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Tuberculosis (TBC) in children remains a serious public health problem in Indonesia, with the 0–14 age group accounting for 16.2% of total notified cases in 2024. The uneven distribution of cases across provinces is thought to be influenced by various social determinants, yet spatial studies specifically on childhood TBC at the national level remain scarce. This study aimed to analyze the spatial pattern of childhood tuberculosis cases and social determinants in Indonesia in 2024 using a spatial ecological design across 38 provinces. Analysis included descriptive statistics, thematic mapping using QGIS, Moran's I test, and Local Indicator of Spatial Association (LISA) with queen contiguity weighting matrix. Results showed a strong positive spatial autocorrelation with a Moran's I value of 0.612. High-high clusters were identified in DKI Jakarta, Central Java, Banten, and West Java, which simultaneously recorded high population density and low primary healthcare ratios. Territory-based interventions should be prioritized in these hotspot provinces.

Tuberculosis (TBC) in children remains a serious public health problem in Indonesia, with the 0–14 age group accounting for 16.2% of total notified cases in 2024. The uneven distribution of cases across provinces is thought to be influenced by various social determinants, yet spatial studies specifically on childhood TBC at the national level remain scarce. This study aimed to analyze the spatial pattern of childhood tuberculosis cases and social determinants in Indonesia in 2024 using a spatial ecological design across 38 provinces. Analysis included descriptive statistics, thematic mapping using QGIS, Moran's I test, and Local Indicator of Spatial Association (LISA) with queen contiguity weighting matrix. Results showed a strong positive spatial autocorrelation with a Moran's I value of 0.612. High-high clusters were identified in DKI Jakarta, Central Java, Banten, and West Java, which simultaneously recorded high population density and low primary healthcare ratios. Territory-based interventions should be prioritized in these hotspot provinces.

Dengue Hemorrhagic Fever (DHF) remains a major public health problem in Indonesia, particularly in densely populated areas. Control efforts require accurate data and spatial analysis to understand disease distribution patterns. Geographic Information System (GIS) is an effective tool for visualizing case distribution and supporting surveillance and planning of control programs at the primary healthcare level. This study aims to describe the spatial distribution of Dengue cases based on medical record data and produce a geographic distribution map to support Dengue control efforts at the Puskesmas level. This study used a quantitative descriptive design with secondary data from medical records at Karangsari Health Center. The sample consisted of 255 DHF patients in 2025, selected using a total sampling technique. Data were processed through editing, geocoding patient addresses, and spatial analysis using QGIS software.The results showed 255 Dengue  cases in 2025 with fluctuating monthly trends, peaking in April and lowest in December. Case distribution was uneven and tended to cluster. High-risk areas accounted for 15.7%–21.2%, moderate-risk areas 9.8%–15.7%, and low-risk areas 7.1%–9.8%. Megu Cilik Village had the highest proportion of cases, while other villages were categorized as moderate and low risk. This pattern indicates that Dengue incidence is influenced by environmental conditions, vector density, host factors, rainfall, and Aedes aegypti presence. GIS provides clearer spatial visualization, helping identify high-risk areas and supporting targeted public health interventions.

Electricity Usage Control (P2TL) is a strategic program of PT PLN to reduce losses due to illegal electricity usage. This study aims to analyze the use of Geographic Information Systems (GIS) based on QGIS in supporting P2TL monitoring in Nabire Regency. The data used includes 54,939 customer coordinate points, collected through field surveys using GPS with a high level of accuracy. The method applied is descriptive spatial analysis with overlay techniques and spatial clustering. The results of the study show an uneven distribution of customers between districts, with the highest concentration in Nabire District (18,247 customers or 33.2%). The dominant tariff type is R1T (60.3%) with the largest power capacity of 1300 VA (49.5%). Spatial analysis identified 12 hotspots and 8 priority monitoring zones. The application of GIS increases the effectiveness of identifying vulnerable areas by 78% and reduces the duration of field inspections by 45%. The resulting thematic map visualization provides significant support in location-based decision making.

