Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Fokus Ekonomi Prosiding Seminar Nasional Official Statistics
Rimawati, Yeni
Unknown Affiliation
Humanities Computer Science & IT Economics, Econometrics & Finance Engineering Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Penerapan Data Pipeline untuk Meningkatkan Efisiensi Penghitungan Indeks Perkembangan Harga (IPH) di Indonesia Sandyawan, Ignatius; Rimawati, Yeni; Suarjaya, I Made Oka
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2045

Abstract

The Price Change Index (PCI) is an indicator for monitor market price fluctuations. In 2022, Statistics Indonesia (BPS), worked with Ministry of Home Affairs (Kemendagri) as data steward and the Ministry of Trade (Kemendag) as a data collector, to calculate the PCI for 20 primary commodities across all cities in Indonesia. Weekly price data was collected by city trade departments and transferred to BPS for processing. Until late 2023, this process, done in Microsoft Excel, could take up to three days and was prone to errors. This research focuses on implementing a data pipeline for PCI calculations, automating tasks like data cleaning, index calculation, and visualization. Results showed the data pipeline reduced calculation time to just 16 minutes while maintaining consistency with manually obtained PCI values. The implementation has significantly improved time efficiency, minimized errors, and optimized resource use.
EMPLOYEE PERFORMANCE REVIEWED FROM LEADERSHIP STYLE, ORGANIZATIONAL CULTURE, WORK MOTIVATION AND WORK DISCIPLINE AT THE REGIONAL SECRETARIAT OF KLATEN REGENCY Rimawati, Yeni; Sarsono, Sarsono; DPW, Ida Aryati
Fokus Ekonomi : Jurnal Ilmiah Ekonomi Vol 20, No 1 (2025): June 2025
Publisher : STIE Pelita Nusantara Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34152/fe.20.1.41-48

Abstract

The study was conducted to determine the effect of leadership style, organizational culture, work discipline and work motivation on the performance of ASN of the Klaten Regency Regional Secretariat. This type of research is quantitative research. This research was conducted at the Klaten Regency Regional Secretariat and the research time was carried out from March to December 2024. This research was conducted on 80 employees at the Klaten Regency Regional Secretariat. The sampling technique used in this study was the census technique so that the sample numbered 80 people. The data in this study were processed using multiple linear regression analysis tools with the help of SPSS software. Based on the results of hypothesis testing and the discussion that has been carried out, it can be concluded as follows: Leadership style, organizational culture, work discipline, work motivation have a positive and significant effect on the performance of employees of the Klaten Regency Regional Secretariat. This means that the variables of leadership style, organizational culture, work discipline and work motivation contribute to ASN performance by 43.4% while the remaining 56.6% is explained by other variables.
Automatic Classification of Multilanguage Scientific Papers to the Sustainable Development Goals Using Transfer Learning Suadaa, Lya Hulliyyatus; Monika, Anugerah Karta; Putri, Berliana Sugiarti; Rimawati, Yeni
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6560

Abstract

The classification of scientific papers according to their relevance to Sustainable Development Goals (SDGs) is a critical task in identifying the research development status of goals. However, with the growing volume of scientific literature published worldwide in multiple languages, manual categorization of these papers has become increasingly complex and time-consuming. Furthermore, the need for a comprehensive multilingual dataset to train effective models complicates the task, as obtaining such datasets for various languages is resource intensive. This study proposes a solution to this problem by leveraging transfer learning techniques to automatically classify scientific papers into SDG labels. By fine-tuning pretrained multilingual models mBERT on SDG publication datasets in a multilabel approach, we demonstrate that transfer learning can significantly improve classification performance, even with limited labelled data, compared to SVM. Our approach enables the effective processing of scientific papers in different languages and facilitates the seamless mapping of research to the relevance of SDGs, the four pillars of SDGs, and the 17 goals of SDGs. The proposed method addresses the scalability issue in SDG classification and lays the groundwork for more efficient systems that can handle the multilingual nature of modern scientific publications.
Co-Authors DPW, Ida Aryati Monika, Anugerah Karta Putri, Berliana Sugiarti Sandyawan, Ignatius Sarsono Sarsono Suadaa, Lya Hulliyyatus Suarjaya, I Made Oka