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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic JWP (Jurnal Wacana Politik) BACA: Jurnal Dokumentasi dan Informasi
Anne Parlina
Staf Perpustakaan BPPT
Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science Social Sciences

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DIGITAL REPRESENTATION OF WOMEN POLITICIANS IN INDONESIA: YOUTH PERSPECTIVES AND SELF-PORTRAYAL ON SOCIAL MEDIA Kusumarani, Riri; Majid, Darmawati; Parlina, Anne; Nugroho, Ari Cahyo
JWP (Jurnal Wacana Politik) Vol 10, No 2 (2025): JWP (Jurnal Wacana Politik) May
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jwp.v10i2.59148

Abstract

Less than 25% of seats in Indonesia’s House of Representatives are held by women politicians. While studies have explored the topic of women in Indonesian politics, this article adopts a unique approach by examining the use of social media as a political marketing tool by women politicians in Indonesia during the 2024 pre-presidential election period. Key questions include how women politicians are portrayed on social media, how they portray themselves, and how Indonesian youths perceive them. Possible mismatches between portrayals are also considered. This study specifically analyzes and maps the characteristics of social media posts from 36 women politicians across their platforms. With the growing involvement of young people in the political arena, understanding younger generations’ views on women politicians is crucial for comprehending social media’s impact on Indonesia’s democratic system. The findings contribute to the understanding of young people’s interest in politics, particularly concerning women in politics, and offer insights into the potential influence of social media on future elections in Indonesia.
ANALISIS SITIRAN JURNAL KEDOKTERAN PERGURUAN TINGGI (TRISAKTI, UNIVERSITAS MARANATHA, UKI ATMAJAYA) Parlina, Anne; Afandi, Sjaeful; Octavia, Rima
BACA: Jurnal Dokumentasi dan Informasi Vol. 33 No. 1 (2012): BACA: Jurnal Dokumentasi dan Informasi (Juni)
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.baca.v33i1.103

Abstract

Citation analysis is a branch of the study of bibliometrics, which analyzes the citation from various aspects. This study uses citation analysis method. The subject of this study is the bibliography of the articles from three health journal published in 2009. The journals are Universa Medicana, Jurnal Kedokteran Maranatha, and Majalah Kedokteran Damianus UKI Atmajaya. The research aims to find out the characteristics of cited literature, the author patterns and the network among health journals in Indonesia
PROTOTIPE MASHUP LAYANAN INFORMASI PUBLIK PERPUSTAKAAN BPPT Parlina, Anne; Ardiansyah, Firman; Budiarto, Hary
BACA: Jurnal Dokumentasi dan Informasi Vol. 35 No. 2 (2014): BACA: Jurnal Dokumentasi dan Informasi (Desember)
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.baca.v35i2.191

Abstract

The Agency for the Assessment and Application of Technology Library has the duty to provide public information services to the community. However, this public information was scattered in several different websites. In this study, mashup technology was used to collect and combine content from external sources. Information architectureand prototype of public information service mashup were designed and created. The result showed that mashup technology can be used to create a new service that easily community to find the public information without open many websites at the same time.
Optimizing Multi-Layer Perceptron Performance in Sentiment Classification through Neural Network Feature Extraction Alam, Muhammad Fikri; Nuryaman, Aang; Khotimah, Purnomo Husnul; Parlina, Anne; Sihombing, Andre
BACA: Jurnal Dokumentasi dan Informasi Vol. 46 No. 1 (2025): BACA: Jurnal Dokumentasi dan Informasi (Juni)
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/baca.2025.8240

Abstract

There are some problems with using the Multi-Layer Perceptron (MLP) model for complex tasks because it can be hard to understand hierarchical relationships and tends to overfit data with a lot of dimensions. This research proposes an enhanced MLP model for sentiment classification by integrating feature extraction layers from advanced neural networks, specifically the Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (Bi-LSTM). These layers aim to improve the model's representation capabilities by capturing more nuanced features. To evaluate the performance improvements of this augmented MLP model, metrics such as accuracy, precision, recall, F1-score, and the Area Under the Curve for Receiver Operating Characteristics (ROC-AUC) were employed. A key metric focus is the delta value, representing changes in the ROC-AUC, to assess the significance of these enhancements. The integration of CNN as a feature extraction layer yielded optimal ROC-AUC results, achieving values of 93.30% and 93.00%, which reflect an improvement of 0.51% and 4.46% over the baseline model. These findings indicate that adding feature extraction layers significantly enhances MLP performance in sentiment classification tasks. Future research may explore the potential of using alternative neural networks as feature extractors to continue advancing MLP capabilities in complex NLP applications.
Water Quality Measurement based on Internet of Thing Fajri, Misbahul; Jumaryadi, Yuwan; Parlina, Anne
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11642

Abstract

Good water quality is crucial for living things, including temperature, pH, and TDS, which are constantly changing due to various factors. These three water parameters are crucial for maintaining water quality within a certain threshold to ensure that an ecosystem meets specified standards. Measuring water quality is essential to anticipate these changes as desired. Internet of Things (IoT) technology allows continuous monitoring of water parameters at any time and can be accessed anywhere with a network connection via computer or smartphone. In this proposed research, an IoT-based system based on ESPHome will be developed for water quality measurement in aquarium water and its ecosystem. The proposed research detects, records, and displays water pH and TDS parameters, including temperature, using an ESP8266 microcontroller. The system utilizes sensors to detect water parameters; the system utilizes an ESP8266 microcontroller and a WiFi connection that sends data to a cloud-based server with a Homeassistant dashboard. The research results are well-functioning in both hardware and software and are easily accessible.
Co-Authors Aang Nuryaman Alam, Muhammad Fikri Ari Cahyo Nugroho Firman Ardiansyah Hary Budiarto Hary Budiarto Jumaryadi, Yuwan Khotimah, Purnomo Husnul Kusumarani, Riri Majid, Darmawati Misbahul Fajri Rima Octavia Sihombing, Andre Sjaeful Afandi