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All Journal JMM (Jurnal Masyarakat Mandiri) Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Widiyasari, Diyah
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Health Professions Materials Science & Nanotechnology Other

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PENERAPAN SISTEM PENYIRAMAN OTOMATIS PADA PROSES PENYEMAIAN BIBIT PADI KERING BERBASIS PANEL SURYA DI DESA BODEH Priharti, Wahmisari; Widiyasari, Diyah; Setiyadi, Suto
JMM (Jurnal Masyarakat Mandiri) Vol 9, No 4 (2025): Agustus
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v9i4.32962

Abstract

Abstrak: Sistem penyemaian bibit padi kering merupakan metode alternatif yang diprakarsai oleh kelompok tani Ponco Tani di Desa Bodeh. Meskipun metode ini terbukti efektif untuk mempercepat proses penanaman dan memperbanyak hasil tanaman padi, terdapat kelemahan yaitu kebutuhan akan sistem penyiraman yang efisien dan terjadwal. Hal ini sulit dipenuhi menggunakan sumber listrik konvensional karena seringnya terjadi pemadaman yang menghambat proses penyiraman bibit.Untuk mengatasi permasalahan tersebut, kegiatan pengabdian masyarakat ini dilaksanakan untuk mengimplementasikan suatu sistem penyiraman otomatis berbasis panel surya. Pada kegiatan ini, 11 petani anggota Ponco Tani ikut dilibatkan sebagai pengguna dan diberikan sosialisasi serta pelatihan terkait cara penggunaan serta pemeliharaan sistem. Umpan balik yang diperoleh dari sosialisasi menunjukkan tingkat pemahaman sebesar 97% yang mengindikasikan bahwa sistem yang diberikan dapat dipahami serta dijaga secara mandiri oleh petani. Harapannya, sistem ini mampu menggantikan ketergantungan pada sumber listrik konvensional dan dapat terus digunakan selama 15-20 tahun ke depan untuk meningkatkan produktivitas petani bibit padi kering di Desa Bodeh.Abstract: The dry rice seedling system is an alternative method initiated by the Ponco Tani farmer group in Bodeh Village. Although this method has proven effective in accelerating the planting process and increasing rice crop yields, it has a drawback the need for an efficient and scheduled irrigation system. This need is difficult to meet using conventional electricity sources due to frequent power outages, which hinder the seedling watering process. To address this issue, this community service activity was carried out to implement an automatic irrigation system powered by solar panels. In this program, 11 farmers who are members of Ponco Tani were involved as users and received socialization and training regarding the usage and maintenance of the system. Feedback obtained from the sessions indicated a 97% level of understanding, showing that the system can be understood and maintained independently by the farmers. It is hoped that this system will replace the dependence on conventional electricity sources and continue to be used for the next 15–20 years to improve the productivity of dry rice seedling farmers in Bodeh Village.
Design and Implementation of an Organic and Inorganic Waste Detection System Using Capacitive, Inductive, and LDR Sensors with Rule-Based Classification Widiyasari, Diyah; Mukhtar, Husneni; Cahyadi, Willy Anugrah; Wijaya, Adhi Dharma Surya
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 7 No. 4 (2025): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v7i4.133

Abstract

The continuous increase in daily waste accumulation has become a major issue in many areas, primarily due to the mixing of various waste types and the lack of effective household waste management. This complicates waste processing and contributes to environmental degradation. This study aims to design and implement a practical tool for detecting organic and inorganic waste types, specifically for use by household waste collection personnel. The developed system utilizes three sensors, capacitive, inductive, and light-dependent resistors (LDR), to acquire characteristic data from different types of waste. The device is designed in the shape of a pistol to enhance mobility and ease of use by waste collection officers. For the waste-type classification system, several machine learning methods were employed, namely Adaptive Boosting (AdaBoost), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN). Based on the experimental results, AdaBoost was selected as the primary model for the waste classification system because of its superior performance in terms of cross-validation accuracy and the balance of evaluation metrics, such as precision, recall, and F1-score. Consequently, AdaBoost predictions were adopted to establish a rule-based classification logic by extracting threshold values from the most influential sensor features. This study utilized AdaBoost analysis as the foundation for rule formulation, ensuring that classification decisions were based on reliable and tested data patterns. Based on testing with several samples, the device can classify organic and inorganic waste types with an accuracy rate of 91.67%. Additionally, the tool can estimate the composition of mixed waste with an error rate of 5.06%. The presence of this device has been proven to accelerate and simplify the waste-sorting process, thereby increasing the efficiency of household waste management.
Co-Authors Husneni Mukhtar Suto Setiyadi Wahmisari Priharti Wijaya, Adhi Dharma Surya Willy Anugrah Cahyadi