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KEKUASAAN DALAM ORGANISASI POLITIK (STUDI KASUS: KELURAHAN JAMBU KARYA) Hayat, Nurul; Hardiansyah, Muhammad Agus; Rojak, Abd; Destiana, Amelia Wahyu; Yulianti, Amelia; Zahra, Marisatu; Mulyani, Sri Tika
Jurnal Kajian Pembelajaran dan Keilmuan Vol 7, No 1 (2023): APRIL 2023
Publisher : Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jurnalkpk.v7i1.63920

Abstract

This research was based on the fact that the village of Jambu Karya, Rajeg District, Tangerang Regency, Banten, Indonesia is harmonious, peaceful and peaceful, has no criminal problems and social problems that exist in other communities. This research on power in political organizations was carried out with the aim of describing the power that exists in the Jambu Karya sub-district, Rajeg District, Tangerang Regency, Banten, Indonesia. This research was conducted at the Jambu Karya village office, Rajeg District, Tangerang Regency, Banten, Indonesia. The participants in this study were the village heads of Jambu Karya Village, Rajeg District, Tangerang Regency, Banten namely Mr. Suherman. The techniques used in this study were direct observation and interviews with the help of question sheets. Based on the observation, the authors reported that political organisations in that area have run well and have followed and complied with the regulations made by the government, so that the villagers can live in peace and harmony.
Implementasi Deteksi Jenis Tanaman Herbal Dengan Model Klasifikasi Gambar Menggunakan Teachable Machine Putri, Amanda Titania; Safira, Ola; Yulianti, Amelia; Faozi, Imam; Setiawan, Retno Agus
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2025 Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2025)
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/snppkm.v4i1.1373

Abstract

Herbal plants are a source of natural ingredients widely used in traditional medicine and alternative therapies. However, the process of identifying herbal plant types is still often done manually, potentially leading to errors, especially for the general public. The aim of this research is to implement an intelligent system capable of classifying herbal plant types based on leaf images, thereby helping to identify herbal plants independently while providing educational value. The research utilizes an image dataset of several types of herbal plant leaves that were processed and trained using Google Teachable Machine. This platform facilitates training machine learning models through an image-based approach without requiring complex programming knowledge. The dataset is divided into several classes according to the type of herbal plant, and the training process is carried out by varying parameters such as epoch, batch size, and learning rate to obtain the most optimal configuration. The results of this research create a web-based intelligent system application that can effectively classify herbal plant images, provide educational information to users, and can be further developed into a practical tool for herbal plant identification. The research also highlights several challenges, such as the need for a sufficiently large and diverse dataset, variations in lighting conditions and image backgrounds, and the model's ability to perform consistently under real-world conditions.