Article Per Year (5 Year)
p-Index From 2021 - 2026
0.778
P-Index
This Author published in this journals
All Journal IJID (International Journal on Informatics for Development) West Science Agro GABBAH : Jurnal Pertanian Dan Perternakan Cahaya Pengabdian
Efendi, Burhan
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Education Social Sciences Other

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Cerdas Digital dengan Artificial Intelligence: Solusi Teknologi untuk Pelayanan dan Keamanan Publik Tristanti, Novi; Fanani, Galih Pramuja Inngam; Romadloni, Nova Tri; Efendi, Burhan; Setiani, Hani
Cahaya Pengabdian Vol. 2 No. 1 (2025): Juni 2025
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/cp.v2i1.207

Abstract

Artificial intelligence (AI)-based digital technology presents both opportunities and challenges for village security officers, particularly Village Supervisory Non-Commissioned Officers (Bhabinkamtibmas), in addressing the spread of hoaxes and meeting the demands for fast and efficient public services. The low level of digital literacy and practical skills in utilizing AI at the village level prompted the implementation of a community service program titled “Digital Intelligence with Artificial Intelligence: Technological Solutions for Public Service and Security.” This program aimed to enhance Bhabinkamtibmas’s understanding and ability to apply AI in public service and village security. The method used was a combination of theoretical and practical training for 30 Bhabinkamtibmas participants, covering three main topics: chatbot utilization for public services, face recognition for security support, and AI-based hoax content detection. Effectiveness was evaluated through pretest and posttest assessments. The results showed an average improvement of 40%, with posttest scores reaching 85% for chatbot usage, 80% for face recognition, and 75% for hoax detection. These findings demonstrate that practice-based training effectively improves Bhabinkamtibmas’s digital literacy and technical skills. In conclusion, this program successfully equips Bhabinkamtibmas as digital literacy agents capable of leveraging AI to strengthen public services and village security, contributing to the development of an adaptive Smart Policing ecosystem in the digital era.
Effect of Dosage of Bokashi Organic Fertilizer on Agronomic Growth and Productivity of Rice Plants (Oryza sativa) Efendi, Burhan; Haryono, Haryono; Mariay, Ivonne Fitri; Andriyani, Liz Yanti; Sarungallo, Amelia S.
West Science Agro Vol. 2 No. 04 (2024): West Science Agro
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsa.v2i04.1451

Abstract

This systematic literature review examines the effects of Bokashi organic fertilizer dosage on rice plants' agronomic growth and productivity (Oryza sativa). Using 16 Scopus-indexed articles, the study synthesizes findings on how Bokashi impacts key agronomic parameters such as plant height, tiller number, biomass production, and grain yield. The review highlights that optimal dosages (5–10 tons/ha) consistently improve growth and yield outcomes compared to chemical fertilizers or untreated controls. Bokashi's nutrient-rich composition and ability to enhance soil health and microbial activity make it a sustainable alternative for rice cultivation. However, its effectiveness depends on soil type, environmental conditions, and rice variety. Challenges related to dosage standardization and large-scale implementation are identified, and recommendations for future research are provided. This review underscores the potential of Bokashi in promoting sustainable agriculture while reducing reliance on synthetic inputs.
Analisis Swot Dan Soar Dalam Mewujudkan Domba Unggul Indonesia Melalui Persilangan Dorper Dengan Domba Lokal Efendi, Burhan; Al Wahid, Zainudin; Andri Atmoko, Bayu
GABBAH : Jurnal Pertanian Dan Perternakan Vol. 1 No. 4 (2024): Juli
Publisher : PT PUBLIKASI INSPIRASI INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62017/gabbah.v1i4.1728

Abstract

Industri peternakan di Indonesia memainkan peran penting dalam menyediakan protein hewani dan mendukung penghidupan petani kecil. Namun, pertumbuhan populasi peternakan di negara ini masih tertinggal, sehingga membatasi kemampuan negara tersebut untuk memenuhi meningkatnya permintaan daging dan produk hewani lainnya dalam negeri. Untuk mengatasi tantangan ini, penelitian ini menggunakan analisis SWOT (Strengths, Weaknesses, Opportunities, and Threats) dan SOAR (Strengths, Opportunities, Aspirations, and Results) untuk mengeksplorasi potensi persilangan domba Dorper, ras yang sangat produktif, dengan domba lokal Indonesia untuk mendorong pertumbuhan populasi ternak yang unggul. Analisis SWOT mengungkapkan beberapa kekuatan, seperti tersedianya bibit domba lokal dengan sifat-sifat yang diinginkan, meningkatnya permintaan daging, dan dukungan pemerintah terhadap pengembangan peternakan. Kesimpulan disajikan untuk memandu penerapan strategi ini secara efektif.
A Hybrid Approach of Pearson Correlation and PCA in Feature Selection for Opinion Mining Tri Romadloni, Nova; Kurniawan, Wakhid; Ariyadi, Muhammad Yusuf; Efendi, Burhan
IJID (International Journal on Informatics for Development) 2025
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study proposes a hybrid feature selection approach that combines Pearson Correlation and Principal Component Analysis (PCA) to improve classification performance in opinion mining tasks. The rapid growth of e-commerce on social media platforms, such as TikTok, has generated a significant volume of user-generated reviews, which are valuable sources of consumer sentiment. However, the high dimensionality of textual data poses challenges in achieving accurate sentiment classification. To address this issue, the proposed method first applies Pearson Correlation to remove irrelevant features with weak correlation to sentiment labels, followed by PCA to reduce dimensionality. The dataset consists of user reviews from the TikTok Seller platform. Experiments using SVM, Naive Bayes, and Random Forest show that the hybrid approach achieves the highest accuracy of 86.2% (SVM and RF), improving over PCA-only by +0.9% and recovering 13.8% accuracy loss for Naive Bayes (from 72.0% to 83.1%). The results demonstrate that integrating correlation- and projection-based methods yields a more compact and effective feature set. This approach is especially suited for opinion mining in noisy, high-dimensional e-commerce data.
Co-Authors Al Wahid, Zainudin Andri Atmoko, Bayu Fanani, Galih Pramuja Inngam Hani Setiani Haryono Haryono Kurniawan, Wakhid Liz Yanti Andriyani Mariay, Ivonne Fitri Muhammad Yusuf Ariyadi Nova Tri Romadloni Sarungallo, Amelia S. Tristanti, Novi