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Wahno Subdistrict in Abepura District, Jayapura City, faces drainage problems that disrupt the area’s water management function. The varied topography, population growth, and the community’s habit of disposing waste into drainage channels have reduced the system’s capacity and caused frequent waterlogging during rainfall. This study aims to analyze the existing condition of the drainage channels in Wahno and to evaluate their effectiveness in conveying stormwater flow. The research methods include field surveys, channel dimension measurements, capacity calculations, and analysis of the effective volume compared to actual conditions affected by waste and sedimentation. The data were analyzed using quantitative and descriptive approaches to assess the performance level of the drainage system. The results show that most drainage channels in Wahno are not functioning optimally, with an average effectiveness of only 45–60% due to blockages caused by waste and sedimentation. The main factors reducing drainage effectiveness are decreased storage capacity, substandard design, and lack of regular maintenance. It is concluded that improvements to channel capacity, better waste management, and routine maintenance programs are necessary to enhance the drainage system’s effectiveness.

Accurate rainfall prediction is needed to improve the performance of land that always uses rainfall data. Data mining or often called knowledge discovery in databases (KDD) is an activity that includes collecting, using historical data to find regularities, patterns or relationships in large data. In predicting rainfall, there are several conditions that can be observed as reference data to predict rainfall, namely wind speed, temperature, and air humidity. In this research, a backpropagation artificial neural network prediction method is developed that can be used in predicting future rainfall. The backpropogation artificial neural network method that was built produced an accuracy value of 95.36%, a precision value of 90.50%, a recall value of 97.50% and an f-measure value of 92.00%

The research area is prone to flooding, which could potentially result in losses for the people of the research area. Based on this, it is important to map flood-prone areas, as a form of flood disaster mitigation effort to reduce the level of flood risk. Hazard mapping is an important stage in the process of disaster risk identification and analysis. Mapping flood-prone areas can use various methods or approaches. Approaches that can be used for assessing or mapping flood hazards are the geomorphological approach and community participation. This type of research is quantitative descriptive, namely a type of investigation that explains or explains a problem. Descriptive studies aim to explain populations, situations or phenomena accurately or systematically. Mapping flood hazards in the Koto Tangah District, Padang City. From the results of the analysis of the level of flood vulnerability above, the relationship between this research is that rainfall is too high and low river beds cause water to overflow into lowlands, causing the level of flood vulnerability to increase as time goes by. So The results obtained from the analysis of Flood Hazard Area Mapping are the area of ​​Koto Tangah sub-district is 22.017,43ha, by getting the level of non-prone areas with an area of ​​10.203.16ha, the level of less-prone areas with an area of ​​4.714.168ha, the level of vulnerable areas with an area of ​​3.990.458ha, the level of very vulnerable area with an area of ​​1.893,630ha. Koto Tangah District, Padang City has five levels of danger zones for flooding, based on the results of the parameter data used. Each parameter used greatly influences the level of flood risk in Koto Tangah District, Padang City, namely river buffer, land use, land height, land slope, soil type and rainfall. From the creation of flood prone levels in Koto Tangah sub-district, Padang city, areas with a very high risk of flooding are 10.68% with an area of ​​1892,630 ha, areas with a danger level of flood prone are 14.68% with an area of ​​3990,458 ha, areas with Kuang's flood-prone level is 21.40% with an area of ​​4714,168 ha, the area with a flood-safe level is 46.32% with an area of ​​10,203.16 ha.