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All Journal Jurnal Pekommas Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Gambetta, Windy
Institut Teknologi Bandung
Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media

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Data Growth Identification and Application Performance Index (APDEX) Evaluation on the Performance of Geospatial Information Mapping Applications Florence Elfriede Sinthauli Silalahi; Mugi Prayitno; Windy Gambetta; Fahmi Amhar; Tia Rizka Nuzula Rachma; Muhammad Nur Qomari Adi Wijaya
Jurnal Pekommas Vol 6, No 1 (2021): April 2021
Publisher : BBPSDMP KOMINFO MAKASSAR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2021.2060110

Abstract

The Awareness for managing information technology (IT) as the responsibility of various parties has emerged, supported by improving in the quality of the Electronic Based Government System (SPBE), made IT cannot be considered as support only, but its strategic function is going started to be reviewed. This aims to realize the availability of data that is accurate, up-to-date, integrated, accountable, and easily accessible and shared by the public. Geospatial data and information (IG) are strategic because they are included in the implementation of the Presidential Decree One Data Indonesia together with statistical and financial data. GI that is generated and reprocessed from service systems and equipment sensors, requires operational management support, performance, and ease of addition, as well as interoperability with other systems. It is necessary to measure user satisfaction with GI services, namely in nine mapping applications, using the Application Performance Index (APDEX) Score using JMeter, identifying user behavior with Google Analytics, and recommending application performance improvements from the GT Metrix test results. From the results, the total number of application users is quite high. The APDEX score results show a range of 0.516 to 0.945, so improvements are needed for scripts, server utilization (CPU, memory, and storage), and available bandwidth. Furthermore, it is necessary to use a CDN or proxy to cache js, CSS scripts, and base maps (images), as well as optimize according to the recommendations of GT Metrix. 
Data Growth Identification and Application Performance Index (APDEX) Evaluation on the Performance of Geospatial Information Mapping Applications Silalahi, Florence Elfriede Sinthauli; Prayitno, Mugi; Gambetta, Windy; Amhar, Fahmi; Rachma, Tia Rizka Nuzula; Wijaya, Muhammad Nur Qomari Adi
Jurnal Pekommas Vol 6 No 1 (2021): April 2021
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jpkm.v6i1.3756

Abstract

The Awareness for managing information technology (IT) as the responsibility of various parties has emerged, supported by improving in the quality of the Electronic Based Government System (SPBE), made IT cannot be considered as support only, but its strategic function is going started to be reviewed. This aims to realize the availability of data that is accurate, up-to-date, integrated, accountable, and easily accessible and shared by the public. Geospatial data and information (IG) are strategic because they are included in the implementation of the Presidential Decree One Data Indonesia together with statistical and financial data. GI that is generated and reprocessed from service systems and equipment sensors, requires operational management support, performance, and ease of addition, as well as interoperability with other systems. It is necessary to measure user satisfaction with GI services, namely in nine mapping applications, using the Application Performance Index (APDEX) Score using JMeter, identifying user behavior with Google Analytics, and recommending application performance improvements from the GT Metrix test results. From the results, the total number of application users is quite high. The APDEX score results show a range of 0.516 to 0.945, so improvements are needed for scripts, server utilization (CPU, memory, and storage), and available bandwidth. Furthermore, it is necessary to use a CDN or proxy to cache js, CSS scripts, and base maps (images), as well as optimize according to the recommendations of GT Metrix. 
Pengaruh Augmentasi Data Back-Translation terhadap Kinerja Analisis Sentimen dalam Bahasa Indonesia Jusuf Junior Athala; Windy Gambetta
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Sentiment analysis is a field of natural language processing (NLP) that aims to classify emotions or opinions contained in a text. When training a machine learning model for sentiment analysis, a problem commonly encountered is imbalanced datasets or datasets with uneven class distributions. This study investigates Back Translation’s effect on improving machine learning performance using an imbalanced dataset. The imbalanced dataset to be used is the NusaX Sentiment Analysis dataset. Experiment results show that Support Vector Machine (SVM) models give notable improvement in scores, especially with Back Translation using Javanese as the intermediate language, which provides the best F1 macro score improvement of 1.89% and the best F1 weighted score improvement of 1.52%. On the other hand, Naive Bayes models do not show any notable improvements. The findings indicate Back Translation can adjust class distribution and can boost certain models' sentiment analysis accuracy.
Co-Authors Fahmi Amhar Fahmi Amhar Florence Elfriede Sinthauli Silalahi Jusuf Junior Athala Mugi Prayitno Muhammad Nur Qomari Adi Wijaya Prayitno, Mugi Rachma, Tia Rizka Nuzula Silalahi, Florence Elfriede Sinthauli Tia Rizka Nuzula Rachma Wijaya, Muhammad Nur Qomari Adi