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All Journal JOIV : International Journal on Informatics Visualization Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Juisi (Jurnal Informatika dan Sistem Informasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Information Technology (JIfoTech) Jurnal Abdimas Bina Bangsa DEVOTE: Jurnal Pengabdian Masyarakat Global Jurnal INFOTEL SAINTEK Infact: Jurnal Sains dan Komputer DEVOTE: Jurnal Pengabdian Masyarakat Global
Haeni Budiati
Universitas Kristen Immanuel
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi

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Penerapan ESP32-CAM dan TinyML dalam Klasifikasi Gambar Buah dan Sayuran Johni Revormasi Ziliwu; Gogor C Setyawan; Haeni Budiati
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 1: April 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i1.1869

Abstract

The classification of fruit and vegetable images still requires high costs, posing challenges in developing efficient solutions. Fruits and vegetables are crucial in healthy food, so efficiency in managing their images impacts the agricultural industry. The aim of this study is to apply ESP32-CAM and TinyML in Fruit and Vegetable Image Classification with efficiency and low cost. The method involves Edge Impluse Studio and training the model with Convolutional Neural Network (CNN). From the testing, the F1 score accuracy reached 68.3% for each class of fruit and vegetables. From the demonstration using ESP32-CAM, the obtained accuracies are Apple (89%), Banana (91%), Orange (89%), Carrot (83%), and Cabbage (66%). The results indicate that applying ESP32-CAM and TinyML has the potential to improve efficiency and reduce costs in managing images.Keywords: ESP32-CAM; TinyML; Image Clasification; Fruit and Vegetables; Solution Efficiency; AbstrakPengklasifikasian gambar buah dan sayuran masih memerlukan biaya yang tinggi, sehingga menghadirkan kesulitan dalam mengembangkan solusi yang efisien. Buah dan sayuran penting dalam makanan sehat, sehingga efisiensi dalam pengelolaan gambar mereka berdampak pada industri pertanian. Tujuan penelitian ini adalah menerapkan ESP32-CAM dan TinyML dalam Klasifikasi Gambar Buah dan Sayuran dengan efisiensi dan biaya rendah. Metode melibatkan Edge Impluse Studio dan pelatihan model dengan Convolutional Neural Network (CNN). Dari pengujian, akurasi F1 score mencapai 68.3% untuk setiap kelas buah dan sayuran. Dari demonstrasi menggunakan ESP32-CAM, akurasi yang diperoleh adalah Apel (89%), Pisang (91%), Jeruk (89%), Wortel (83%), dan Kubis (66%). Hasil menunjukkan penerapan ESP32-CAM dan TinyML memiliki potensi untuk meningkatkan efisiensi dan mengurangi biaya pengelolaan gambar. 
Analisis Sentimen Opini Masyarakat Terhadap Presiden Jokowi Sebelum Dan Sesudah Pilpres 2024 Menggunakan Metode Naive Bayes Classification Pius Hermanto Nehe; Sunneng Sandino Berutu; Haeni Budiati
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 1: April 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i1.1841

Abstract

The 2024 presidential election in Indonesia is an important moment in political dynamics. This research analyzes changes in public sentiment towards President Jokowi before and after the 2024 Presidential Election using the naive bayes classification method. Datasets consist of 10,014 tweets that have gone through the process of crawling, preprocessing, translating, labeling, classification, and model evaluation. The analysis results show that before the 2024 presidential election, positive sentiment reached 41.17%, neutral sentiment 34.30%, and negative sentiment 24.53%. After the 2024 presidential election, positive sentiment decreased to 39.08%, neutral sentiment increased to 37.59%, and negative sentiment decreased to 23.33%. Prediction accuracy increased to 64 and neutral sentiment had a precision of 88, with a dataset focusing on President Jokowi after the 2024 Presidential Election, while recall for positive sentiment was 87, and f1-score for neutral sentiment was 69, with a dataset of President Jokowi before the 2024 Presidential Election. Keywords: Presiden Jokowi; Public opinion dynamics; Naive Bayes Classification; Presidential Election 2024; Sentiment AbstrakPemilihan Presiden 2024 di Indonesia merupakan momen penting dalam dinamika politik. Penelitian ini menganalisis perubahan sentimen publik terhadap Presiden Jokowi sebelum dan sesudah Pilpres 2024 dengan menggunakan metode klasifikasi naive bayes. Datasets terdiri dari 10.014 tweets yang telah melalui proses crawling, preprocessing, translating, labeling, classification, dan evaluation model. Hasil analisis menunjukkan bahwa sebelum Pilpres 2024, sentimen positif mencapai 41,17%, sentimen netral 34,30%, dan sentimen negatif 24,53%. Setelah Pilpres 2024, sentimen positif menurun menjadi 39,08%, sentimen netral meningkat menjadi 37,59%, dan sentimen negatif menurun menjadi 23,33%. Akurasi prediksi meningkat menjadi 64 dan Sentimen netral memiliki precision 88, dengan dataset yang berfokus pada Presiden Jokowi setelah pelaksanaan Pilpres 2024, sementara recall untuk sentimen positif adalah 87, dan f1-score untuk sentimen netral adalah 69, dengan dataset Presiden Jokowi sebelum Pilpres 2024.
Co-Authors A. R. Himamunanto Agus Dirgahayu Zendrato Agustinus Rudatyo Himamunanto Anan Sosmita Lase Antonius Bima Murti Wijaya Apriani Apriani Barita Suci Vernando Zebua Delima Zai Farelia Devi Julia Putri Fornieli Gulo Gogor C Setyawan Gogor Christmass Setyawan Heri Wijayanto Hermas Rizzal Indriyani Hulu Jatmika Jatmika Jatmika Johni Revormasi Ziliwu Joseph Supriadi Juli Supriyanto Gea Kristian Juri Damai Lase Liefson Jacobus, Liefson Lukas Agung Heriputranto Peter1 Pius Hermanto Nehe Sunneng Sandino Berutu Surjawirawan Dwiputranto Timothy Ageng Pracaya Yeong-Chin Chen Yo’el Pieter Sumihar