This research examines the Jegingger, novel written by Ahmad Tohari (JAT) which highlights the banal life of a family (palm trees climbers). JAT was re-narrated as exploiting the tension between the economy and family ties, whether ideally economic activities are separate (industrial economy) or integrated with the family (subsistence). Cultural establishments are mutually contested: the subsistence culture of traditional society is challenged by the productive economy, or conversely, the productive economy is challenged by the banal subsistence economy of traditional society. The methodology of postclassical narratology—exploring and explaining cultural manifestations and then exposing chronological sequences-was used to structure the vulnerability or resilience of banal communities in maintaining social ties. A subsistence economy with its characteristics of low productivity because it tends to be a cultural activity—not economic. It contains vulnerabilities seen from two sides: 1) banal agencies that do not have literacy and competence in carrying out subsistence professions have the potential to commit malpractice; 2) low productivity limits access to health facilities. These two weaknesses become obstacles to maintaining social ties. Sacrilege—abuse of sacred symbols—which was triggered by the malpractice of coconut climbing, has caused social disorganization—the loss of basic family and community affection—becoming a hub for the idea of raising awareness of the importance of the power of knowledge and materials in supporting traditional community ties. Mastery of material, especially in massive amounts (1.5 billion diamond necklaces), can transform a banal agency into a powerful one.

Technological advancements are transforming agriculture, yet adoption rates among agricultural extension officers, especially in regions like West Java, remain modest due to several challenges. This study applies the Technology Acceptance Model (TAM) to investigate factors influencing the adoption of agricultural technologies by agricultural extension officers in West Java. Specifically, we explore the role of socialization, training, access to technology, cost, perceived ease of use, and perceived usefulness in shaping behavioral intention and actual adoption. Data were collected from 295 agricultural extension officers via structured surveys and analyzed using SmartPLS 4 software. The findings indicate that socialization and training collectively enhance both perceived ease of use and perceived usefulness, while Technology Investment Worth specifically enhances perceived usefulness by emphasizing the value of the investment. Access to technology also plays a critical role in increasing ease of use perceptions. Both perceived ease of use and usefulness positively influence behavioral intention, which in turn is a strong predictor of actual adoption. The results provide valuable insights for policymakers aiming to increase technology uptake among agricultural extension officers, promoting sustainable agricultural practices through improved access, support, and cost reduction initiatives.

Industrial zones require careful and meticulous planning because industry can have a major impact on the surrounding environment. The research location is the northern part of West Java Province which is a gold triangle area named Rebana Triangle Area. The purpose of this study is to measure the weight of the research variables in determining industrial zones from the results of fuzzy analytical hierarchy process (F-AHP) analysis, assessing the location of industrial zones in the research area based on important variables in determining industrial zones. The result of this study is the weight of the research variables in determining the industrial zone from the results of the fuzzy analytical hierarchy process (F-AHP) analysis obtained is the availability of electrical infrastructure with an influence weight of 15.00%. The second most influential factor is the availability of telecommunications infrastructure with an effect of 13.02%, the distance of land to roads and access of 11.76%, land use of 11.21%, distance of land to public facilities of 9.99%, labour cost work is 9.60%, the distance of land to the river is 8.19%, the price of land is 7.97%, the slope is 6.79%, and the type of soil is 6.43%. This GIS analysis model can be a reference model for the government in determining the potential of industrial zones in other regions in Indonesia. A total of 4822.41 Ha or the equivalent of 3.50% of the total area of 6 (six) regencies/cities research areas which are very suitable to be used as industrial zones. The district that has the largest area of potential industrial zone is Majalengka, while Cirebon does not have a location that has the potential for industrial zone locations. Based on the results of the analysis of 10 (ten) variables for determining industrial zones from expert opinion, a draft policy proposal for the government can be proposed, among others. These 10 (ten) variables are variables that are expected to be mandatory variables in planning and determining the location of potential industrial areas.

This study aims to identify and the implementation of ASN Management policies on career development aspects based on the merit system in the West Java Provincial Government and 6 Regency/City Governments in West Java Province. The failure of the institutionalization of the meritocratic system in ASN career development is partly triggered by the symptoms of the appointment or selection of officials in the central and regional levels not based on their professionalism or competence except for subjective considerations, political ties, close relationships and even bribery. This study uses a qualitative method with a descriptive approach. The operationalization concept in this study uses Merilee S. Grindle's Policy Implementation theory which consists of dimensions of policy content and its implementation context. The factors that cause the implementation of the policy to be less than optimal include: 1. Uneven understanding of meritocracy; 2. Slowness/unpreparedness in synchronizing central and regional rules/policies; 3. The information integration system between the center and regions has not yet been implemented; 4. Limited supporting infrastructure; 5. Limited permits for related officials; 6. Transparency; 7. Collaboration across units/agencies; 8. External intervention; 9. Use of information systems/technology. To optimize these factors, an Accelerator of Governmental Unit's Success (AGUS) model was created, which is a development of the Grindle policy implementation model with the novelty of adding things that influence implementation, including top leader's commitment and wisdom, effectiveness of talent placement, on-point human development, technology savvy, cross-unit/agency collaboration, and monitoring and evaluation processes.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.