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The greening program is an important effort to improve environmental quality and strengthen community awareness of ecological sustainability. This study aims to describe the implementation of tree-planting activities carried out by university students in Kalikatir Village through a participatory approach. The research employed a qualitative descriptive method, using observation, interviews, and documentation as data-collection techniques. The findings indicate that community participation plays a significant role in the success of the program, particularly in selecting planting locations, providing tools and support, and maintaining the planted trees. The greening activities have produced positive impacts, including increased vegetation cover, a cooler village environment, and stronger community awareness of the importance of green spaces. Moreover, collaboration between students and local residents has enhanced social cohesion and supported the sustainability of environmental initiatives. This study concludes that a participatory approach combined with a qualitative descriptive method is effective in understanding the dynamics of implementing greening programs at the village level.

The customary forest of Sub-Tribe Afsya, Bariat Village, South Sorong Regency, Southwest Papua is a lowland tropical rainforest of approximately 2,500 hectares managed under the indigenous "Sasi Adat" system. This study aimed to determine bird species diversity, evenness of distribution, and the relationship between bird communities and vegetation structure. Research was conducted in January 2026 using a combination of line transect and point count methods along five 1,000-meter transects, observed in the morning (06:00–10:00 WIT) and afternoon (15:30–18:00 WIT). Data were analyzed using the Shannon–Wiener Diversity Index (H’), Simpson's Dominance Index (D), Evenness Index (E), and vegetation Important Value Index (IVI). The study recorded 30 bird species from 16 families with 492 individuals, including 12 Papua-endemic species protected under Minister of Environment and Forestry Regulation No. P.106/2018. H’ values ranged from 1.197 to 2.472 (moderate to high); dominance was low to moderate; and evenness ranged from 0.668 to 0.933, with most transects showing high evenness (E > 0.75). Vegetation was dominated by damar trees (Agathis labillardierei) and fruiting trees synergistically supporting frugivore, insectivore, and nectarivore bird guilds. The Sasi Adat management system demonstrably contributes to habitat quality, rendering this forest of significant conservation value for Southwest Papua's avifauna.

Rubber (Hevea brasiliensis) is an important plantation commodity that contributes to improving rural livelihoods. However, the productivity of smallholder rubber plantations remains relatively low due to various technical constraints, socio-economic conditions, and limited farmers’ knowledge and technology. This study aims to analyze the influence of technical aspects of cultivation and socio-economic aspects on farmers’ knowledge and technology in rubber cultivation in Desa Antutan, Kecamatan Tanjung Palas, Kabupaten Bulungan. This research employed a mixed methods approach with a descriptive design. Quantitative data were collected through questionnaires distributed to 30 rubber farmers selected using purposive sampling, while qualitative data were obtained through in-depth interviews and documentation. Quantitative data were analyzed using multiple linear regression with SPSS software, while qualitative data were analyzed through data reduction, data display, and conclusion drawing The results indicate that technical aspects of cultivation and socio-economic aspects simultaneously influence farmers’ knowledge and technology in rubber cultivation. Partially, technical cultivation aspects have a more dominant effect than socio-economic aspects. Qualitative findings reveal that the main problems faced by farmers include improper tapping techniques, aging rubber trees, rubber price fluctuations, and limited access to agricultural training and extension services.

The community service program in Dusun Bendrong aimed to foster environmental awareness through the planting of timber and fruit seedlings as a response to declining forest quality and reduced water availability caused by vegetation loss. This program sought to enhance community participation in forest conservation while strengthening local wisdom related to environmental stewardship. The activity was conducted in three stages: pre-activity observation and coordination with the Village Head and community leaders, joint planting of 14 seedlings by Student Community Service (KKM) participants and local residents, and monitoring and evaluation to assess implementation and participant understanding. The results showed that all seedlings were successfully planted, with high levels of participation from both students and community members. The activity increased awareness of forest conservation and highlighted the importance of collective action in maintaining environmental sustainability. Timber trees contributed to forest restoration, improved water absorption, and reduced erosion risk, while fruit trees provided additional economic and social benefits for the community. Overall, this participatory approach proved effective as a sustainable model for community service programs that integrate environmental conservation and community empowerment.

