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All Journal Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Emerging Information Science and Technology Jurnal Nasional Teknik Elektro dan Teknologi Informasi jabdimasunipem
Nisrina Akbar Rizky Putri
Universitas Muhammadiyah Klaten
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Data Benchmark pada Google BigQuery dan Elasticsearch Nisrina Akbar Rizky Putri; Widyawan; Teguh Bharata Adji
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 3: Agustus 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1334.058 KB) | DOI: 10.22146/jnteti.v10i3.1745

Abstract

Nowadays,the cloud is not only a data storage medium but can be used as a medium for managing or analyzing data. Google offers Google BigQueryas a platform capable of managing and analyzing data,while Elasticsearch itself is a search and analysis engine that can be used to analyze data using Kibana. Using a dataset in the form of tweets crawled through http://netlytic.org/,containing the hashtags #COVID19 and #coronavirus, the data will be analyzed and used to compare its performance with benchmarks. Benchmark is a process used to measure and compare performance against an activity so that the desired level of performance is achieved. Data benchmark is performed on both platforms to generate or determine the workload of the platforms. The result obtained in this study is that Google BigQueryhas superior results, both from the upload container for larger datasets than Elasticsearch and with two query testing models.The query management time on Google BigQueryis also shorter and faster than Elasticsearch. Meanwhile, the visualization results from these two platforms have the same percentage amount.
Designing a Payroll System Database for Staff of the Informatics Engineering Department of Universitas Muhammadiyah Yogyakarta Nisrina Akbar Rizky Putri; Slamet Riyadi; Aprilia Kurnianti
Emerging Information Science and Technology Vol 1, No 3: August 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1253.364 KB) | DOI: 10.18196/eist.v1i3.13157

Abstract

The development of a staff payroll system aims to create a system that can help an administrator recapitulate attendance and payroll data of Informatics Engineering (IE) Department staff quickly and accurately. Such a development requires a database. The database design is divided into four stages: requirement collection and analysis, conceptual database design, logical database design, and physical database design. Design testing was performed on the database by testing the access policies, anomaly check, and view check. The results reveal that the proposed system worked well did not encounter anomalies.
Analisa Sentimen Masyarakat Terhadap Kebijakan Vaksinasi Covid-19 Di Indonesia Pada Twitter Menggunakan Algoritma LSTM La Laila Marifatul Azizah; Dimas Bagas Ajipratama; Nisrina Akbar Rizky Putri; Cahya Damarjati
IPTEK-KOM : Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi Vol 24 No 2 (2022): Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi)
Publisher : BPSDMP KOMNFO Yogyakarta, Kementerian Komunikasi dan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17933/iptekkom.24.2.2022.161-172

Abstract

Indonesia was shocked by the emergence of the first case of Covid-19 in March 2020. The Covid-19 virus can be fought with herd immunity, namely by vaccinating. On December 16, 2020, President Joko Widodo announced that he would provide the Covid-19 vaccine to the people of Indonesia. The information received various responses from the public. One of them through twitter. There are opinions that support and there are also those who reject vaccination. To find out the opinion of public sentiment regarding vaccination, a sentiment analysis process is carried out using an algorithm that aims to assist the sentiment analysis process with quite a lot of data. In this study, the sentiment analysis process uses one of the deep learning methods, namely LSTM (Long Short-Term Memory). The results of this study tend to support the vaccination program by producing 79% positive tweets, 13% neutral tweets and 8% negative tweets and getting a model accuracy of 71% using parameters of 15 epochs, 64 batch sizes and a comparison of training data and test data of 9:1 ​​(3600:400).
Analisis sentimen terhadap pelayanan Kesehatan berdasarkan ulasan Google Maps menggunakan BERT Ardiansyah; Adika Sri Widagdo; Krisna Nuresa Qodri; Fachruddin Edi Nugroho Saputro; Nisrina Akbar Rizky P
JURNAL FASILKOM Vol 13 No 02 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i02.5170

