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All Journal Majalah Ilmiah Teknologi Elektro Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) CommIT (Communication & Information Technology) Jurnal Transformatika JUITA : Jurnal Informatika Journal of Information Systems Engineering and Business Intelligence Indonesian Journal on Computing (Indo-JC) Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Knowledge Engineering and Data Science JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING DoubleClick : Journal of Computer and Information Technology Journal of Information Technology and Computer Engineering JURIKOM (Jurnal Riset Komputer) Logista: Jurnal Ilmiah Pengabdian Kepada Masyarakat KOMPUTIKA - Jurnal Sistem Komputer Jurnal Riset Informatika Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Building of Informatics, Technology and Science JTIM : Jurnal Teknologi Informasi dan Multimedia RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi Jurnal Teknik Elektro dan Komputasi (ELKOM) Jurnal E-Komtek Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer System and Informatics (JoSYC) Madani : Indonesian Journal of Civil Society Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Jurnal Teknik Informatika (JUTIF) Journal of Informatics and Vocational Education Teknika ICTEE (Engineering Journals of Information, control, telecommunication and electrical) Insyst : Journal of Intelligent System and Computation Journal of Dinda : Data Science, Information Technology, and Data Analytics IJCOSIN : Indonesian Journal of Community Service and Innovation Journal of Embedded Systems, Security and Intelligent Systems El-Mujtama: Jurnal Pengabdian Masyarakat Majalah Ilmiah Teknologi Elektro JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi
Faisal Dharma Adhinata
Institut Teknologi Telkom Purwokerto
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

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Classification Taxonomies Genus of 90 Animals Using Transfer Learning Resnet-152 Saputro, Satria Nur; Adhinata, Faisal Dharma; Athiyah, Ummi
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.9482

Abstract

The process of learning theory and the limited ability to remember anything, especially a foreign language, often cause students to have difficulty understanding lessons, especially in determining the type and taxonomy of the animal. With the assistance of computer vision technology, students can more effectively face various challenges, enhance their understanding, and improve their ability to apply the concept of animal classification. The research classifies the taxonomy of 90 animals using Transfer Learning ResNet 152. It aims to analyze the performance of Transfer Learning ResNet 152 on the 90-animal dataset. The results show that in Model A with an architecture with frozen layers in 6 ResNet blocks, the highest evaluation value obtained is 0.9222 on Batch size 4 with Dropout 6, 0.9241 on Batch size 8 with Dropout 7, 0.9259 on Batch size 16 with Dropout 8, and 0.9296 on Batch size 32 with Dropout 4 and Dropout 7. Meanwhile, in model B with an architecture with frozen layers in 5 ResNet blocks and one non-frozen block, the highest evaluation value obtained is 0.7611 on Batch size 4 with Dropout 8, 0.8713 on Batch size 8 with Dropout 2, 0.8852 on Batch size 16 with Dropout 1, and 0.9204 on Batch size 32 with Dropout 3.
Sistem Kendali Proporsional pada Robot Penghindar Halangan (Avoider) Pioneer P3-DX Akhmad Jayadi; Try Susanto; Faisal Dharma Adhinata
Jurnal Teknologi Elektro Vol 20 No 1 (2021): (Januari - Juni ) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2021.v20i01.P05

Abstract

The basic ability that a mobile robot must have is to avoid obstacles, by being able to avoid obstacles, the robot will be able to do its job well without having to hit any obstacles, because by hitting an obstacle it will make the robot take longer to complete the mission even the robot can experience disorientation With the implementation of a control system on obstacle avoidance robots, the robot can overcome existing obstacles. Proportional control is a simple and easy to use control on a mobile robot, with eight sensors on the robot making the robot more sensitive to obstacles in front of it, so the pioneer type mobile robot P3-DX was used in this study. The robot has been able to pass through the existing obstacles with a Kp value of 2 and a constant speed of 4 without hitting it.
Nudibranch Suborders Classification based on Densely Connected Convolutional Networks Christyan, Timothy; Utama, Safitri Yuliana; Darmawan, Bagus Tri Yulianto; Adhinata, Faisal Dharma
JITCE (Journal of Information Technology and Computer Engineering) Vol. 8 No. 1 (2024)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.8.1.30-37.2024

Abstract

Nudibranchs, often called sea slugs, are a group of soft-bodied marine gastropod mollusks that shed their shells after their larval stage. With their body structure that is very similar between one suborder and another, sometimes it is hard to tell apart the suborder of a nudibranch. In this work, we make an Image Classification model for determining the suborder of a nudibranch using deep learning algorithms DenseNet and EfficientNet. The experiment is conducted using Google Colaboratory environment. For DenseNet, we use 121, 169, and 201 layers; meanwhile, we only use the baseline algorithm for EfficientNet. The dataset for research is randomly taken from marine fauna forums on the internet. DenseNet with 201 layers shows a better generalization than other classifiers (accuracy of DenseNet 121, 169, 201, and baseline EfficientNet, respectively 53%, 41%, 73%, and 47%). The research produces a decent system for classifying the suborder of the Nudibranch. Usage of image recognition or background blurring systems in future research can improve the system's accuracy.
Klasifikasi Sampah Organik dan Non-Organik Menggunakan Convolutional Neural Network Abdurrahman Ibnul Rasidi; Yolanda Al Hidayah Pasaribu; Afzal Ziqri; Faisal Dharma Adhinata
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 1 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i1.4314

