Covid 19 has become a pandemic that has hit all over the world. Almost all sectors are affected by this pandemic, not only in the health sector. The economic and industrial sectors have also suffered severe impacts due to the coronavirus pandemic. This spreading virus does not support economic growth either nationally or globally. Finally, it has an impact on various industrial sectors in the country, from manufacturing to finance. The industry was one of the largest contributors to Indonesia's Gross Domestic Product (GDP) last year. The contribution given from this industry to the 2019 GDP was recorded at 19.62%. Due to this pandemic, according to the Central Statistics Agency (BPS), during February 2020, the importance of all categories of goods decreased compared to January 2020. This stunted industrial development was due to the government's appeal for social distancing; social distancing made it difficult for industry players to make transactions. Several obstacles require re-engineering of business processes in the industry. In general, the industry already has an Enterprise Resource Planning (ERP) system used in the related production process. However, ERP does not enter into the realm of buying and selling or the process of procuring goods with consumers. Therefore we need a Business Process Reengineering as an engineering process to integrate the ERP and the bidding system or quotation system. Using the moving average method as a forecasting method, we can get sustainable sales even during the Covid period, even seen an increase in transactions in the new period, along with the implementation of the quotation information system applied in the re-engineering business process.
Business Process Re-engineering to Support Sustainability of The Sales Commodities in Large Transaction with Quotation System Budiman, Kholiq; Subhan, Subhan; Efrilianda, Devi Ajeng
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.27969

Abstract

Purpose: COVID-19 pandemic has an impact in almost all sectors, including economic and industrial sectors. The aim of this research is to support the sustainability of the sales commodities in large transactions due to pandemic conditions by business process re-engineering. Methods: Using the moving average method as a forecasting method. Result: It can get sustainable sales even during the COVID period, even seen an increase in transactions in the new period, along with the implementation of the quotation information system applied in the re-engineering business process. Novelty: Business Process Reengineering as an engineering process to integrate the ERP and the bidding system or quotation system is needed.
Pelatihan Digitalisasi Modul Ajar Kurikulum Merdeka bagi Guru SMP Negeri 2 Tulung Ardiansyah, Adi Satrio; Dewi, Nuriana Rachmani; Junaedi, Iwan; Efrilianda, Devi Ajeng; Mulyono, Mulyono; Astuti, Clara Rosita Hani Yuli; Erlita, Dea; Hasaroh, Elsa Fadila
Jurnal Pengabdian kepada Masyarakat Indonesia (JPKMI) Vol. 3 No. 3 (2023): Desember : Jurnal Pengabdian Kepada Masyarakat Indonesia (JPKMI)
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jpkmi.v3i3.2177

Abstract

Technological developments and changes in the curriculum are challenges for teachers to overcome. Presenting digitalized learning and digitalized learning tools is a necessity that needs to be prepared well. A training program that focuses on strengthening teacher literacy and competency in developing digitalized Modul Ajar in Kurikulum Merdeka is the aim of this community service activity. Modul Ajar in Kurikulum Merdeka itself is one of the key learning tools in the learning process, so it needs to be developed well. Systematically, teachers have been given training ranging from socialization activities, demonstrations, mentoring, to evaluation design so that teacher literacy and competence develops. With this activity, not only does teacher literacy and competence develop, but the learning process becomes better quality so that students' learning outcomes can increase.
Machine Learning Model Using Extreme Gradient Boosting (XGBoost) Feature Importance and Light Gradient Boosting Machine (LightGBM) to Improve Accurate Prediction of Bankruptcy Syafei, Risma Moulidya; Efrilianda, Devi Ajeng
Recursive Journal of Informatics Vol 1 No 2 (2023): September 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v1i2.71229

Abstract

Abstract. Humans have limitations in processing and analyzing large amounts of data in a short time, including in terms of analyzing bankruptcy data. Bankruptcy data is one of the data that has complex information, so it requires technology that can assist in the process of analyzing and processing data more quickly and efficiently. Data science technology enables data processing and analysis on a large scale, using parallel processing techniques. Parallel processing can be implemented in machine learning models. Purpose: Using parallel processing techniques, data science technologies enable data processing and analysis at scale. Parallel processing can be implemented in machine learning models. Therefore, this study aims to implement a machine learning model using the Light Gradient Boosting Machine (LightGBM) classification algorithm which is optimized using Extreme Gradient Boosting (XGBoost) Feature Importance to increase the accuracy of bankruptcy prediction. Methods/Study design/approach: Bankruptcy prediction is carried out by applying LightGBM as a classification model and optimized using the XGBoost algorithm as a Feature Importance technique to improve model accuracy. the dataset used is the Taiwanese Bankruptcy dataset collected from the Taiwan Economic Journal for 1999 to 2009 and has 6,819 data. Taiwanese Bankruptcy is unbalanced data, so this study applies random oversampling. Result/Findings: The results obtained after going through the model testing process using the confusion matrix obtained an accuracy of the performance of LightGBM+XGBoost Feature Importance of 99.227%. Novelty/Originality/Value: So it can be concluded that the implementation of XGBoost Feature Importance can be used to improve LightGBM's performance in bankruptcy prediction.
Analysis of twitter sentiment in COVID-19 era using fuzzy logic method Efrilianda, Devi Ajeng; Dianti, Erika Noor; Khoirunnisa, Oktaria Gina
Journal of Soft Computing Exploration Vol. 2 No. 1 (2021): March 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i1.12

