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Machine Learning-Based Compost Maturity Prediction Using Multisensor IoT Data Siti Rokhmah; Ihsan Cahyo Utomo
International Journal of Computer and Information System (IJCIS) Vol 7, No 3 (2026): IJCIS : Vol 7 - Issue 3 - 2026
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v7i3.299

Abstract

Conventional composting process monitoring still faces various limitations, particularly in determining the level of compost maturity, which generally relies on visual observation and operator experience. The development of Internet of Things (IoT) technology enables real-time multisensor data acquisition during the decomposition process, but most research still focuses on developing monitoring systems without utilizing the resulting data to build predictive models. This study aims to develop a Machine Learning-based compost maturity prediction model using a multisensor dataset obtained from an IoT-based Smart Composting Bin system. The data used includes environmental parameters that affect the composting process, such as temperature, humidity, media moisture, and gas concentrations that are recorded periodically. The research stages include data preprocessing, handling missing data and outliers, normalization, feature selection, Random Forest model training, and performance evaluation using metrics appropriate to the prediction target type. To increase model transparency, this study also applies Explainable Artificial Intelligence through SHAP analysis to identify the contribution of each sensor parameter to the prediction results. The expected results show that the Machine Learning approach is able to predict the level of compost maturity with high accuracy while identifying the most influential environmental factors during the decomposition process. This research contributes to the utilization of IoT data not only as a monitoring medium, but also as a basis for intelligent decision-making in data-based organic waste management systems, thereby supporting the implementation of smart waste management and the concept of a circular economy.
Co-Authors Afiqoh Akmalia Fahmi Ahmada Auliya Rahman Al Farisi, Mu’taz Aldin Nasrun Minalloh Alfian Yulianto Ali Zainal Abidin Amalia Fatmasari Ardiyanto, Yunita Arif Surya Kusuma Aris Rakhmadi Asy Syifaur Roisah Rufaida Atmadja, Syifaturrobbani Maeda Azzahra, Daniel Darmanto Darmanto Darmanto Darmanto Dedi Gunawan Devi Afriyantari Puspa Putri Dewi Sasika Rani Dewita Puspawati Diah Priyawati Dimas Aryo Anggoro Dinova, Calvin Alvito Dwi Anto Punguh Widodo Dwiki Reza Nova Alvianto Fadhilah Ismarani Fatah Yasin Al Irsyadi fatah yasin irsyadi, fatah yasin Gallant Smart, Victor Ghurrotun Niswah Kafi Haidar Aulia Rahman Helmi Imaduddin Heru Supriyono Huda Kurnia Maulana Keisha Jenny Maulida Nugraha Khanun Roisatul Ummah Kojyro, Hyuga Dewanto Kun Harismah Kurnia Rina Ariani Kussudyarsana Lintang Kurniawati Mahendra, Galuh Raka Makkahani, Kiatina Maryam Maryam Muhammad Fahmi Johan Syah Muhammad Halim Maimun Muhammad Randhy Kurniawan Muhammad Randhy Kurniawan Muhammad, Baihaqi Fatah Mujazin Muqorobin Muqorobin Mursetyani, Dhea Muslihah, Isnawati Nabil Aziz Bima Anggita Nendy Akbar Rozaq Rais Nisaa, Salma Khirun Novel Idris Abas Novendius Eka Saputra Putri, Felissa Auriel Rahmalia Putri, Salwa Qurrota A'yun Qanza, Aiza Fravy Ragiel Abiul Pratama Rais, Nendy Akbar Rozaq Raissa Mayla Jasmine Ramadhan, Muhammad Rivai Putra Reisya Rahmadani Riani, Lencia Putri Septa Rusnilawati Sabiila, Yuwhay Jahdan Sania Citra Palupi Saputra, Novendius Eka Septa Riani, Lencia Putri Siti Rokhmah Siti Rokhmah Siti Rokhmah Siti Rokhmah Siti Rokhmah Syafi’uddin, Muhammad Wahyu Syafi’udin, Muhammad Wahyu Titis Setyabudi Umi Fadlilah Widi Widayat Widi Widayat Yunita Ardiyanto Yusuf Sulistyo Nugroho Yusuf Sulistyo Nugroho