Garuda - Garba Rujukan Digital

Pelatihan Aplikasi Untuk Industri Berbasis Arduino di SMK Letris Tangerang Selatan Elly, Muhamad Jafar; Emillia, Emillia; Husada, Hendrianto; Asri, Yessy; Hartanti, Dian; Sikumbang, Hengki; Kuswardani, Dwina
Jurnal SOLMA Vol 8 No 2 (2019): Jurnal Solma
Publisher : Uhamka Press

Seiring perkembangan teknologi informasi yang sangat cepat, teknologi mikrokontroler pun ikut berkembang pesat. Mikrokontroler digunakan di hampir semua perlengkapan elektronik rumah tangga dan industri. Salah satu mikrokontroler yang sangat popular yang banyak digunakan dalam pembuatan prototipe peralatan elektronik untuk aplikasi industri adalah arduino. Aplikasi arduino ini belum banyak dikenal masyarakat. Salah satu cara untuk mengenalkan peralatan elektronik yang menggunakan mikrokontroler ini adalah memberikan bimbingan dan pelatihan tentang arduino yang meliputi fungsi, blok diagram, pemrogramman dan implementasinya. Dalam kaitan itu, kegiatan Pengabdian Kepada Mayarakat dari STT PLN pun dilakukan. Kegiatan ini dimaksudkan untuk memberikan bimbingan dan penyuluhan mengenai Arduino dan implementasinya dalam industri terutama kepada para pelajar di Sekolah Menengah Kejuruan (SMK) Letris, Tangerang Selatan.

Using Gauss - Jordan elimination method with The Application of Android for Solving Linear Equations Hasanudin, Muhaimin; Kristiadi, Dedy Prasetya; Yuliana, Khozin; Tarmizi, Rasyid; Kuswardani, Dwina; Abdurrasyid, A
International Journal for Educational and Vocational Studies Vol 1, No 6 (2019): October 2019
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/ijevs.v1i6.1670

Problems involving mathematical models appear in many scientific disciplines. Complex mathematical models sometimes cannot be solved by analytic methods using standard algebraic formulas. Computers play a major role in the development of the field of numerical methods because the calculation uses numerical methods in the form of arithmetic operations, the number of arithmetic operations is very large and repetitive, so manual calculations are often tedious and errors occur. This study aims to develop software solutions for linear equations by implementing the Gauss-Jordan elimination(GJ-elimination) method, building software for linear equations carried out through five stages, namely: (1) System Modeling (2) Simplification of Models, (3) Numerical Methods and algorithms, (4) programming languages using The Android Studio and (5) Simulation programs. Overall regarding content, proper software that can be used by students and lecturers in implementing numerical methods because there are ways to use the application and steps to solve linear equation problems using the GJ-elimination method.

Sentiment analysis based on Indonesian language lexicon and IndoBERT on user reviews PLN mobile application Asri, Yessy; Kuswardani, Dwina; Suliyanti, Widya Nita; Manullang, Yosef Owen; Ansyari, Atikah Rifdah
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp677-688

PLN mobile application as an integrated platform for self-service among mobile consumers, facilitating easier access to various services, including receiving information such as public complaints. The application can be downloaded through the Google Play Store and App Store, and users can express their opinions through reviews and ratings. In this era of advanced technology, aspects such as reviews, ratings, and evaluations have important value for business practitioners. However, there are often inconsistencies between ratings and reviews that do not fully represent the quality of the application. In response, a study was conducted to analyze the sentiment of user reviews from January to June 2022, by collecting 1,000 review samples from the Google Play Store. The data was collected using web scraping techniques and then processed into a dataset through text pre-processing methods. Sentiments were analyzed using an automatic labeling method in Indonesian based on a lexicon known as INSET (Indonesia sentiment), which resulted in 482 positive reviews, 144 negative reviews, and 374 neutral reviews. The next step is classification using Indonesian bidirectional encoder representations from transformers (IndoBERT). In this process, the data was divided into testing, training, and validation sets with a ratio of 80:10:10. The analysis managed to achieve an impressive accuracy rate of 81%.