Abstract

The sentiment is an assessment of attitudes towards certain events or things. Collecting opinion is known as a sentiment from existing data. This technique can also help analyze the opinions given by people in assessing certain objects. The best available source for gathering sentiment is the internet. In the era of the Covid-19 pandemic, many people access social media, especially Twitter to give their opinion on certain objects. Twitter is known as the social media that is accessed by users to post their opinions online. By using soft computing, especially fuzzy logic, it is possible to design, create and build bots that can analyze user opinions on Twitter. This model is used for data sentiment analysis on Twitter.
Operational Supply Chain Risk Management on Apparel Industry Based on Supply Chain Operation Reference (SCOR) Pertiwi, Dwika Ananda Agustina; Yusuf, Muhammad; Efrilianda, Devi Ajeng
Journal of Information System Exploration and Research Vol. 1 No. 1 (2023): January 2023
Publisher : shmpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joiser.v1i1.103

Abstract

The occurrence of uncertainty requires proper handling to avoid the adverse effects called risk. Risk tends to arise in the supply chain process called supply chain risk. The purpose of this research is to identify the possible level of risk that occurs and has the potential to disrupt supply chain activities, determine priority risk sources based on Supply Chain Operation References (SCOR). The object of this research is the apparel industry, which is a company engaged in fashion and apparel production. This study uses a qualitative and quantitative approach, the value of the instrument is assessed based on the results of the Aggregate Risk Potential (ARP) calculation in the House of Risk method phase 1.  The results showed that there were 39 correlations between risk events and risk agents, with 22 correlations with a high scale and 1 correlation with a low scale, and 15 correlations on a medium scale.
Analysis of User Readiness and Acceptance of SeaBank Indonesia Using the Technology Readiness and Acceptance Model (TRAM) Approach Ramadhan, Hibban Daffa; Efrilianda, Devi Ajeng
Journal of Advances in Information Systems and Technology Vol. 7 No. 1 (2025): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v7i1.15423

Abstract

The financial sector has been significantly impacted by informationtechnology, with digital banks emerging to provide services throughdigital platforms. SeaBank Indonesia, a digital bank, offers convenienceslike online account opening, free interbank transfers, and various digitalpayment options. However, some users have reported issues with theapplication, such as login problems and slow processing times.Additionally, some conventional customers remain hesitant to adoptdigital banking due to inexperience and security concerns. This studyaims to explore factors influencing users' adoption of SeaBank Indonesiaby applying the Technology Readiness and Acceptance Model (TRAM).Using a quantitative approach with purposive sampling, the researchcollected 421 valid responses from SeaBank Indonesia users throughonline questionnaires. Data analysis employed partial least squaresstructural equation modeling (PLS-SEM). The results accepted 8 out of12 hypotheses, revealing that intention to use is directly influenced byperceived usefulness, perceived ease of use, and perceived security.Perceived usefulness is directly affected by optimism, innovativeness,and perceived ease of use, while perceived ease of use is directlyinfluenced by optimism and innovativeness. These findings provideinsights into the factors driving digital banking adoption in Indonesia,highlighting the importance of user-friendly interfaces, perceivedsecurity, and technological readiness in shaping users' intentions to usedigital banking applications like SeaBank Indonesia.
Co-Authors Ali Djamhuri Astuti, Clara Rosita Hani Yuli Budiman, Kholiq Dewi, Nuriana Rachmani Dianti, Erika Noor Erlita, Dea Hasaroh, Elsa Fadila Iwan junaedi Khoirunnisa, Oktaria Gina Muhammad Yusuf Mulyono Mulyono Pertiwi, Dwika Ananda Agustina Ramadhan, Hibban Daffa Satrio Ardiansyah, Adi Syafei, Risma Moulidya