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All Journal Jurnal Manajemen Pendidikan BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Informatika: Jurnal Pengembangan IT
Zahra, Latifah
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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MENGANALISIS STRATEGI PENGEMBANGAN PROFESIONALISME GURU DALAM PEMBELAJARAN SEUMUR HIDUP DI ERA DIGITAL: TANTANGAN DAN PELUANG Ginting, Anisa Nur Baidah; Zahra, Salwa; Aulia, Mita; Zahra, Latifah; Sigiro, Martina; Purba, Sasta Glovia Talenta; Nainggolan, Elizon; Subaedah, Sitti
Jurnal Manajemen Pendidikan Vol. 10 No. 1 (2025): Regular Issue
Publisher : STKIP Pesisir Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34125/jmp.v10i1.392

Abstract

This study examines the integration of digital technology in learning and the professional development of teachers in the digital era at the elementary school level. The digital transformation requires teachers to master digital competencies in order to deliver interactive and innovative instruction. The study is motivated by various challenges, including limited formal training, inadequate digital infrastructure, and the differing instructional needs between lower and upper elementary levels. A review of literature supports that enhancing digital literacy through TPACK models and intensive training approaches is an effective strategy to improve teaching quality. Data were collected through in-depth interviews with two teachers (from a first-grade class and a fifth-grade class) and current literature studies. Content and thematic analysis were employed to identify key issues regarding technological integration and professional development strategies. The results reveal that limited formal training and digital infrastructure adversely affect the teaching process, while participation in workshops and peer collaboration enhances teachers’ digital competencies. These findings provide strategic recommendations for schools and education authorities to develop continuous training programs tailored to the specific needs of each educational level.
Pemodelan Topik pada Komentar YouTube Arra: Komparasi LDA dan K-Means Menggunakan Fitur Leksikal dan Semantik Nuradilla, Siti; Kamila, Sabrina Adnin; Zahra, Latifah; Suhaeni, Cici; Sartono, Bagus
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 3 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i3.8763

Abstract

YouTube has become a platform for sharing content, including positive material and stereotypes that often trigger debates. One noteworthy phenomenon is the video of Arra, a toddler known for her remarkable communication skills. This uniqueness has drawn significant attention and sparked debates about the mismatch between her age and cognitive development. The diverse comments on Arra’s videos reflect sharply differing perspectives among netizens, making manual analysis highly challenging. Therefore, it is important to examine the topics discussed by netizens to understand the dominant issues emerging in these discussions. Through this approach, the public can gain insights, and parents may receive valuable input regarding child-rearing practices. The main objective of this study is to explore the effectiveness of the two methods and their combinations of text representations in identifying key topics within comments by comparing the coherence performance of the models. This research applies topic modeling to analyze comments using two primary approaches: Latent Dirichlet Allocation (LDA) and K-Means clustering. The study involves data collection through comment crawling, followed by text preprocessing and text representation using TF-IDF and GloVe embeddings. LDA and K-Means are then used to identify dominant topics appearing in the comments. The results show that LDA with TF-IDF achieved the highest coherence score of 0.662, although the resulting topics were still difficult to interpret due to overlap. Meanwhile, K-Means with GloVe 100D yielded a slightly lower coherence score of 0.6538 but outperformed in terms of interpretability. Therefore, K-Means with GloVe 100D is considered a more balanced approach in terms of both coherence and topic readability.
A COMPARISON OF FUZZY TIME SERIES CHENG AND CHEN-HSU IN FORECASTING TOTAL AIRPLANE PASSENGERS OF SOEKARNO-HATTA AIRPORT Zahra, Latifah; Maiyastri, Maiyastri; Rahmi, Izzati
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0019-0028

Abstract

In some cases, the demand for flights has increased or decreased unexpectedly. Based on this airport as a service provider balance the availability of the service and the needs in the field. To balance all the provided services, the airport needs to predict the total passenger that would visit the airport on consecutive days. Thus, a form of time-series forecast is used in this research. We applied fuzzy time series (FTS) to forecasting total airplane passengers, where there are several logics in FTS including FTS Cheng’s Logic and FTS Chen-Hsu’s Logic. To determine the accuracy of the forecast, use three criteria, namely Root Mean Squared Error (RMSE), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE). In terms of modelling and forecasting data, FTS Chen-Hsu’s Logic is better than FTS Cheng’s Logic. This is shown in the value of three accuracy criteria of FTS Chen-Hsu’s Logic are smaller than FTS Cheng’s Logic. Conclusion, FTS Chen-Hsu method can be used as a forecasting model for the total passenger airplane in Soekarno-Hatta International Airport
Identification of Latent Dimensions of Digital Readiness and Typology of Districts/Cities in Indonesia Using PCA and K-Means Clustering Sari, Jefita Resti; Fahira, Fani; Zahra, Latifah; Fitrianto, Anwar; Alifviansyah, Kevin
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11487

Abstract

Digital transformation is a key agenda in Indonesia’s national development that requires balanced readiness across regions. However, the level of digital readiness among districts and cities still varies widely, highlighting the need for a typology that can comprehensively describe existing disparities. This study aims to identify the latent dimensions of digital readiness and to develop a regional typology of Indonesian districts/cities using Principal Component Analysis (PCA) and K-Means clustering. The data were obtained from the 2024 Indonesian Digital Society Index (IMDI), which consists of four pillars—Infrastructure and Ecosystem, Digital Skills, Empowerment, and Employment—with ten sub-pillars. PCA reduced these correlated indicators into two main latent components, namely Digital Capacity and Participation and Digital Infrastructure Foundation, which together explain 70.4% of the total variance. Cluster validation using the Silhouette Score and Davies–Bouldin Index (DBI) showed that K = 2 yielded the best internal validity (Silhouette = 0.402; DBI = 0.906), but a three-cluster configuration (K = 3) was adopted to obtain a more interpretable typology of high-, medium-, and low-readiness regions (Silhouette = 0.346; DBI = 1.007). Spatial mapping reveals that high-readiness districts are concentrated in Java, Bali, and parts of Sumatra, whereas low-readiness areas dominate eastern Indonesia. These findings confirm persistent digital inequality across regions and provide a quantitative basis for targeted policy interventions, including infrastructure development, digital literacy programs, and innovation ecosystem strengthening, to support an inclusive digital transformation in Indonesia.
Co-Authors Alifviansyah, Kevin Aulia, Mita Bagus Sartono Fahira, Fani Fitrianto, Anwar Ginting, Anisa Nur Baidah Izzati Rahmi HG Kamila, Sabrina Adnin Maiyastri, Maiyastri Nainggolan, Elizon NURADILLA, SITI Purba, Sasta Glovia Talenta Sari, Jefita Resti Sigiro, Martina Subaedah, Sitti Suhaeni, Cici Zahra, Salwa