Abstract

Garbage is a unique problem in Indonesia. From ordinary waste to limited emergency plastic waste, Indonesia is the second-largest source of plastic waste in the world. Separate collection and disposal of waste is one way to reduce the waste generated by society and industry in Indonesia. Sorting out the types of waste is the first step before the recycling process. In the field of Computer Vision research, it is difficult to see the type and form of waste with a camera, therefore this study aims to overcome this problem by using Deep Learning technology which is expected to be implemented in the whole of Indonesia starting from some of the largest waste-producing cities. Deep Learning is a computer (AI) technique for learning like a human - with experiments being a Part of Machine Learning that can be used to classify images. The method used in this study uses the Convolutional Neural Network (CNN) method which can be used to detect and recognize objects in an image, which can be used to create an automatic waste classification system. Broadly speaking, CNN utilizes the convolution process by moving a convolution kernel (filter) of a certain size to an image, the computer gets new representative information from the results of multiplying that part of the image with the filter used. The test results show that the CNN method can classify inorganic waste with accuracy. 96% and organic waste with an accuracy of 62%.
TEKNIK SMOTE DAN GINI SCORE DALAM KLASIFIKASI KANKER PAYUDARA Ramadhan, Nur Ghaniaviyanto; Adhinata, Faisal Dharma
RADIAL : Jurnal Peradaban Sains, Rekayasa dan Teknologi Vol. 9 No. 2 (2021): RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi
Publisher : Universitas Bina Taruna Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37971/radial.v9i2.229

Abstract

Breast cancer is a malignancy in breast tissue that can originate from the epithelium of the ducts and lobules. WHO says 30% - 50% of cancer cases can be prevented. Breast cancer prevention can be done utilizing screening or early diagnosis. The purpose of the initial diagnosis is that if a lump appears, predictions can be made whether it is classified as malignant or benign. Breast cancer prediction can be done using a dataset containing cancer-related parameters. However, sometimes the dataset used also has problems such as the amount of data is not balanced and the use of irrelevant features. This study aims to improve breast cancer prediction results by balancing the number of data classes and using the rank feature. The method used is SMOTE for imbalanced data and Gini score for rank features. The classification model used is random forest and naïve Bayes. The results obtained by the random forest classification model are superior to Naïve Bayes.
Co-Authors Abdul Majid Abdurrahman Ibnul Rasidi Adam Nur Kridabayu Adil El-Faruqi Aditya Wijayanto Afzal Ziqri Ahmad Muslih Syafi’i Ajeng Fitria Rahmawati Akhmad Jayadi Aldhan Tri Maulana Alfan Adi Chandra Alissyah Putri Alon Jala Tirta Segara Alya Aulia Hanafi Ananda Aulia Rizky Ananda Aulia Rizky Andra Aulia Rizaldy Anshari Rusmeniar R.A Apri Junaidi, Apri Arief Rais Bahtiar Arif Amrulloh Ariq Cahya Wardhana Bagus Bayu Sasongko Christoph Quix Christyan, Timothy Condro Kartiko Dani Azka Faz Darmawan, Bagus Tri Yulianto Dayal Gustopo Setiadjit Dian Nugraha Diovianto Putra Rakhmadani Emmanuel Genesius Evan Devara Fadlan Raka Satura Fajar Malik Falah Arfani Fauzi, Muhammad Dzulfikar Fawwaz Muhammad Zulfikar Febry Ardiansyah Firdonsyah, Arizona Fitran Dwi Pramakrisna Fitran Dwi Pramakrisna Gilang Aditia GITA FADILA FITRIANA Gracia Rizka Pasfica Herman Yuliansyah Ibnul Rasidi, Abdurrahman Ikadhanny Yudyan Pratama Irsyad Zulfikar Jahfal Rizqi Putra Pradhana Kridabayu, Adam Nur M Alfian Maulana Al Azhar Merlinda Wibowo Metha Khafifah Isty Rikhanah Mohammad Rifqi Zein Muhammad Arif Saputra Muhammad Fajar Ahadi Muhammad Ikhsan Muhammad Iqbal Rasyid Muhammad Pajar Kharisma Putra Narantyo Maulana Adhi Nugraha Naseh Hibban Nasution, Annio Indah Lestari Nia Annisa Ferani Tanjung Nike Prasetyo Nisrina Eka Salsabila Novi Rahmawati Novi Rahmawati Nugraha, Narantyo Maulana Adhi Nur Ghaniaviyanto Ramadhan Nur Syahela Hussien Nursatio Nugroho Pasaribu, Yolanda Al Hidayah Purnama Dileon Yamora Nainggolan Putra, Muhammad Daffa Arviano Rachma Wukir Purwitasari Rahardian, Reva Rahmanda Trinova Putra Renna Nur Injiyani Retno Hendrowati Reva Rahardian Rifki Adhitama, Rifki Rifqi Akmal Saputra Rifqi Akmal Saputra Rifqi Alfinnur Charisma Rival Fahmi Hidayat Rizki Rafiif Amaanullah Rohman Beny Riyanto Saputro, Satria Nur Satria Adi Nugraha Sayyid Yakan Khomsi Pane Sofiyudin Pamungkas Teguh Rijanandi Teguh Rijanandi Teguh Rijanandi Tri Dimas Cipto Satrio Wibowo Try Susanto Ummi Athiyah Utama, Safitri Yuliana Utami, Annisaa Vincent Nathaniel Wahyono Wahyono Widi Widayat Wijayanto, Danur Winanto, Tawang Sahro Yaqutina Marjani Santosa Yohani Setiya Rafika Nur Yolanda Al Hidayah Pasaribu Yuni nur fari'ah Zanuar Rahmat Saputra Ziqri, Afzal