Artikel ditulis seluruhnya berdasarkan judul, abstrak, pengantar referensi, dan sesuai template International Conference of Artificial Intelligence and Information Technology (ICAIIT) 2019 yang diterbitkan oleh IEEE. Untuk izin mencetak ulang atau menerbitkan ulang, silakan kirim email ke Manajer Hak Cipta IEEE di pubs-permissions@ieee.org. Universitas Atma Jaya Yogyakarta, Indonesia) o Paulus Mudjihartono, S.T., M.T. Universitas Atma Jaya Yogyakarta, Indonesia) atau Kusworo Anindito, S.T., M.T. Universitas Atma Jaya Yogyakarta, Indonesia) o Universitas Y. Atma Jaya Yogyakarta, Indonesia) o Harya Bima Dirgantara S.Kom., M.T.I.
Mujiono Sadikin (Universitas Mercu Buana, Indonesia) atau Ionia Veritawati, S.Si., M.T. Universitas Pancasila, Indonesia) o Febri Maspiyanti, S.Kom., M.Kom (Universitas Pancasila, Indonesia) o Diah Harnoni Apriyanti, S.T, M.Kom. Sudi Mungkasi (Universitas Sanata Dharma, Indonesia) atau Iwan Binanto, S.Si., M.Cs. Universitas Sanata Dharma, Indonesia) atau Teny Handhayani, S.Kom, M.Kom (Universitas Tarumanagara, Indonesia). Makalah dalam International Conference of Artificial Intelligence and Information Technology 2019 hanya untuk media komunikasi yang didistribusikan kepada penulis, keynote speaker dan rekan akademik lainnya dalam International Conference of Artificial Intelligence and Information Technology 2019, pada tanggal 13-14 Maret 2019 di Platinum Adisucipto Hotel & Pusat Konferensi, Yogyakarta, Indonesia.
Each article featured in this International Conference on Artificial Intelligence and Information Technology 2019 may be published in the progress of the International Conference on Artificial Intelligence and Information Technology 2019 where the authors of each article should. Failure to meet this requirement will result in exclusion from the progress of the 2019 International Conference on Artificial Intelligence and Information Technology.
Thursday, 14 March 2019 Time Activity
Friday, 15 March 2019 Time Activity
International Conference of Artificial Intelligence and Information Technology 2019
List of Papers
Paper
Session) Time Page
1570512614 IOT: Peningkatan Sistem Pengendalian Energi Rumah Berdasarkan Perilaku Konsumen (Melky Radja, Gilbert Gutabaga Hungilo, Gahizi Emmanuel, Suyoto). 1570513608 Pembentukan Particle Swarm Menggunakan Artificial Neural Network Self-Organizing Map (ANN-SOM) dengan Strategi 2 Level. Bayu Fandidarma, Achmad Yazidie, Rusdhianto Efendi Abdul Kadir). Antonius Christiyanto Saputra, Pius Guiseppe Sarto Aji Tetuko, Giovani Christian Nugroho, Anjelina Saudara Sitepu, Stanley, Yohanes Sigit Purnomo WP).
1570515432 Big Data Analytics: Estimasi Tujuan Pengguna Angkutan Umum Bus Rapid Transit (BRT) di Jakarta. MOHAMMAD SYARIF, Widyawan, Teguh Bharata Adji). 1570519077 Simulasi fluida berbasis metode titik material dengan jaringan syaraf tiruan (Pandu Akbar Dwikatama, Dody Dharma, Achmad Imam Kistijantoro). 1570523658 Regresi mentah untuk prediksi data kategorikal berdasarkan studi kasus (Riswan Efendi, Susnaningsih Mu'at, Voni Apriana Dewi, Nelsi Arisandy, Noor Azah Samsudin, Dadang Syarif Sihabudin Sahid).
1570523931 A comparison of the use of several different resources on lexicon-based Indonesian sentiment analysis on app review datasets. Fuzzy Coordinator based AI for Dynamic Difficulty Adjustment in Starcraft 2. Muhammad Daryl Bey Sandy Supriyadi, Supeno Mardi Susiki Nugroho, Mochamad Hariadi). 1570526214 Harmonic reduction for four-leg distribution grid-connected single-phase transformerless PV inverter system using diagonal recurrent neural network.
1570526281 Deteksi bahasa ofensif menggunakan jaringan syaraf tiruan (Meredita Susanty, Ahmad Fauzan Rahman, Muhammad Dzaky Normansyah, Ade Irawan, Sahrul). 1570526502 Perbandingan penyematan kata untuk analisis sentimen bahasa Indonesia (Helmi Imaduddin, Widyawan, Silmi Fauziati). Rohmat Tulloh, Ridha Muldina Negara, Yayan Eka Yudha Prasetya, Sendy Saputra). 1570526541 Optimasi termal pada inkubator menggunakan sistem inferensi fuzzy berbasis IoT (Renny Rakhmawati, Irianto, Farid Dwi Murdianto, Atabik Luthfi, Aviv Yuniar Rahman).
1570526544 Pendekatan Berbasis Neural Network untuk Memperkirakan Indeks Keterlibatan Guru Indonesia (ITEI). Sucianna Ghadati Rabiha, Sasmoko, Emny Harna Yossy, Yasinta Indrianti). 1570526547 Mengintegrasikan konsep teknologi informasi ke dalam bisnis berkelanjutan (Erda Guslinar Perdana, Husni S. Sastramihardja, Iping Supriana Suwardi). 1570526552 Deteksi pneumonia dengan arsitektur konvolusional dalam (Abdullah Faqih Al Mubarok, Ahmad Habbie Thias, Dominique Jeffrey Alamaro Maximilianus).
List of Papers Per Room
Session Time Paper Code Title
A comparison of the use of several different sources in lexicon-based Indonesian sentiment analysis on the app review dataset. Determination of the threshold value for the identification of goblet cells in the chicken small intestine (Conference paper). The health status of the chicken intestine can be seen by the number of goblet cells found in the epithelium of the small intestine.
The cell identification is required to count the number of goblet cells and in most cases identification of goblet cells is performed directly through a microscope. Here we aim to design a system that can automatically identify goblet cells by segmentation using two threshold values. Grayscale image is defined as the result of extracting the color component in color saturation value type images.
Goblet cells, as the main producer of mucin, can be stained when processing a tissue preparation using the Schiff staining technique with alcian blue periodic acid. This technique turns mucin blue so that goblet cell identification can be done automatically by extracting the blue features. Segmentation using two thresholds demonstrates that the system is able to correctly identify goblet cells.
Binary descriptors require less computational time than floating-point-based descriptors because of the comparison of intensities between pairs of sample points and the comparison after creating a binary string. BE-SIFT: A Shorter and Efficient SIFT Image Matching Algorithm for Computer Vision 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Reliable, autonomous and secure computing; Pervasive Intelligence and Computation Published: 2015. Abstract: This paper proposes an automatic summarization method for a video lecture transcript that uses attention-based Recurrent Neural Network (RNN) to capture the content of..View more.
This paper proposes an automatic summarization method for lecture video that uses an attention-based recurrent neural network (RNN) to capture lecture content. We also use a language-based feature that helps the model identify the important word and key topic in a segment, improving the quality of the summary. Our model shows a significant improvement in the expression of the ROUGE score compared to the baseline models.
Compared to other types of learning content, lecture video plays a prominent role in the learning process as it provides the richest content, in the sense that it provides visual and auditory stimulation that is associated with higher student concentration and content acceptance. [1] . Previous study has also shown that video is one of the most preferred learning media by students [2].
