AJIE (Asian Journal of Innovation and Entrepreneurship)

Creative Industries’ Perspectives on AI’s Potential Impact on Creative Jobs: Qualitative Study on Creative Professionals in Yogyakarta and Surrounding Areas

2026-05-19T01:13:02+00:00

The widespread uses of AI in creative industries are unavoidable. Thus, the impacts of AI on human jobs in creative industries are very intriguing to be investigated. This study aims to explore the perspectives of creative professionals regarding to AI’s impacts on human jobs in their respective industries. The qualitative data collected from in-depth interviews on 10 creative professionals are analyzed using thematic analysis approach. Our analysis resulted in eight main themes and 18 categories. There are four important findings to be highlighted from this study. First of all, the positive and negative impacts of AI depend on the quality of human resources. Secondly, the positive and negative impacts of AI also depend on individual’s wisdom and mindset. Third, in principle, AI is merely assistive tools for human and the uses of AI are optional and depending on human’s need. Finally, the diverse opinion about AI’s impact might be influenced by human’s role in the economic system.

Analisis Studi Kelayakan Rencana Pembangunan Tempat Pengolahan Sampah Terpadu (TPST) Kabupaten Kapuas Hulu, Provinsi Kalimantan Barat

2026-03-09T01:43:23+00:00

Population growth and increased activity have a direct impact on the increase in the amount and composition of waste produced by a region, requiring an effective and efficient waste management system. The development of an Integrated Waste Management Facility (TPST) is one alternative that can be implemented to address this issue. However, the construction of an ISWMP requires a significant investment, so it needs to be based on a comprehensive feasibility analysis in terms of environmental, technical, and economic aspects so that the facility can operate sustainably. This study aims to analyze this feasibility so that the ISWMP in Kapuas Hulu Regency can be built and operated until 2045. The methods used are population projection analysis until 2045, waste generation and composition projection analysis, assessment of alternative waste management technologies using a scoring method, and economic and financial feasibility analysis including Net Present Value (NPV), Internal Rate of Return (IRR), Benefit Cost Ratio (BCR), and Pay Back Period (PP). The analysis results show that the population of Kapuas Hulu Regency is projected to increase to 310,866 people by 2045, with waste generation reaching 57.95 tons/day. The composition of waste is dominated by food waste and plastic waste. Based on the technology scoring results, the recommended treatment system is a combination of BSF (Black Soldier Fly) maggots and Open Windrow composting for organic waste, Material Recovery Facility (MRF) for inorganic waste, and incineration for residual waste treatment. The economic and financial feasibility analysis shows that the TPST plan is feasible to implement, as indicated by an NPV > 0, an IRR of 112% exceeding the discount rate, a BCR > 1, and a PP shorter than the economic life of the plan. Based on these research results, the planning for the construction of the Kapuas Hulu Regency TPST is feasible from an economic and financial perspective and is therefore recommended as a long-term waste management solution.

Pemetaan Infrastruktur Pengelolaan Sampah Berbasis Masyarakat (PSBM) Menggunakan Sistem Informasi Geografis (SIG) dengan Wilayah Studi di Kabupaten Sleman, Yogyakarta

2026-04-01T03:28:05+00:00

The population growth in Sleman Regency has led to an increase in waste generation, necessitating an effective and participatory management system. This study aims to map the distribution of Community-Based Waste Management (CBWM) infrastructure, such as TPS3R, waste banks, and "waste donation" programs, and to evaluate their distribution and effectiveness using Geographic Information Systems (GIS). A descriptive quantitative method with a spatial approach was employed using QGIS software. Data analysis utilized overlay, buffering, and nearest neighbor analysis to evaluate the spatial service coverage. The results indicate a significant surge in the number of facilities, rising from 234 units in 2022 to 508 units in 2025; however, the distribution remains uneven. Population density significantly influences this distribution, where Ngaglik District, with the highest density (202 people/ha), still possesses a sub-optimal facility ratio compared to other regions. This study recommends spatial evidence-based priority zoning, including the establishment of a 500-meter service buffer in densely populated settlements and the revitalization of inactive units. These mapping results are expected to serve as a framework for more measurable and sustainable policy-making and evaluation of waste management in Sleman Regency