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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Pengabdian Masyarakat Bangsa
Ahsan, Muhammad Salimy
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PREDIKSI KEBAKARAN HUTAN MENGGUNAKAN ALGORITMA NAIVE BAYES DAN KNN Ahsan, Muhammad Salimy; Zakaria, Zakaria; Hadi, Zulpan; Kurni, Samuel Everth Andrias; Kusrini
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i4.11609

Abstract

Forest fires are one of the disasters that cause problems for the environment. Forest fires can cause damage and threats, not only to forest resources but also to the entire ecosystem, both fauna and plants that can damage biodiversity and the environment of an area and can endanger human life. The source of forest fires was initially thought to come from a dry and hot environment, but in some cases, forest fires are triggered by human activities in clearing land for agriculture or other purposes. One of the factors that influence the spread of forest fires is several variables combined with humidity levels, wind speed, and rainfall. In this study, researchers used machine learning algorithms KNN and Naïve Bayes to predict forest fires and compare the results of the performance levels of each method used. The results obtained indicate that the naive Bayes method has an accuracy value of 53.33% and K-NN has an accuracy value of 62.66%
Chicken Disease Classification Based on Inception V3 Algorithm for Data Imbalance Ahsan, Muhammad Salimy; Kusrini; Dhani Ariatmanto
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 3 (2023): Article Research Volume 7 Issue 3, July 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.12737

Abstract

In order to supply the world's protein needs, one of the most crucial industries is the poultry business. The problem that often occurs in chicken farms is disease, and this can have a significant impact on the farm. The availability of large enough amounts of data makes it possible to carry out the process of monitoring chicken diseases using deep learning technology for the classification of chicken diseases. With the availability of large enough data, the dataset has a variety of features that cause problems with data clutter. To overcome the problem of data conflict, an oversampling technique is used to increase the sample data from the minority class so that it has the same value as the other majority classes, and the Inception-V3 algorithm is used to classify chicken diseases based on fecal images. The total number of data used was 8067, which were broken down into the following four categories: Healthy, Salmonella, Coccidiosis, and Newcastle disease. Data balancing was done using oversampling to get the total data to 10500 before the evaluation process was started. The data was distributed by splitting it by 80% of the data will be used for training, 10% for data validation, and 10% for testing. The results of the test, which employed Inception V3 without oversampling, produced the highest possible score of 94.05%.
Edukasi dan Pelatihan Pemrograman Dasar Menggunakan Google Colab bagi Guru SDN Klagen 4, Barat, Kec. Maospati Kab. Magetan Nugrahanti, Fatim; Sari, Eka Resty Novieta; Ahsan, Muhammad Salimy; Pasyawati, Putri Ramadhani
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 6 (2025): Agustus
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i6.2824

Abstract

Edukasi dan pelatihan ini diselenggarakan dengan tujuan untuk meningkatkan literasi digital dan kemampuan dasar pemrograman bagi guru-guru di SDN Klagen 04 Barat, Kecamatan Maospati, Kabupaten Magetan. Dalam era pendidikan berbasis teknologi, pemahaman tentang pemrograman menjadi salah satu kompetensi penting yang dapat menunjang pembelajaran abad 21. Google Colab dipilih sebagai platform pelatihan karena bersifat gratis, berbasis cloud, dan mendukung bahasa pemrograman Python yang mudah diakses serta digunakan oleh pemula. Melalui kegiatan ini, para guru diperkenalkan pada konsep dasar logika pemrograman, struktur kode Python sederhana, serta penerapan Google Colab dalam konteks pembelajaran di sekolah dasar. Metode pelatihan meliputi pemaparan materi, praktik langsung, serta diskusi dan tanya jawab. Hasil dari pelatihan menunjukkan adanya peningkatan pemahaman peserta terhadap dasar-dasar pemrograman serta motivasi untuk mengintegrasikan teknologi dalam kegiatan belajar mengajar. Diharapkan, pelatihan ini dapat menjadi langkah awal dalam mendukung transformasi digital di lingkungan pendidikan dasar.
Co-Authors DHANI ARIATMANTO Kurni, Samuel Everth Andrias KUSRINI Nugrahanti, Fatim Pasyawati, Putri Ramadhani Sari, Eka Resty Novieta Zakaria Zakaria Zulpan Hadi