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All Journal Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat UNP Journal of Statistics and Data Science Indonesia Berdampak: Jurnal Pengabdian Kepada Masyarakat
Sarah Fadhlia
Universitas Indraprasta PGRI
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Nursing Public Health Social Sciences Other

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Memahami Konsep Perkembangan Anak Usia Dini bagi Orang Tua Susiati Susiati; Ninta Sri Ulina; Deasy Dwi Cahyaningtyas Arifin; Sarah Fadhlia
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 6 No. 4 (2026): Juli 2026 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v6i4.1233

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan memberikan layanan informasi tentang konsep perkembangan anak usia dini bagi orang tua di Pos KB Kes Terpadu Bungur IV, Pasar Rebo, Jakarta Timur. Sebagian besar orang tua belum memiliki pengetahuan yang lengkap mengenai perkembangan anak, sehingga berdampak pada peran mereka dalam mendampingi anak mencapai perkembangan yang optimal. Metode yang digunakan adalah layanan informasi melalui seminar parenting disertai diskusi dan tanya jawab seputar materi perkembangan anak usia 1–6 tahun, yang mencakup aspek kognitif, bahasa, fisik-motorik, moral, dan sosio-emosional. Hasil kegiatan menunjukkan bahwa orang tua memperoleh wawasan baru tentang tahapan dan tugas perkembangan anak usia dini sehingga dapat lebih baik dalam membimbing dan memantau perkembangan anak di rumah, sekolah, maupun lingkungan sekitarnya. Kegiatan ini diharapkan memberikan manfaat jangka panjang dalam peningkatan kualitas pengasuhan anak oleh orang tua.
Peningkatan Pengetahuan Rambu Lalu Lintas melalui Penyuluhan kepada Ibu-Ibu PKK di Desa Cimanggis, Kabupaten Bogor Eko Primadi Hendri; Aan Sunandar; Torang Hutabarat; Tatang Adhiatna; Sulistyo Sutanto; Sarah Fadhlia
Indonesia Berdampak: Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 2 (2026): JULI-DESEMBER
Publisher : Indo Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/8xnhnb29

Abstract

Limited public understanding of the functions and meanings of traffic signs may affect traffic discipline and increase the risk of traffic violations and accidents. Women members of the Family Welfare Empowerment (PKK) organization play a strategic role as educators within their families; therefore, improving their knowledge of traffic signs is expected to have a broader impact on community traffic safety awareness. This community service program aimed to improve the participants’ knowledge of traffic sign classifications, functions, and meanings through lectures, interactive discussions, and demonstrations. The activity was conducted in RT 001/RW 001, Cimanggis Village, Bojonggede District, Bogor Regency, involving 17 PKK members. The effectiveness of the program was evaluated using a one-group pretest–posttest design. Data were analyzed using descriptive statistics, followed by the Shapiro–Wilk normality test and a paired-samples t-test. The results showed that the mean score increased from 4.65 in the pretest to 7.53 in the posttest, representing an improvement of 2.88 points. The Shapiro–Wilk test indicated that the data were normally distributed (p = 0.207), while the paired-samples t-test revealed a statistically significant improvement in participants’ knowledge after the educational intervention (t = −6.255, p < 0.001). Furthermore, 76.47% of the participants achieved a posttest score of at least seven, meeting the predetermined success indicator. These findings demonstrate that lecture-based education combined with discussion, demonstration, and visual learning media is effective in improving community knowledge of traffic signs and supporting the development of a traffic safety culture within families and the wider community.
Hierarchical Bayesian Modeling with IAR Hexagonal Grids for Reconstructing Incomplete OD Matrices Eko Primadi Hendri; Sarah Fadhlia; Edi Santosa; Rachmat Sadili; Sudirman Anggada
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss3/508

Abstract

Extracting Origin-Destination (OD) matrices in open Bus Rapid Transit systems such as Transjakarta is essential for urban mobility analysis. However, this process is often hindered by incomplete observations, particularly due to missing tap-out data, which leads to extreme sparsity, zero-inflation, and overdispersion in the resulting matrices. This study addresses the problem of probabilistically reconstructing highly sparse OD matrices while accounting for spatial dependencies. To overcome limitations in previous imputation methods—such as ignoring network topology or being affected by the Modifiable Areal Unit Problem (MAUP)—this research proposes a hierarchical Bayesian approach integrating an Intrinsic Autoregressive (IAR) prior within an isotropic hexagonal (H3) tessellation framework. A Negative Binomial distribution is employed to model overdispersed count data, while latent spatial intensities and missing destinations are jointly estimated using Markov Chain Monte Carlo (MCMC). The proposed Spatial IAR model achieves stable convergence with a maximum , whereas the independent non-spatial model fails to converge adequately ( ). Although the independent model produces lower WAIC and LOOIC values (14313.41 and 14313.66) than the Spatial IAR model (14551.88 and 14611.18), the indicates that the apparent predictive superiority is spurious due to inferential instability. Posterior Predictive Checks further confirm that the spatial model successfully reproduces the overdispersion and zero-inflation characteristics of the observed mobility data. Overall, the results demonstrate that spatial regularization is essential for reconstructing high-dimensional sparse urban mobility data and improving the robustness of transportation mobility analysis.
Co-Authors Aan Sunandar Deasy Dwi Cahyaningtyas Arifin Edi Santosa Hendri, Eko Primadi Ninta Sri Ulina Rachmat Sadili Sudirman Anggada Sulistyo Sutanto Susiati Susiati Tatang Adhiatna Torang Hutabarat