Nabire Regency in Central Papua Province confronts significant geographical complexities in transportation system development, characterized by hilly topography and limited road infrastructure that impacts community mobility efficiency. This research analyzes road route optimization through Geographic Information System (GIS) approach using QGIS 3.28.3 software with QNEAT3 plugin for network analysis. The research methodology applies network analysis considering multiple parameters including travel distance, travel time, road surface conditions, slope gradients based on Digital Elevation Model (DEM), and impedance factors according to infrastructure quality. Spatial data were obtained from Geospatial Information Agency (BIG) and OpenStreetMap (OSM) with analysis focusing on 8 origin-destination pairs representing critical movements to health facilities, education centers, and economic hubs. Analysis results identified alternative routes demonstrating 12.5-20% travel time efficiency compared to existing routes, with an average optimization of 15.7%. Field validation confirmed model prediction accuracy with error rates below 8%. These research findings provide strategic recommendations for local government in sustainable transportation infrastructure planning that can enhance regional accessibility and support local economic development in the Central Papua region.

The implementation of the zoning-based admission policy (PPDB) in Semarang City continues to face challenges related to the accuracy of distance measurement and the transparency of information provided to the public. This study aims to examine the application of Geographic Information Systems (GIS) in defining zoning boundaries for public junior high schools in Semarang City and integrating the results into a web-based information platform. A quantitative descriptive approach was employed, incorporating spatial analysis through a 3-kilometer buffer radius using QGIS software. The results indicate that buffer analysis is effective in delineating priority domicile zones based on school coordinate data. These findings are integrated into a GIS-based website that presents visual information on school locations, enrollment capacity, and final score calculation mechanisms in accordance with current regulations. The proposed system contributes to improving information transparency, enabling the public to better understand admission opportunities while supporting government decision-making in promoting equitable access to education. For future development, the use of road network analysis is recommended to obtain more realistic distance estimations.

Brebes Regency is one of the main national centers of shallot production in Indonesia, where agricultural land dynamics play a crucial role in sustaining production performance. Rapid infrastructure development and land-use change have raised concerns regarding the sustainability of shallot cultivation areas. This study aims to analyze spatial–temporal changes in shallot cultivated area and production in Brebes Regency during 2023–2024 and to examine the relationship between land area changes and production levels at the sub-district scale. A descriptive quantitative approach based on spatial analysis was employed using Geographic Information Systems (GIS). Spatial data consisted of administrative boundary maps, while non-spatial data included shallot cultivated area and production data obtained from the Brebes Regency Office of Agriculture and Food Security. Data integration and analysis were conducted using QGIS through attribute joining and inter-annual comparison. The results indicate that total shallot cultivated area increased from 26,331 ha in 2023 to 28,628 ha in 2024, accompanied by a significant rise in production from 289,942.05 tons to 409,106.90 tons. Spatial analysis reveals that major production centers remain concentrated in the central and northern sub-districts, particularly Wanasari, Larangan, Bulakamba, and Tanjung. Although a positive relationship between land expansion and production increase is evident, variations among sub-districts suggest that productivity and local conditions also play important roles. The findings highlight the effectiveness of GIS-based analysis in supporting spatially informed agricultural land management and policy formulation.

Diarrhea and Tuberculosis (TB) remain significant public health problems in Indonesia, including Rembang Regency. This study aims to analyze the spatial distribution and temporal changes of Diarrhea and TB cases in Rembang Regency during 2023–2024 using a Geographic Information Sistem (GIS) approach. A descriptive-analytic method was applied using secondary data, including administrative boundary shapefiles, disease case data, and health facility data at the sub-district level. Spatial processing and analysis were conducted using QGIS to produce thematic maps and compare disease distribution patterns between years. The results indicate that Diarrhea and TB cases were unevenly distributed across sub-districts and formed distinct spatial patterns. Case changes between 2023 and 2024 varied spatially, reflecting dynamic disease trends. The integration of disease maps with health facility distribution shows that areas with high case numbers were not always supported by adequate health facilities. The implementation of GIS-based maps into a web platform enhances accessibility and supports spatial-based public health decision-making.

