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Waste Management Model in Gamalama Village Ternate City Nini, Wa; Pobela, Elva
Jurnal Geografika (Geografi Lingkungan Lahan Basah) Vol 5, No 1 (2024): GEOGRAFIKA
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jgp.v5i1.12330

Abstract

This research aims to identify waste management models and public perceptions about waste in Gamalama Village, Central Ternate City. This research used a qualitative descriptive. Data collection was carried out through interviews, questionnaires, documentation and testing the validity of the data using the triangulation method. The research results show that the volume of waste in Gamalama sub-district increased by 514,834 m3/day, and 187,914,319 m3/year. Waste management still uses the old model, namely picking up the source of the waste at the TPS and continuing it to the TPA. This risks of accumulation waste made people have a negative perception about waste management in Gamalama sub-district. Gamalama Village should implement the 3 R model (reuse, reduce and recycle) which can process waste into useful and economically valuable goods, and ultimately waste can be handled from upstream to downstream. 
Identification of Smart Environment Readiness in Realizing Smart City Kotamobagu Nini, Wa; Anripa, Nuralfin; Alian, La Ode; Maulana, Muh Vikky
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.646

Abstract

This study aims to identify the readiness of the innovative environment in realizing an intelligent city. A descriptive qualitative approach combined data collection techniques such as in-depth interviews, observation, and documentation. Primary data were obtained directly in the field through observation and interviews with diverse respondents. Secondary data were obtained from the Kotamobagu Environmental Service and the Kotamobagu PUPR Service. Data analysis was conducted through four stages: data collection, data reduction, data display, and conclusion drawing. The study results revealed that five innovative environment indicators were adequately met: the feasibility of water channels, irrigation channels, green space planning, water and air quality, and waste management systems. One indicator, the use of environmentally friendly energy resources, was not met. The study recommends that the Kotamobagu government develop policies or programs to build renewable energy resources to support the intelligent environment and realize Kotamobagu's smart city vision.