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All Journal International Journal of Artificial Intelligence Research INDONESIAN JOURNAL OF URBAN AND ENVIRONMENTAL TECHNOLOGY
Wibowo, Fauzy Satrio
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Energy Environmental Science

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SMART WEIGHING FOR WASTE MANAGEMENT SYSTEM USING INTEGRATION INTERNET OF THINGS AND ARTIFICIAL INTELLIGENCE TO ASSIST CIRCULAR ECONOMICS Sendari, Siti; Mokthar, Norrima binti; Ramadan, Bimastyaji Surya; Ramadani, Bakhrul Mukhid Fadilah; Pramesti, Fadila Claudia; A'ini, Qurrotul; Wibowo, Danang Arengga; Sucipto, Putra Wisnu Agung; Rahmawati, Yuni; Wibowo, Fauzy Satrio
INDONESIAN JOURNAL OF URBAN AND ENVIRONMENTAL TECHNOLOGY VOLUME 8, NUMBER 2, OCTOBER 2025
Publisher : Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/urbanenvirotech.v8i2.23959

Abstract

Aims: This study was aimed to Supit Urang Landfill in Malang, East Java, Indonesia, urgently needs a smart waste management system because it is strategically important as a large landfill with a monthly operating capacity of 4.560 trucks. Landfill management is very challenging due to some cases, such as overcapacity, inefficient waste sorting, and environmental risks. Methodology and results: The research introduced an integration of Internet of Things (IoT) and Artificial Intelligence (AI) into the waste management system to support the principles of a circular economy. IoT was applied for real time monitoring of waste conditions, while AI was utilized for big data analytics, enabling predictions, decision-making support, and policy recommendations. The results demonstrated that the proposed system improves efficiency and cost-effectiveness by reducing the amount of waste disposed of in the landfill and optimizing the waste sorting and recycling process. Conclusion, significance and impact study: The study concludes that the transformation toward a sustainable waste management model is urgently needed and can be achieved through AIoT integration. This innovation supports circular economy practices by enhancing waste reduction, reuse, and recycling. The successful implementation at Supit Urang could serve as a scalable model for other landfills across Indonesia, thereby contributing to national strategies for sustainable waste management. This technological intervention not only improves environmental outcomes by reducing pollution and conserving resources but also fosters economic development through efficient resource utilization and job creation in the recycling and waste processing sectors.
Applied of Analytical Hierarchy Process and Fuzzy Time Series in Hybrid for Optimizing Smart Vertical Farming with Multi-Variety Plants Wibowo, Danang Arengga; Sendari, Siti; Wibawa, Aji Prasetya; Wibowo, Fauzy Satrio
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.402

Abstract

Vertical Farming is a kind of modern agricultural methods, where the structure of growing racks are arranged upwards. This method aims to optimize the use of agricultural space. There are many plants, which are suitable to be planted for vertical farming, such as Strawberry, Tomatoes, Celery, Chili, Mint, Chives, Kuchay, Spinach, and Water spinach. The problem, which is studied in this paper, is how to control the environments of vertical farming with multi-variety plants. This paper proposed a hybrid method of Analytical Hierarchy Process and Fuzzy Time Series AHP-FTS, that is, plants with similar characteristics are placed at the same block area determined by the method of Analytical Hierarchy Process (AHP). Furthermore, controlling the environments regarding the needs of appropriate growing parameters for multi-variety plants, the Fuzzy Time Series (FTS) method is used. Then, time variable for activating actuators could be adjusted as a multi-control system. The effectiveness of the proposed method was evaluated with 365 record data in 12 months. The result shows that the AHP was successful to determine the multi-criteria to determine the zone and priority of plants. The second stage is that the FTS predicts the temperature to determine time variable for activating actuators, and the third stage is the implemented AHP-FTS as a hybrid system to evaluate the vertical Farming system. The results show that the proposed system works well as hybrid system of AHP-FTS
Co-Authors A'ini, Qurrotul Agung Sucipto, Putra Wisnu Aji Prasetya Wibawa Mokthar, Norrima binti Pramesti, Fadila Claudia Ramadan, Bimastyaji Surya Ramadani, Bakhrul Mukhid Fadilah Siti Sendari Wibowo, Danang Arengga Yuni Rahmawati