The transformation of villages into digital villages requires the availability of accurate and integrated data, one of which is geospatial data. Wonoayu Village, Pilangkenceng District, still faces problems such as overlapping land use and limited well-documented geospatial data. This community service activity aims to improve the digital competence of village officials through education on geospatial data management and the practice of creating analog maps using the QGIS application. The implementation method includes partner needs analysis, material preparation, training implementation through interactive lectures, technical demonstrations, hands-on practice, and evaluation using pre- and post-tests. The activity participants consisted of eight Wonoayu Village officials. The results of the activity showed an increase in participants' understanding of basic geospatial concepts, as indicated by an increase in the evaluation score from 72 in the pre-test to 85 in the post-test. In addition, participants were able to process spatial data, digitize it, and produce simple thematic maps that include the coordinates of village officials, educational institutions, and UMKM. This activity has a positive impact on the village's readiness to support data-based development planning and is the first step in realizing a sustainable digital village.

Per capita expenditure is an important indicator of household welfare because it reflects the economic capacity and consumption patterns of the community, as explained in Engel's Law. In regions with diverse geographical characteristics such as Papua Province, spatial analysis is needed to understand the variations in expenditure between districts/cities and the differences between urban and rural areas. This study aims to analyze the spatial distribution of per capita expenditure percentages for food and non-food items in nine districts/cities in Papua Province during the 2022–2024 period. The research data was sourced from the National Socioeconomic Survey (Susenas). The methods used included quantile-based choropleth mapping using QGIS, attribute data merging through table joins, and Pearson's correlation test to evaluate the consistency of spending patterns between years. The analysis results show that food and non-food spending patterns were relatively stable during the observation period with high correlation values (r = 0,85–0,93), although spatial variations between regions were still apparent. Mamberamo Raya Regency consistently had the highest proportion of food spending (>68%), while Jayapura City showed the lowest proportion. These findings indicate spatial disparities related to urbanization levels and economic access. Spatial visualization proved effective in revealing regional disparity patterns that were not fully apparent through conventional statistical tables and has the potential to support the formulation of more evidence-based regional development policies.  

Flooding is one of the most recurrent natural disasters in Central Java Province, particularly during the rainy season. Diverse geographical characteristics, high rainfall intensity, and rapid urban development contribute to the region’s high vulnerability to flood hazards. According to the Central Java Statistics Agency, a total of 414 flood events and 407,784 affected victims were recorded between 2019 and 2021. This study aims to develop a web-based Geographic Information System (GIS) capable of mapping the spatial distribution and impact levels of floods across Central Java. The methodology includes collecting flood event data from the Central Java Statistics Agency, processing spatial data such as administrative boundary shapefiles, performing attribute integration between spatial and non-spatial datasets, and creating thematic maps using QGIS. The visualization outputs were exported into an interactive web format using the qgis2web plugin and subsequently integrated into a website developed with HTML, CSS, and JavaScript. The results show that the GIS system successfully visualizes flood-prone areas, identifies regions with high flood intensity, and enables users to explore detailed information through interactive digital maps. Additional website features—such as historical flood data, statistical summaries, and descriptive impact indicators—enhance the system's usefulness for disaster analysis. This study demonstrates the crucial role of GIS in supporting disaster mitigation, spatial planning, and policy evaluation related to flood management. Future research is recommended to incorporate more recent datasets and additional non-spatial variables such as rainfall intensity and floodwater depth to improve the system’s analytical accuracy and comprehensiveness.