Word embedding for contextual similarity using cosine similarity Asri, Yessy; Kuswardani, Dwina; Sari, Amanda Atika; Ansyari, Atikah Rifdah
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp1170-1180

Perspectives on technology often have similarities in certain contexts, such as information systems and informatics engineering. The source of opinion data comes from the Quora application, with a retrieval limit of the last 5 years. This research aims to implement Indo-bidirectional encoder representations from transformers (BERT), a variant of the BERT model optimized for Indonesian language, in the context of information system (IS) and information technology (IT) topic classification with 414 original data, which, after being augmented using the synonym replacement method, The generated data becomes 828. Data augmentation aims to evaluate the performance of models by using synonyms and rearranging text while maintaining meaning and structure. The approach used is to label the opinion text based on the cosine similarity calculation of the embedding token from the IndoBERT model. Then, the IndoBERT model is applied to classify the reviews. The experimental results show that the approach of using IndoBERT to classify SI and IT topics based on contextual similarity achieves 90% accuracy based on the confusion matrix. These positive results show the great potential of using transformer-based language models, such as IndoBERT, to support the analysis of comments and related topics in Indonesian.

Meningkatkan Performa Ulasan Berbahasa Indonesia dengan Spelling Corrector Peter Norvig dan Pelabelan SentiStrength_id Asri, Yessy; Kuswardani, Dwina; Ferdinanda Purba TS, Josephine
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp92-98

Digital transformation is driven by the increasing number of internet and mobile phone users in Indonesia, including public services such as the PLN Mobile application. The purpose of this study is to evaluate user sentiment towards PLN Mobile application reviews and find gaps between user ratings and reviews. Through web scraping on Google Play Store, with a total review data of 11,004 reviews between January 2022 and December 2023. During the preprocessing step, SentiStrength_id was used as the labeling approach, and Support Vector Machine was used for modeling. A spelling corrector using Peter Norvig was applied to correct spelling issues. The accuracy of sentiment analysis was much better with this procedure, reaching 82% at a data split ratio of 90:10. The percentage of sentiment obtained was 16.5% negative, 16.1% neutral, and 67.4% positive. The percentage of mismatched user ratings and reviews was 23.1% for negative reviews, 4.5% for neutral, and 72.49% for positive reviews.

Using Gauss - Jordan elimination method with The Application of Android for Solving Linear Equations Hasanudin, Muhaimin; Kristiadi, Dedy Prasetya; Yuliana, Khozin; Tarmizi, Rasyid; Kuswardani, Dwina; Abdurrasyid, A
International Journal for Educational and Vocational Studies Vol. 1 No. 6 (2019): October 2019
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/ijevs.v1i6.1670

Problems involving mathematical models appear in many scientific disciplines. Complex mathematical models sometimes cannot be solved by analytic methods using standard algebraic formulas. Computers play a major role in the development of the field of numerical methods because the calculation uses numerical methods in the form of arithmetic operations, the number of arithmetic operations is very large and repetitive, so manual calculations are often tedious and errors occur. This study aims to develop software solutions for linear equations by implementing the Gauss-Jordan elimination(GJ-elimination) method, building software for linear equations carried out through five stages, namely: (1) System Modeling (2) Simplification of Models, (3) Numerical Methods and algorithms, (4) programming languages using The Android Studio and (5) Simulation programs. Overall regarding content, proper software that can be used by students and lecturers in implementing numerical methods because there are ways to use the application and steps to solve linear equation problems using the GJ-elimination method.

Meningkatkan Performa Ulasan Berbahasa Indonesia dengan Spelling Corrector Peter Norvig dan Pelabelan SentiStrength_id Asri, Yessy; Kuswardani, Dwina; Ferdinanda Purba TS, Josephine
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp92-98

Digital transformation is driven by the increasing number of internet and mobile phone users in Indonesia, including public services such as the PLN Mobile application. The purpose of this study is to evaluate user sentiment towards PLN Mobile application reviews and find gaps between user ratings and reviews. Through web scraping on Google Play Store, with a total review data of 11,004 reviews between January 2022 and December 2023. During the preprocessing step, SentiStrength_id was used as the labeling approach, and Support Vector Machine was used for modeling. A spelling corrector using Peter Norvig was applied to correct spelling issues. The accuracy of sentiment analysis was much better with this procedure, reaching 82% at a data split ratio of 90:10. The percentage of sentiment obtained was 16.5% negative, 16.1% neutral, and 67.4% positive. The percentage of mismatched user ratings and reviews was 23.1% for negative reviews, 4.5% for neutral, and 72.49% for positive reviews.

Title

Found 7 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 7 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 7 Documents
Search