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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) SemanTIK : Teknik Informasi JURNAL INTEGRASI Indonesian Journal of Artificial Intelligence and Data Mining JURNAL PENGABDI Journal of Applied Data Sciences Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen JAIA - Journal of Artificial Intelligence and Applications J-Icon : Jurnal Komputer dan Informatika The Indonesian Journal of Computer Science
Firdaus, Muhammad Bambang
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Implementation of Naïve Bayes Gaussian Algorithm for Real-Time Classification of Broiler Cage Conditions Rosmasari, Rosmasari; Prafanto, Anton; Firdaus, Muhammad Bambang
Journal of Applied Data Sciences Vol 6, No 3: September 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i3.694

Abstract

Monitoring large-scale broiler farms poses considerable challenges due to the variable nature of environmental conditions, which have a direct impact on poultry health and productivity. This study proposes a real-time classification system for broiler house conditions, utilizing the Naïve Bayes Gaussian algorithm in conjunction with the Internet of Things (IoT) technology. The system has been developed to address the limitations of manual monitoring by automating the collection of temperature, humidity, and ammonia data through BME-680 and MICS-5524 sensors, which are strategically positioned 30 cm from the floor to optimize ammonia detection. Utilizing a dataset comprising 865 records, meticulously divided into 75% for training (648 records) and 25% for testing (217 records), the model attained an accuracy of 82.03%, a precision of 75.67%, a recall of 82.67%, and an F1-score of 77.67%. A comparative analysis was conducted, which demonstrated significant advantages over alternative classification methods, with Decision Trees achieving 79.5% accuracy and Support Vector Machines reaching 80.8%. The innovation lies in the integration of automated condition classification into an IoT system, enabling rapid responses to environmental changes with processing times of approximately 500 milliseconds from sensing to classification. The system demonstrated an accuracy of 178 data points, with a misclassification rate of 39 out of 217 test samples. The strategic placement of sensors at a height of 30 cm optimizes ammonia detection while ensuring accurate temperature and humidity readings. The system provides historical data, enabling farms to analyze long-term environmental trends, and thereby support data-driven decision-making strategies to enhance broiler welfare and operational efficiency. Usability testing with five poultry farm operators confirmed the dashboard's intuitive design, though recommendations for visual alerts for critical ammonia levels were suggested for future iterations.
Analisis Pilkada Medan pada Sosial Media Menggunakan Analisis Sentimen dan Social Network Analyisis Anam, M. Khairul; Firdaus, Muhammad Bambang; Fitri, Triyani Arita; Lusiana; Agustin, Wirta; Agustin
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i1.3027

Abstract

The simultaneous regional head elections were over, but during the campaign until it was decided to become regional head there were many comments, both pro and contra. The city of Medan is one of the regions that will hold the 2020 ELECTION during the pandemic. The Medan City Election has decided that the pair Bobby Nasution and Aulia Rachman have won. This victory certainly gets a variety of comments on social media, especially Twitter. This study conducts sentiment analysis to see the sentiment that occurs, namely seeing negative, positive, or neutral comments. This sentiment analysis uses two methods to see the resulting accuracy, namely Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC). This study also looks at the interactions that occur using Social Network Analysis (SNA). In addition to sentiment analysis and SNA, this study also looks at the existence of BOT accounts used in the #PilkadaMedan. The results obtained from the sentiment analysis show that NBC has the highest accuracy, which is 81, 72% with a data proportion of 90:10. Then on SNA, the @YanHarahap account got the highest nodes, namely 911 nodes. Then from 10326 tweets, 11% were suspected of being BOT by the DroneEmprit Academic system.
Rancang Bangun Aplikasi Mobile Crowdfunding untuk Donasi Sosial Kota Samarinda Firdaus, Muhammad Bambang; Efendy, Muhammad Yusuf; Prafanto, Anton; Rosmasari, Rosmasari; Suandi, Fadli; Lathifah, Lathifah
JURNAL INTEGRASI Vol. 16 No. 1 (2024): Jurnal Integrasi - April 2024
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v16i1.5083

Abstract

Donations are physical gifts made by individuals or legal entities that are given voluntarily and without imbalance. Advances in internet technology are now used to raise social and humanitarian funds and help victims of natural disasters. Crowdfunding takes advantage of this situation, because it uses the internet to generate funds from internet and social media users. This research will look at how to create an Android-based crowdfunding contribution application management system for the Samarinda City area. This study intends to use the Rational Unified Process technique to create an Android-based fundraising application for flood victims, fires of religious buildings, and social institutions in Samarinda City. The main goal is to create software that fits the needs of users. It not only meets system specifications and is usable but also validates whether the system is acceptable. In accordance with the objectives of this study, researchers succeeded in building a donation-raising application for disaster victims, and based on the results of functional testing with the Black Box, the Samarinda City Donation Application has an attractive appearance, the menus available in the application are easy to understand, and the Samarinda City Donation Application this is good enough.
Co-Authors Agustin Anam, M Khairul Arba, Muhammad Hendra Budiman, Edy Efendy, Muhammad Yusuf Efrizoni, Lusiana Elva, Yesri Gunawan, Chichi Rizka Halim, Muhammad Yusuf Hamdani Hamdani Haviluddin Haviluddin Ikhsan Ikhsan Irsyad, Akhmad Irwanda Syahputra Karfindo, Karfindo Lathifah, Lathifah Lusiana Mahessya, Raja Ayu Munawir Munawir Nupa, Joy Disanto Nurul fadillah, Nurul Pandu Pratama Putra, Pandu Pratama Prafanto, Anton Puspitasari, Novianti Rio Andika Malik Rosmasari Rosmasari, Rosmasari Saragih, Muhammad Nabil Sari, Atalya Kurnia Sarjon Defit Setiawan, Maulana Agus Suandi, Fadli Sumijan Sumijan Taruk, Medi Tejawati, Andi Teri Ade Putra Tri Putri Lestari, Tri Putri Triyani Arita Fitri Wahyudianto, Mochamad Rizky Waksito, Alan Zulfikar Wati, Masna Wirta Agustin Zainal Arifin