Article Per Year (5 Year)
p-Index From 2020 - 2025
3.416
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Komputer dan Informasi IPTEK The Journal for Technology and Science Techno.Com: Jurnal Teknologi Informasi Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization ILKOM Jurnal Ilmiah Journal TEPAT: Teknologi Terapan untuk Pengabdian Masyarakat Jurnal Penelitian Enjiniring Fakultas Teknik Unhas Jurnal Teknologi Elekterika Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Indonesian Journal of Electrical Engineering and Computer Science Jurnal Minfo Polgan (JMP) Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI) Jurnal Pengabdian Mandiri Malcom: Indonesian Journal of Machine Learning and Computer Science Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Ingrid Nurtanio
Universitas Hasanuddin
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

Published : 27 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 27 Documents
Search

 1   2   3 
Pelatihan Mengenal Karakter Dasar Siswa untuk Coaching di SMK Telkom Makassar Indrabayu Indrabayu; Ingrid Nurtanio; Ady Wahyudi; Christoforus Yohannes; Ais Prayogi; Elly Warni; Anugrayani Bustamin; Astri Oktianawaty; A. Marimar Muchtamar; Intan Sari Areni
JURNAL TEPAT : Teknologi Terapan untuk Pengabdian Masyarakat Vol 4 No 2 (2021): Community Empowerment through Health Awareness in the New Normal
Publisher : Faculty of Engineering UNHAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25042/jurnal_tepat.v4i2.183

Abstract

This rapid technological development needs to be addressed wisely regarding the millennial generation. One of them is knowing the character and mindset of the millennial generation. This community service aims to provide new insights and knowledge for teachers and specifically for students to recognize basic characters. Character education is one of the main discourses in national policies in the field of character education. The entire teaching and learning process must refer to character development and this is something that partners will implement, in this case, SMK Telkom Makassar. The implementation of community service is carried out by two methods, namely the socialization of basic character recognition and Brain Color tests. This socialization consists of introducing basic characters which is also one of the sub-topics in the Technopreneurship Course taught at the Department of Informatics Engineering, Hasanuddin University. And as a solution in solving partner problems, a brain color test is carried out to identify the personality color of each student. The results of each student's Brain Color model can be used as a reference in developing teaching and learning process strategies. This community service was attended by 63 teachers of SMK Telkom through a zoom meeting. The participants were very enthusiastic in participating in this activity, as seen from the questionnaire results, which showed 96% agreed with the implementation of the method introduced. In addition, the participants also hoped that there would be further training related to the introduction of student characters which are important in the learning process at school.
Detection of Kidney Organ Condition Using Hidden Markov Models Siska Anraeni; Ingrid Nurtanio; Indrabayu Indrabayu
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp294-300

Abstract

The frequencies of chronic kidney disease are likely to continue to increase worldwide. So people need to take a precaution, which is by maintaining kidney health and early detection of renal impairment by analyzing the composition of the iris is known as iridology. This paper presents a novel approach using a one-dimensional discrete Hidden Markov Model (HMM) classifier and coefficients Singular Value Decomposition (SVD) as a feature for image recognition iris to indicate normal or abnormal kidney. The system has been examined on 200 iris images. The total images of the abnormal kidney condition were 100 images and those for the normal kidney condition were 100 images. The system showed a classification rate up to 100% using total of image for training and testing the system unspecified, resize iris image 56x46 pixels, coefficient values U(1,1), Σ(1,1) and Σ(2,2), quantized values [18 10 7], and classify by 7-state HMM with .pgm format database.
Deepfake Detection in Videos Using Long Short-Term Memory and CNN ResNext Muhammad Indra Abidin; Ingrid Nurtanio; Andani Achmad
ILKOM Jurnal Ilmiah Vol 14, No 3 (2022)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i3.1254.178-185

