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All Journal Indonesian Journal of Electronics and Instrumentation Systems IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Pendidikan Matematika AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vidya Karya Al-Jabar : Jurnal Pendidikan Matematika JCES (Journal of Character Education Society) Indonesian Journal on Learning and Advanced Education (IJOLAE) Kasuari: Physics Education Journal (KPEJ) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Bubungan Tinggi: Jurnal Pengabdian Masyarakat Computing and Education Technology Journal Jurnal Pendidikan dan Pengabdian Masyarakat Proceeding of International Conference on Special Education in South East Asia Region Mathematics Education Journal Jurnal Sistem Informasi dan Teknologi Informasi
Wiranda, Nuruddin
Universitas Lambung Mangkurat
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Mathematics Physics Social Sciences Other

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Journal : Indonesian Journal of Electronics and Instrumentation Systems

 1 
Model Identifikasi Kata Ucapan Tuna Wicara Nuruddin Wiranda; Agfianto Eko Putro
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 9, No 2 (2019): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (508.944 KB) | DOI: 10.22146/ijeis.47609

Abstract

Speech impaired is the inability of someone to speak, even though speaking ability is important in order to communicate with other people. Dealing with this as someone who has speech impairments has their own way of communicating, namely by using sign language, but not everyone understands the sign language. The MFCC and Backpropagation ANN methods are implemented on a Single Board Computer (SBC) designed to overcome speech impaired communication problems. The MFCC method is used to retrieve the features of speech impairment and the Backpropagation ANN is used for sound pattern recognition.The system was trained using 750 sound samples consisting of 5 speakers, each uttering as many as 30 repetitions of the pronunciation of words (makan, kamar, kerja, harga and lapar), then tested using 125 sound samples consisting of 5 speakers, each saying 5 repetitions of words. Training and testing of Backpropagation ANN using input coefficients generated from MFCC. The results showed that the MFCC and Backpropagation ANN methods were able to identify speech words with 60% accuracy, 40% precision and 40% sensitivity.
Survei Penggunaan Tensorflow pada Machine Learning untuk Identifikasi Ikan Kawasan Lahan Basah Nuruddin Wiranda; Harja Santana Purba; R Ati Sukmawati
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 10, No 2 (2020): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.58315

Abstract

Wetlands are habitats commonly used for fish cultivation. South Kalimantan is one of the provinces that has a wetland area, which is 11,707,400ha, there are 67 rivers and an estimated 200 species of fish. This shows the abundant wealth of fish treasures and economic value. The study of fish identification is an important subject for the preservation of wetland fish. In the field of artificial intelligence, identification can be done using Machine Learning (ML). There are many libraries, a collection of functions that can be used in ML development, one of which is Tensorflow. In this paper, we survey a variety of literature on the use of Tensorflow, as well as datasets, algorithms, and methods that can be used in developing wetland area fish image identification applications.The results of the literature survey show that Tensorflow can be used for the development of fish character identification applications. There are many datasets that can be used such as MNIST, Oxford-I7, Oxford-102, LHI-Animal-Faces, Taiwan marine fish, KTH-Animal, NASNet, ResNet, and MobileNet. Classification methods that can be used to classify fish images include CNN, R-CNN, DCNN, Fast R-CNN, kNN, PNN, Faster R-CNN, SVM, LR, RF, PCA and KFA. Tensorflow provides many models that can be used for image classification, including Inception-v3 and MobileNets, and supports models such as CNN, RNN, RBM, and DBN. To speed up the classification process, image dimensions can be reduced using the MDS, LLE, Isomap, and SE algorithms.
Pembelajaran Mesin untuk Sistem Keamanan - Literatur Review Nuruddin Wiranda; Fal Sadikin; Wanvy Arifha Saputra
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 12, No 1 (2022): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.69022

Abstract

Security systems are one of the crucial topics in the era of digital transformation. In the use of digital technology, security systems are used to ensure the confidentiality, integrity, and availability of data. Machine learning techniques can be applied to support the system's adaptability to the environment, so that prevention, detection and recovery can be carried out. Given the importance of these things, it is necessary to review the literature to find out how machine learning is applied to security systems. This paper presents a summary of 31 research papers to determine what machine learning techniques or methods are the most promising for prevention, detection and recovery. The research stages in this paper consist of 6 stages, namely: formulating research questions, searching for articles, documenting search strategies, selecting studies, assessing article quality, and extracting data obtained from articles. Based on the results of the study, it was found that the K-means method was the most promising for prevention, while for detection, SVM could be used, and for security recovery, machine learning could be implemented using NLP-based features.
Co-Authors Ade Winanto Adini, Muhammad Hifdzi Agfianto Eko Putra Agfianto Eko Putro Ahmad Sajjad Akhyari Aida Rizkina Alizhafya, Nova Nor Andi Ichsan Mahardika Anisa Pratiwi Annisa Apriliyanti Aprilian, Rizaldi Ardhabilly, Muchammad Ati Sukmawati Ati Sukmawati, Ati Cahya Kamila Maulida Cahya, Delfisea Delsika Pramata Sari Fal Sadikin Fal Sadikin Fatchul Mu'in Firman Hidayat Hasanah, Julita Heni Pujiastuti Hermanto Hermanto Husna, Risalatul Imron Rosyadi Jajang Kusnendar Jarkani Lestari, Putri Tari M. Andry Gunawan M. Kamal Marlina Marlina Merina Merina Mila Erlina Mitra Pramita Mitra Pramita Mohd Samsu Sajat Mu'in, Fatchul Muhammad Agi Sahriza Daan Nur Muhammad Arifuddin Muhammad Fahmi Ridhani Muhammad Ibnu Alkautsar Muhammad Nasrudin Muriyadi Muriyadi Mutia Yustifisiyah Rahma Shafira Mu’in, Fatchul Noor Cahaya Noor Fajriah Pamuji, Rizky Pramatasari, Delsika Putri Yani R Ati Sukmawati R Ati Sukmawati R Ati Sukmawati R. Ati Sukmawati R. Ati Sukmawati, R. Ati Rizaldi Aprilian Rizky Pamuji Rusma Noortyani Santana Purba, Harja Saputra, Novan Alkaf Bahraini Sukmawati, R Ati Suryaningsih, Yuni Tiara Cahya Kumala Uswatun Hasanah Wahid Irhamna Wanvy Arifha Saputra Wawan Setiawan Yogi Windiannor Yukita Haura Anisa Yuni Suryaningsih