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Penerapan Psikoedukasi Nomophobia Terhadap Insight Siswa SDN Bojong 02 Kemang Bogor Dalam Penggunaan Gadget Tarisafitri, Nahla; Hilaliyah, Maimunah; Wahyudin, Aris; Azhari, Azhari; Ali, Ircham
PRAXIS: Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 1 (2024): PRAXIS Special Issue
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/praxis.v2i1.755

Abstract

Gadgets in various forms and functions have become a crucial part of life everyday Indonesian society. Over time, gadgets have become an integral part inseparable from their lives. The kids from before may be more familiar traditional games in the open air now tend to be more time consuming them with gadgets. However, behind the comfort and practicality offered by This technology has increasingly disturbing negative impacts, one of which is gadget addiction. Apart from that, gadgets also have a psychological impact, such as An anxiety disorder known as no mobile phone phobia or nomophobia. This activity took the form of psychoeducation which was carried out at SDN Bojong 02 Kemang Bogor. The method used is interactive lectures and discussions and is processed descriptively, with one group pretest and posttest as well as FGD. This psychoeducation aims to provide insight to students regarding the impact of excessive gadget use. The results of this research show that psychoeducation has influence and is capable increase insight into gadgets.
Sentiment Analysis in Indonesian’s Presidential Election 2024 Using Transfomer (Distilbert-Base-Uncased) Aljabar, Andi; Karomah, Binti Mamluatul; Tarisafitri, Nahla; Jeffry, Jeffry
Journal of System and Computer Engineering Vol 6 No 2 (2025): JSCE: April 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i2.1867

Abstract

Utilizing a transformer-based natural language processing model called DistilBERT-base-uncased, this study investigates the use of sentiment analysis in relation to Indonesia's 2024 presidential election. Particularly during political events, sentiment analysis is a potent tool for gaining insight into public opinion. The program divides public posts' sentiment into positive and negative categories by examining social media data (twitter). In order to assure consistency and correctness, the dataset used in the research has been carefully selected. DistilBERT is then used to train the model. The result shows from 19920 row of data only 4.47% of Indonesia’s citizen left positive comment.
Penerapan Psikoedukasi Nomophobia Terhadap Insight Siswa SDN Bojong 02 Kemang Bogor Dalam Penggunaan Gadget Tarisafitri, Nahla; Hilaliyah, Maimunah; Wahyudin, Aris; Azhari, Azhari; Ali, Ircham
PRAXIS: Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 1 (2024): PRAXIS Special Issue
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/praxis.v2i1.755

Abstract

Gadgets in various forms and functions have become a crucial part of life everyday Indonesian society. Over time, gadgets have become an integral part inseparable from their lives. The kids from before may be more familiar traditional games in the open air now tend to be more time consuming them with gadgets. However, behind the comfort and practicality offered by This technology has increasingly disturbing negative impacts, one of which is gadget addiction. Apart from that, gadgets also have a psychological impact, such as An anxiety disorder known as no mobile phone phobia or nomophobia. This activity took the form of psychoeducation which was carried out at SDN Bojong 02 Kemang Bogor. The method used is interactive lectures and discussions and is processed descriptively, with one group pretest and posttest as well as FGD. This psychoeducation aims to provide insight to students regarding the impact of excessive gadget use. The results of this research show that psychoeducation has influence and is capable increase insight into gadgets.
Classification of Skin Diseases using Digital Image Processing with MobileNetV2 Architecture Tarisafitri, Nahla; Aljabar, Andi
Nusantara Journal of Artificial Intelligence and Information Systems Vol. 1 No. 1 (2025): June
Publisher : Faculty of Engineering and Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/nuai.v1i1.1594

Abstract

Skin diseases are prevalent in tropical countries like Indonesia, where geographical and climatic conditions facilitate their spread. This research aims to classify skin diseases using digital image processing with the MobileNetV2 architecture. The DermNet dataset is used to develop and test the model. Various image preprocessing techniques, including resizing, augmentation, and normalization, were applied to the dataset, which consists of 300 images categorized into dermatitis, psoriasis, and scabies. The model achieved a training accuracy of 90% and a validation accuracy of 70%, with notable success in classifying psoriasis. The findings suggest that MobileNetV2, when combined with CNN, is a promising tool for diagnosing skin diseases early and efficiently.