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Implementasi Augmented Reality Sebagai Media Interaktif Edukasi Anak Untuk Peningkatan Kognitif Hidayani, Nur; Rosyidah, Ulya Anisatur; Abdurrahman, Ginanjar
Journal of Digital Literacy and Volunteering Vol. 2 No. 2 (2024): July
Publisher : Puslitbang Akademi Relawan TIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57119/litdig.v2i2.82

Abstract

In the world of education, especially in kindergarten education, there is a problem with the use of technology, namely excessive dependence on gadgets. The solution provided for this problem is Augmented Reality-based learning using the markerbased method. This application provides an innovative and interactive experience through 2-dimensional and 3-dimensional displays as well as visual and audio displays. The research method used a literature study involving lecturers from the Faculty of Teacher Training and Education in order to validate a questionnaire for usability testing which was specifically conceptualized for the purpose of increasing cognitive understanding in kindergarten children. The research results showed that the educational interactive media application for kindergarten children with the aim of increasing cognitive understanding in the HICIHAA application showed an increase of 17.09% in the aspect of cognitive understanding.
Implementasi Metode Importance Performance Analysis (IPA) Untuk Pengukuran Indeks Kepuasan Masyarakat (IKM) Terhadap Pelayanan Administrasi di Desa Klatakan Asror, Moh. Miftahul; Rosyidah, Ulya Anisatur; Daryanto, Daryanto
Journal of Digital Literacy and Volunteering Vol. 2 No. 2 (2024): July
Publisher : Puslitbang Akademi Relawan TIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57119/litdig.v2i2.90

Abstract

Klatakan village of Kendit district in Situbondo district is one of the villages that strives to improve the performance of public services to the community. We need an information system that can measure and manage the value of the Public Satisfaction Index (IKM) from the questionnaire filled in by the public through the website and performed satisfaction calculations with the method of Importance Performance Analysis (IPA). The results of data processing and analysis using this web-based information system, the public satisfaction index to the services of the Klatakan Village Office is 80,43% with three variables not matching. From the results of Quadrant 1 there are some things that are expected to be described as priority services, Quadrants 2 show achievements or services that can be sustained, Quadran 3 is input from the community related to services with low priority so it needs to be improved and Quadrans 4 is the opinion of the public about what services are considered excessive from the Klatakan village device to the community
Analisis Sentimen Kebijakan Pemberlakuan Cukai pada Minuman Berpemanis dalam Kemasan Menggunakan Metode Multinomial Naive Bayes Firdaus, Muhammad; Rosyidah, Ulya Anisatur; Handayani, Luluk
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 4 (2025): Desember : Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i4.704

Abstract

Sugar consumption in Indonesia remains high, with diabetes affecting 20.4 million people. This condition has prompted the government to introduce an excise policy on Minuman Berpemanis Dalam Kemasan (MBDK) to reduce sugar intake. Social media, particularly the X platform, serves as a medium for the public to express their opinions regarding this policy. This study aims to analyze public sentiment toward the MBDK excise policy using a lexicon-based approach for data labeling and the Multinomial Naive Bayes algorithm with unigram and bigram feature extraction. The initial results show that the highest performance was achieved using 5-Fold Cross Validation, with an average accuracy of 83%, precision of 84%, recall of 75%, and an F1-Score of 77%. After applying data balancing using Stratified Cross Validation combined with Borderline-SMOTE and limiting the features to the 700 most frequent terms, the model’s performance improved. The best results were obtained with 10-Fold Cross Validation, achieving 86% accuracy, 84% precision, 83% recall, and an F1-Score of 83%. These findings indicate that the Multinomial Naive Bayes model can effectively classify public sentiment regarding the MBDK excise policy after the data balancing process.
Analisis Sentimen Kebijakan Pemberlakuan Cukai pada Minuman Berpemanis dalam Kemasan Menggunakan Metode Multinomial Naive Bayes Firdaus, Muhammad; Rosyidah, Ulya Anisatur; Handayani, Luluk
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 4 (2025): Desember : Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i4.704

Abstract

Sugar consumption in Indonesia remains high, with diabetes affecting 20.4 million people. This condition has prompted the government to introduce an excise policy on Minuman Berpemanis Dalam Kemasan (MBDK) to reduce sugar intake. Social media, particularly the X platform, serves as a medium for the public to express their opinions regarding this policy. This study aims to analyze public sentiment toward the MBDK excise policy using a lexicon-based approach for data labeling and the Multinomial Naive Bayes algorithm with unigram and bigram feature extraction. The initial results show that the highest performance was achieved using 5-Fold Cross Validation, with an average accuracy of 83%, precision of 84%, recall of 75%, and an F1-Score of 77%. After applying data balancing using Stratified Cross Validation combined with Borderline-SMOTE and limiting the features to the 700 most frequent terms, the model’s performance improved. The best results were obtained with 10-Fold Cross Validation, achieving 86% accuracy, 84% precision, 83% recall, and an F1-Score of 83%. These findings indicate that the Multinomial Naive Bayes model can effectively classify public sentiment regarding the MBDK excise policy after the data balancing process.