This study aims to design and build a population distribution application in Demak Regency in 2025 using a Geographic Information System (GIS) approach. The study focuses on three main variables: population, population density, and population growth rate per sub-district. The author used the research method of collecting data and references that can later strengthen the results of this study and the application design using the waterfall model. Non-spatial data, namely data in the form of population information, was obtained from the Central Statistics Agency of Demak Regency, while spatial data is data related to regional administrative boundaries. Data processing was carried out using QGIS 2.18 through the stages of joining attributes, classification using the Natural Breaks (Jenks) method, and thematic map creation. The results show that population distribution is uneven. Demak Kota, Karangtengah, and Sayung sub-districts have the highest number and density, while coastal sub-districts such as Wedung and Bonang have low densities. The highest population growth rate is in Karangtengah sub-district at 0.8%. The application of GIS has proven effective in visualizing population distribution and supporting spatial-based regional development planning.  

Commercial facilities such as supermarkets, minimarkets, and traditional stalls are an essential part of urban economic infrastructure services, especially in areas with high population growth. However, the rapid growth of population is not always balanced by an even distribution of commercial facilities. This triggers spatial accessibility inequality. This study aims to analyze the coverage of service areas of the three categories of commercial facilities in Pinang Kencana sub-district, Tanjungpinang City, using a spatial approach based on GIS. The methods employed include network analysis, service area analysis, and Euclidean distance analysis. The results of the study show that the coverage of 0-2,000 meters is an area served by all types of commercial facilities, with an area of 82.5%, while the area beyond 2,000 meters, which accounts for 17.5%, is an unserved area located in the east and southeast. The served zone is characterized by agglomerated residential areas, which have an adequate road network. In contrast, the unserved area is marked by limited road networks and low residential density. This research has strategic implications for policymakers, especially in preparing zoning regulations and Detailed Spatial Planning Plans (RDTR) in Pinang Kencana sub-district, East Tanjungpinang District, Tanjungpinang City.

Acute Respiratory Infection (ARI) is an infectious disease that often affects the upper and lower respiratory tract. This disease is one of the main causes of death in children under five, especially in areas with less favourable environmental conditions. This study aims to map the distribution of ARI in Central Java Province using the K-Means clustering method. Through data analysis that includes inputting, transforming, processing, and visualisation, this study successfully identified three clusters of areas with different levels of ARI distribution. Cluster 0 indicates areas with low risk, such as Demak and Semarang Regency, Cluster 1 indicates areas with medium risk, such as Klaten, Magelang Regency, Pati, while cluster 2 indicates areas with high risk, including Semarang City and Surakarta City. The results of this analysis are presented as a map using QGIS to spatially visualise the distribution of ARI across Central Java. Thus, local governments can design more effective and targeted ARI prevention and control strategies.

This study aims to analyze and visualize the distribution of COVID-19 cases in Indonesia throughout 2020 with a spatial-based quantitative approach. The data used was obtained from the official report of the Ministry of Health of the Republic of Indonesia as of December 30, 2020, including the number of confirmed cases, recovered, and died. The analysis was carried out by integrating clustering methods and Geographic Information Systems (GIS) using Quantum GIS (QGIS) software. The visualization results show significant spatial variations between provinces, where provinces with high population density such as DKI Jakarta, West Java, East Java, and Central Java are recorded as areas with the highest caseload. In addition, areas with limited health facilities also show a high potential risk of transmission and death. Cluster patterns of positive and cured cases generally show similarities, while mortality rates show spatial inequalities that are important to look at. These findings emphasize the importance of spatial data integration in area-based policy planning for pandemic control. Spatial visualization not only facilitates understanding of distribution patterns, but also supports more effective and targeted decision-making.

Using End User Computing Satisfaction (EUCS) and User Centered Design (UCD) methods, this study investigated user satisfaction with QGIS and CarryMap.  The research objective was to deploy elements such as content, accuracy, ease of use, and timeliness.  A survey of students and teachers showed that users were more satisfied with the latest versions of both applications.  The findings show that the user interface and functionality have evolved, which indicates the direction of future development of mapping applications.