Peat characteristics include low fertility, high acidity, and poor drainage because it comes from the weathering of organic matter under anaerobic conditions. However, peat has environmental benefits such as absorbing carbon, water buffers, and providing habitat for various unique flora and fauna. The use of peat as agricultural land is widely used by farmers in Pontianak City because it has a very large peatland area with a traditional agricultural system. However, traditional farming will have local knowledge (local wisdom) as a way to minimize damage to the peat ecosystem as an adaptation effort. This study aims to examine the adaptation of peatland management in traditional farming in Pontianak City. The method used in this study is qualitative descriptive and multiple linear regression analysis. The number of research samples was 68 farmers. The results of the study showed that traditional farmers have paid attention to the sustainability of their farming to minimize environmental damage. The results of the study showed that the adaptations carried out were making wells to maintain water availability, using short-lived vegetables that require shallow drainage of 20-30 cm and are adaptive to peat, providing intensive shade, planting trees on empty land, cleaning intensive irrigation, providing ameliorant ash, lime, chicken manure intensively, and arranging planting patterns with diversification. The determining factors for peatland management adaptation include age, land area, length of farming, participation of fire-conscious communities, and intensity of participation in outreach.

Malino City in Gowa Regency plays a crucial ecological role as a water catchment area, yet it currently faces the threat of land degradation due to land-use conversion and erosion in hilly areas. This community service activity aims to implement soil conservation while enhancing the economic potential of local residents through the planting of productive fruit tree seedlings. The methods employed include educational socialization, training on planting techniques for sloped land, and the distribution of superior fruit tree seedlings (avocado, durian, and orange). The results indicate an increase in community understanding regarding the importance of permanent vegetation in maintaining soil stability. A total of [Mention number] tree seedlings were planted with the active participation of local farmer groups. In conclusion, the integration of ecological and economic aspects through productive trees creates a sustainable conservation system by providing direct financial benefits to the community, thereby increasing their motivation to preserve the environment in the Malino region.

In high-performance computing (HPC) environments, the need to balance memory efficiency and query performance is crucial for ensuring optimal system performance. Traditional data structures, such as B-trees and hash tables, often prioritize either memory usage or query speed, leading to suboptimal performance in memory-constrained systems. This paper proposes a hybrid data structure that combines the strengths of multiple traditional data structures to optimize both memory usage and query processing speed. The proposed hybrid structure integrates cache-conscious algorithms, dynamic memory allocation, and compression techniques for intermediate query results. The approach is evaluated through extensive benchmarking tests comparing it to standard data structures like B-trees and hash tables under various workloads. Results show that the hybrid data structure reduces memory overhead by up to 30% while maintaining query processing speeds up to 1.5 times faster than conventional methods. Furthermore, the hybrid structure demonstrates robust performance across different types of queries, including both point and range queries, ensuring versatility and efficiency. The findings indicate that this hybrid approach provides a promising solution for HPC systems, where both memory efficiency and query speed are essential. Future research can explore extending the hybrid structure to distributed systems and emerging technologies, further improving its scalability and adaptability to new computational paradigms.

Detection and identification of plant diseases is critical to the success and efficiency of agricultural production. Plant disease outbreaks are becoming more frequent throughout the world, and the presence of these diseases in cultivated plants has a significant impact on productivity. Therefore, researchers are focusing on developing effective and reliable plant disease detection methods. Thus, farmers can take advantage of early detection of this disease to minimize future losses. This article discusses machine learning approaches as well as decision trees, K-nearest neighbors, naive Bayes, support vector machines (SVM), and random forests for detecting coffee leaf diseases using leaf images. The above-mentioned classifications were researched and compared to determine the most suitable plant disease prediction model with the highest accuracy. Compared with other classification algorithms, the SVM algorithm achieves the highest accuracy of 99.75%. All the models trained above will be used by farmers to quickly identify and classify new diseases in images as a prevention strategy. As a preventive measure, farmers can detect and classify new diseases in images early.

Crime, an unlawful act that contradicts ethics and norms, has now become a primary factor for the police in Lampung province. This presents a challenge for the police institution in predicting high crime rates. However, there are still many crimes that have not become the main focus of problem-solving at the Lampung Regional Police.This research aims to identify the types and criminal acts of crime with the highest recorded incidence in a crime dataset by performing classification using the Naïve Bayes algorithm. The data was obtained from investigators at the Directorate of General Criminal Investigation of the Lampung Regional Police, with a total of 12,034 JTP (Total Criminal Acts) and 7,518 PTP (Crime Resolution) data points for each type of crime, distributed across the Regional Police, City Police, and District Police throughout Lampung province. The classification process using the Naïve Bayes algorithm reveals the relationship between the work unit (Satker) and the type of crime handled, thereby identifying crime patterns based on the location where they are handled. The results of the research, which involved converting numerical data into binomial (binary) form using the "Numerical to Binominal" feature in Rapid miner, show that the analysis and modeling process, especially in algorithms like Naïve Bayes or decision trees, is more effective when using data in a binary format. Thus, the initial dataset can be visualized in the form of a , with the size of the text varying according to the level of each high-incidence crime; the larger the text, the more frequently or significantly the crime occurred or was reported. The application of this method can help in identifying patterns, dominant trends, and areas of focus for more targeted law enforcement efforts or crime prevention policies.