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PERUBAHAN AKTIVITAS NELAYAN DI URK, PROVINSI FLEVOLAND SETELAH PEMBANGUNAN AFSLUITDIJK Shasa Chairunnisa; Dewi Susiloningtyas; Tuty Handayani; Titin Siswantining
JFMR (Journal of Fisheries and Marine Research) Vol 5, No 1 (2021): JFMR VOL 5 NO.1
Publisher : JFMR (Journal of Fisheries and Marine Research)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2021.005.01.5

Abstract

Afsluitdijk adalah tanggul laut terbesar yang dibangun oleh pemerintah untuk mengatasi masalah banjir di Belanda. Pembangunan Afsluitdijk menyebabkan beberapa perubahan pada lingkungan dan komunitas pesisir di sekitarnya, salah satunya adalah komunitas nelayan di Urk, Provinsi Flevoland, Belanda. Tujuan dari penelitian ini adalah untuk menganalisis perubahan kegiatan penangkapan ikan setelah pembangunan Afsluitdijk. Penelitian ini dilakukan di Desa Urk, Provinsi Flevoland, Belanda pada Mei - Juni 2019. Penelitian ini menggunakan pendekatan deskriptif kualitatif. Data penelitian diperoleh dari wawancara mendalam dan studi literatur. Hasil penelitian menunjukkan adanya perubahan lingkungan akuatik yang awalnya merupakan air asin menjadi air tawar. Terdapat beberapa nelayan yang masih bertahan hidup untuk menangkap ikan di perairan sekitar Urk dan Harlingen setelah pembangunan, tetapi ada juga yang beralih profesi dan pindah ke daerah lain di Belanda. Kesimpulan dari penelitian ini adalah terdapat perubahan pada kondisi lingkungan perairan dan ekonomi nelayan, serta nelayan harus beradaptasi dengan kondisi baru setelah pembangunan Afsluitdijk.
Evaluation of Biclustering Imputation Methods for Glioblastoma Gene Expression Data Silalahi, Agatha; Titin Siswantining; Setia Pramana
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 5 Issue 1, April 2025
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol5.iss1.art7

Abstract

Glioblastoma is a highly aggressive primary brain tumor with a low survival rate. One of the main challenges in analyzing glioblastoma gene expression data is the presence of missing values, which can reduce biclustering accuracy and affect biological interpretation. This research compared six imputation methods k-nearest neighbors (KNN), mean imputation, singular value decomposition, nonnegative matrix factorization, soft impute, and autoencoderon the GSE4290 gene expression dataset with missing values ranging from 5% to 50%. An evaluation using root mean square error (RMSE), mean absolute error (MAE), and structural similarity index measure (SSIM) showed that soft impute provided the best performance at all levels of missing values, with RMSE of 0.0076, MAE of 0.0073, and perfect SSIM of 1.0000 at 50% missing values. Meanwhile, deep learning-based autoencoder experienced significant performance degradation at high missing values. These findings indicate that more complex models are not always superior, and regularization-based approaches like soft impute are more effective in preserving the biological structure of the data. The results of this research contribute to the optimization of imputation strategies to improve the accuracy of biclustering analysis in glioblastoma studies.
Indeks Pembangunan Kesehatan Polri: Indeks Pembangunan Kesehatan Polri Frans Tjahyono; Dwi Purwoko; Titin Siswantining
Jurnal Litbang Polri Vol 27 No 3 (2024): JURNAL LITBANG POLRI
Publisher : Pusat Penelitian dan Pengembangan Polri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46976/litbangpolri.v27i3.252

Abstract

National Police health development is a long-term investment in the development of National Police personnel with the hope that it can play a role in increasing life expectancy and maintaining and improving their level of health so that they can carry out their main duties optimally in safeguarding and maintaining security and public order optimally. This research was conducted in 11 Polda and 96 Polres. Data collection was carried out by distributing questionnaires to all Civil Servants at the National Police, FGDs with key officials at the Regional Police and Regional Police, as well as FGDs with health workers at the National Police Polyclinic/FKTP. The results showed that the national percentage of PNPP health conditions was 29% (84,102 PNPP) obesity, 20.40% (58,997 PNPP) central obesity, the highest prevalence rate of PTM (Gastric, Heart Diabetes Mellitus and Stroke), the highest prevalence rate of PM (Diarrhea, Typus and Malaria). Nationally, around 0.7% (1,902 PNPP) SRQ-20 screening results indicated mild GME. A total of 0.15% (432 PNPP) indicated moderate GME, and 0.1% (292 PNPP) indicated heavy GME. Apart from that, there were also 0.07% (206 PNPP) who thought about committing suicide.