Abstract

The utilization of technology has developed in various scientific fields, without exception in health. Hospitals, health centers, and clinics are part of the health sector. Thus, it must evolve according to health service standards and patient measures or service user satisfaction that needs to be measured using sentiment analysis. The Media to give opinions to Health service providers is Google Maps. However, the anomaly is that the reviews and the given text are sometimes not correlated. Thus, The utilization of sentiment analysis using the scientific branch of artificial intelligence, namely Natural Language Processing (NLP), is an effective way to infer opinions. The research concluded that the BERT indobenchmark/indobert-base-p1 model has good performance to use of Indonesian text classification with a dataset of 4228 data after preprocessing, which at the beginning of the collection process obtained data as much as 4748 data. Split datasets into 3 data, namely training, validation, and test data, with a ratio of 70:30:30. The experimental results, The researchers found that the model allows the use of the model with other Indonesian texts. The results are 0.85 for accuracy and weighted avg, and macro avg 0.75 on the validation data training process. While the testing data training process is 0.86 for accuracy and weighted avg, the macro avg 0.73. In addition, researchers found that services are the most frequent topic in Health Services. Even though health services have improved, positive sentiment is the highest compared to other sentiment classes.
PELATIHAN DIGITAL MARKETING UNTUK MENINGKATKAN KINERJA PELAYANAN HAPUS TATO PRO CARE Fachruddin Edi Nugroho Saputro; Adika Sri Widagdo; Ardiansyah; Habib Ismail; Krisna Nuresa Qodri; Nisrina Akbar Rizky Putri
Jurnal Abdimas Universitas Insan Pembangunan Indoneisa Vol. 2 No. 1 (2024): Abdimas Unipem
Publisher : LPPM Universitas Insan Pembangunan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/jabdimasunipem.v2i1.21

Abstract

Promotion is an activity that aims to inform, influence, and influence consumer attitudesand behavior so that they are interested in and buy the products or services offered. In itsapplication, promotion has many methods including direct promotion or calledconventional promotion. Conventional promotion refers to promotion methods orstrategies that have long been used before the digital era or have not utilized informationtechnology. Promotion by utilizing information technology also known as digital marketingis an innovation in the marketing process promotional activities that involve the use oftechnology and digital platforms to achieve marketing goals to expand and enhancetraditional marketing functions.‘Hapus Tato Pro Care’ have constraints that have notmaximized the use of information technology in the promotion of tattoo removal servicesand the limited reach of targeting in the promotion of tattoo removal services. Byconducting training and being guided in creating content that will be used as promotionalmedia. In addition, participants will be guided to create captions and keywords used onsocial media to attract the attention of other social media users, participants gain skills inmanaging social media and doing graphic design better.
Analisis Sentimen Mobil Listrik di Indonesia Menggunakan Long-Short Term Memory (LSTM) Adika Sri Widagdo; Ardiansyah; Krisna Nuresa Qodri; Fachruddin Edi Nugroho Saputro; Nisrina Akbar Rizky Putri
JURNAL FASILKOM Vol 13 No 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6303

Abstract

Vehicles using fuel oil that is converted into mechanical energy were introduced in 1891 by John W. Lambert in America. But with this, the level of air pollution caused by exhaust emissions has become a problem today, until environmentally friendly engine innovations appear. The beginning of the development of these innovations was marked by hybrid technology cars. This technology has not completely abandoned the use of oil as fuel. In general, these vehicles are known as HEV or Hybrid Electic Vehicles. Then came a car that was entirely with an electric motor drive or EV or Electric Vehicle. Although the technology is considered environmentally friendly, on the other hand it does not make all elements of society accept any changes, especially in fuel oil engines to electric motors. With these changes, there are pros and cons that are the focus of researchers by utilizing sentiment analysis which is a Natural Language Processing (NLP) scientific family to analyze what aspects make society pro or con to the emergence of environmentally friendly vehicles. Data collection in this study took from YouTube comments in the form of Indonesian text data carried out using Python programming language and Long-Short Term Memory (LSTM) as an algorithm for analyzing public opinion. The dataset was divided into training data and test data with a ratio of 67:33, The results showed that the model can be used on Indonesian text data well. Then for the process of accuracy test data 63%, then macro avg precision 62%, macro avg recall 60%, macro avg f1-score 60%, weighted avg precision 62%, weighted avg recall 63%, weighted avg f1-score 62%, roc_auc 81%. In this study, it can also be seen that the topic of discussion that often arises, namely prices in all classes. However, negative sentiment is more than other sentiment classes, one of which is due to electric car manufacturers so it is very necessary to pay attention to stakeholders regarding prices that are suitable for the Indonesian market.
Co-Authors Adika Sri Widagdo Aprilia Kurnianti Ardiansyah Ardiansyah Azizah, Laila Marifatul Cahya Damarjati Dimas Bagas Ajipratama Fachruddin Edi Nugroho Saputro Habib Ismail Krisna Nuresa Qodri Slamet Riyadi Teguh Bharata Adji Widyawan