This study aims to utilize QGIS as a spatial analysis tool to map the distribution of divorces based on economic factors and disputes in Surakarta City during the 2020–2023 period. The data used includes spatial data in the form of Surakarta City's administrative map in shapefile format and non-spatial data comprising the number of divorces obtained from BPS Surakarta. Non-spatial data were integrated into spatial data using the "join attribute" feature in QGIS. The analysis process was conducted using classification methods to identify areas with the highest divorce density. The findings reveal that divorces due to economic factors are concentrated in low-income areas, such as Banjarsari and Jebres, while divorces caused by disputes exhibit a more evenly distributed pattern. The thematic maps were then exported into GeoJSON format for implementation on an interactive website accessible to the public and policymakers. This study contributes to the utilization of GIS technology in supporting data-driven decision-making.

Basil Mycobacterium Tuberculosis adalah penyebab utama penyakit menular yang dikenal sebagai Tuberkulosis Paru. RSUD dr. Adhyatma, MPH Semarang memiliki 125 pasien TB paru pada tahun 2021. Tujuan penelitian adalah menganalisis persebaran kasus TB di Kota Semarang menurut jenis kelamin, usia, per kecamatan. Penelitian ini adalah penelitian deskripsi melalui observasi data sekunder. Pembuatan peta menggunakan aplikasi (QGIS). Hasil menunjukkan Sebagian besar kasus TB Paru adalah pada laki – laki, kelompok usia dewasa dan anak, dan domisili di Kecamatan Ngaliyan, Semarang Barat, Tugu, dan Mijen. Faktor yang berhubungan dengan TB Paru adalah kebiasaan merokok, pola hidup kurang sehat, status gizi, kurang istirahat, rumah tidak sesuai standar, lingkungan tidak sehat, interaksi sosial, perbedaan tingkat pengetahuan, dan Pendidikan. Saran penyuluhan kesehatan tentang penyakit TB Paru sebaiknya dilakukan di Kecamatan dengan kasus tertinggi di Kota Semarang. Peta persebaran kasus TB dapat digunakan untuk mengetahui informasi dan memantau perkembangan persebaran kasus TB di Kota Semarang.

Research carried out by KKN students in the form of community service aims to facilitate public access to location points in a place or region through public facilities in Pancuran Gading Village, Tapung District, Kampar Regency, Riau Province. This research was carried out using an implementation technique in the form of Participatory Action Research (PAR) Method (Participatory Action Research) with three principles which serve as a reference for service research. In carrying out the mapping of the coordinates of public facilities in Pancuran Gading Village, the research we carried out was coordinated by the village, namely Mr. Hari Isnaldi as Secretary of Pancuran Gading Village, Tapung District. Villages are seen as the starting point for empowering regional potential. With this village potential mapping, it can be used to find out existing potential information, and can be used as material for village development planning. This potential map was created using digital mapping technology in the form of the QGIS application which is viewed through a map and then created manually in the application. With the success of the students, they created a map as a means used by the community to access public facilities or places in Pancuran Gading Village.

Central Papua Province is a new autonomous region province located in the Papua region. consists of 8 districts with the dominant topography of high rainfall for most of the year. As a result, the region in Central Papua often experiences hydrometeorological disasters, including floods, landslides, fallen trees, collapsed roofs. This study aims to map weather forecast infographics in Central Papua Province with QGIS and Adobe Photoshop Using the utilization model in the QGIS application which is overlaid with shapefile data from the BMKG signature of Central Papua Province. As well as shapefile data from the geospatial Indonesia website, namely the latest village and administrative boundaries 2022/2023 for the expansion of 38 provinces on a scale of 10K BIG. Then On the photoshop application helps infographic image editing. In making a map of Central Papua province with additional administrative boundaries of protected areas, tourist sites and latitude and longitude. As well as BMKG signature polygon alerts from signature.bmkg.go.id/ site. Once overlayed, it produces any area affected.