This study proposes a new model for land suitability for educational facilities based on spatial product development to determine the optimal locations for achieving education targets in West Java, Indonesia. Single-aspect approaches, such as accessibility and spatial hazard analyses, have not been widely applied in suitability assessments on the location of educational facilities. Model development was performed based on analyses of the economic value of the land and on the integration of various parameters across three main aspects: accessibility, comfort, and a multi-natural/biohazard (disaster) risk index. Based on the maps of disaster hazards, higher flood-prone areas are found to be in gentle slopes and located in large cities. Higher risks of landslides are spread throughout the study area, while higher levels of earthquake risk are predominantly in the south, close to the active faults and megathrusts present. Presently, many schools are located in very high vulnerability zones (2057 elementary, 572 junior high, 157 senior high, and 313 vocational high schools). The comfort-level map revealed 13,459 schools located in areas with very low and low comfort levels, whereas only 2377 schools are in locations of high or very high comfort levels. Based on the school accessibility map, higher levels are located in the larger cities of West Java, whereas schools with lower accessibility are documented far from these urban areas. In particular, senior high school accessibility is predominant in areas of lower accessibility levels, as there are comparatively fewer facilities available in West Java. Overall, higher levels of suitability are spread throughout West Java. These distribution results revealed an expansion of the availability of schools by area: senior high schools, 303,973.1 ha; vocational high schools, 94,170.51 ha; and junior high schools, 12,981.78 ha. Changes in elementary schools (3936.69 ha) were insignificant, as the current number of elementary schools is relatively much higher. This study represents the first to attempt to integrate these four parameters—accessibility, multi natural hazard, biohazard, comfort index, and land value—to determine potential areas for new schools to achieve educational equity targets.

Posyandu is an Indonesian mother-child health, community-based healthcare. The provision of the Posyandu data quality map is crucial for analyzing results but is limited. This research aimed to (a) demonstrate data quality analysis on its completeness, accuracy, and consistency and (b) map the data quality in Indonesia for evaluation and improvement. An observational study was conducted using the Posyandu application. We observed data in Indonesia from 2019 to 2021. Data completeness was identified using children’s visits/year. Data accuracy was analyzed using WHO anthropometry z-score and implausible z-score values analyzing the outliers. Cronbach’s α of variables was used to know data consistency. STATA 15.1 SE and QGIS 3.10 was used to analyze and map the quality. Data completeness and accuracy in three years show a good start for the pilot project area, continued with declines in pandemic time, while some other areas demonstrated a small start, then slightly increased. The overall consistency decreased through the study period. A good report on data completeness can occur initially in a pilot project area, followed by others. Data accuracy and consistency can decrease during the pandemic. The app can be promising when synchronized with the government health information system.

Kerapatan vegetasi merupakan presentase suatu spesies vegetasi atau tumbuhan yang hidup di suatu luasan tertentu. Kerapatan vegetasi salah satunya dapat diketahui dengan menggunakan teknik NDVI. Teknik yang dapat digunakan untuk keperluan menganalisis vegetasi. Informasi data kerapatan vegetasi, luas lahan, dan keadaan dilapangan dapat dideteksi dari penginderaan jauh. Penelitian ini bertujuan untuk untuk mengetahui hasil identifikasi kerapatan vegetasi daerah Kabupaten Pangandaran menggunakan metode klasifikasi terbimbing minimum distance dan menguji hasil interpretasinya menggunakan confussion matrix. Salah satu manfaat informasi data kerapatan vegetasi ini ialah dapat memberikan gambaran mengenai ketersediaan ruang terbuka di Kabupaten Pangandaran. Klasifikasi kerapatan vegetasi pada citra Landsat 8 dengan kombinasi RGB 753 menghasilkan warna ungu dengan yang berarti sangat rapat, oranye yang berarti rapat, kuning yang berarti cukup rapat, hijau dengan vegetasi jarang, dan biru yang berarti vegetasi sangat jarang. Total hasil akurasi pada confussion matriks bernilai 64% yang berarti tingkat akurasi peta cukup rendah karena biasanya nilai yang diterima dan diharapkan itu lebih dari 85%.Hal ini dikarenakan oleh keadaan di lapangan yang dinamis karena sebagian besar kerapatan vegetasi di lapangan berkurang akibat pengalihfungsian lahan.

Pengindraan jauh saat ini sudah mulai dikembangkan dan dimanfaatkan untuk berbagai bidang keilmuan. Penelitian ini dilakukan dengan menggunakan metode pengindraan jauh) di Kecamatan Pangandaran untuk mengetahui kesesuaian kerapatan vegetasi dengan hasil interpretasi. Menggunakan citra Landsat 8 dengan metode Unsupervised Classification Iso Data dan dalam pengolahannya menggunakan softwareEnvi 5.0 dan Arcgis 10.4. Analisis yang digunakan yaitu analisis spasial dan membandingkan hasil interpretasi dengan hasil data di lapangan, dan melakukan uji akurasi. Uji akurasi dilakukan untuk menemukan besaran kesesuaian metode dengan data yang dilakukan. Maka akan dapat diketahui bahwa metode klasifikasi yang digunakan kurang tepat untuk mengidentifikasi kerapatan vegetasi karena memiliki banyak data yang tidak sesuai dengan yang ada di lapangan. Dengan mengidentifikasi kerapatan vegetasi, maka dapat membantu mengetahui perencanaan ruang terbuka hijau yang tepat untuk wilayah kecamatan Pangandaran.