Abstract

Deep-fake in videos is a video synthesis technique by changing the people’s face in the video with others’ face. Deep-fake technology in videos has been used to manipulate information, therefore it is necessary to detect deep-fakes in videos. This paper aimed to detect deep-fakes in videos using the ResNext Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) algorithms. The video data was divided into 4 types, namely video with 10 frames, 20 frames, 40 frames and 60 frames. Furthermore, face detection was used to crop the image to 100 x 100 pixels and then the pictures were processed using ResNext CNN and LSTM. The confusion matrix was employed to measure the performance of the ResNext CNN-LSTM algorithm. The indicators used were accuracy, precision, and recall. The results of data classification showed that the highest accuracy value was 90% for data with 40 and 60 frames. While data with 10 frames had the lowest accuracy with 52% only. ResNext CNN-LSTM was able to detect deep-fakes in videos well even though the size of the image was small.
Strategi Pembelajaran Menggunakan Metaverse Bagi Guru Di Madrasah Aliyah Al Hidayah Indrabayu Indrabayu; Zahir Zainuddin; Ingrid Nurtanio; Amil Ahmad Ilham; Muhammad Niswar; Adnan Adnan; Elly Warni; Zulkifli Tahir; Ady Wahyudi Paundu; Christoforus Yohanes; Mukarramah Yusuf; A.Ais Prayogi; Anugrayani Bustamin; Iqra Aswad; Muhammad Alief Fadhal Imran Oemar; Intan Sari Areni; Zaenab Muslimin; Rieka Zalzabillah Putri; Aulia Darnilasari
JURNAL TEPAT : Teknologi Terapan untuk Pengabdian Masyarakat Vol 5 No 2 (2022): Mengembangkan Kehiodupan Masyarakat melalui Kesatuan dan Kekuatan
Publisher : Faculty of Engineering UNHAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25042/jurnal_tepat.v5i2.287

Abstract

The rapid development of digital technology makes the world of education must continue to be dynamic and develop in order to produce adaptive and competent generations. Previously in conventional teaching methods, the material was taught by the teacher to students in the classroom orally or by telling students to read books to watch videos. However, with the online school method in Metaverse, it is hoped that it can provide clear explanations regarding material that is difficult to explain through books or videos. Metaverse is a future technology in the form of a virtual space where people from all over the world can gather and communicate using virtual technology. With the presence of a virtual world like this Metaverse, the world of education will be greatly helped. For example, when learning takes place, students can see firsthand how the machine works without having to cut it, the anatomy of the body without having to cut live animals or visiting a historical place without having to flock to ride buses all the way to the place they want to go, see phenomena and direct natural disasters, or even school buildings can also be built majestically in the Metaverse world. There are so many conveniences that we find when we use the Metaverse as a learning innovation in the future. Community service carried out at Madrasah Aliyah Al Hidayah, aims to provide insight into educational applications that will be used in the Metaverse so as to facilitate interaction between teachers at MA Al Hidayah and students, as well as provide enormous opportunities, especially for matters related to the world of education. , internet design and gaming. This community service is also a place to socialize research results at the Department of Informatics Engineering, namely Metaverse in the field of education. The results of the service showed that the level of understanding of the training participants increased significantly on the importance of Metaverse education.
Improving Community Digital Literacy Capability in Efforts to Build a Digital Village Amil Ahmad Ilham; Zahir Zainuddin; Ingrid Nurtanio; Indra Bayu; Muhammad Nizwar; Adnan Adnan; Elly Warni; Zulkifli Tahir; Ais Prayogi Alimuddin; Christoforus Yohannes; Ady Wahyudi Paundu; Mukarramah Yusuf; Anugrayani Bustamin; Iqra Aswad; Muhammad Alief Fahdal Imran Oemar; Intan Sari Areni; Zaenab Muslimin
JURNAL TEPAT : Teknologi Terapan untuk Pengabdian Masyarakat Vol 6 No 1 (2023): Kesadaran Teknologi untuk Mengatasi Permasalahan Kemasyarakatan
Publisher : Faculty of Engineering UNHAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25042/jurnal_tepat.v6i1.296

Abstract

Digital village is a government program concern on village development to improve the quality of life of rural communities through the use of technology in various aspects of village development. This community service aims to provide essential insight and knowledge regarding Digital Village and its application to support the realization of a smart village. This activity was carried out in Desa Tamaona, Bulukumba Regency, through a socialization process attended by four village officials and ten productive people from the local village. Digital information about this village is still relatively minimal on the Internet, while the potential for natural wealth and products in the village is excellent. Therefore, this activity was carried out to support the concept of village digitization as well as an event to introduce the potential of Desa Tamaona to the outside community. The implementation of this service is carried out by socializing village information applications/systems using the Participatory Rural Appraisal (PRA) method. The results of the initial data collection show that the Desa Tamaona community has sufficient potential for developing a digital village, which is seen from the already high intensity of internet use by the community. After the socialization and training on using the website information system, the participants acknowledged that they got a lot of convenience in accessing information digitally compared to before this activity was carried out. This stage is a motivation for further developing technological resources to achieve the smart village concept, which can also increase digital literacy for the Desa Tamaona community.
Estimasi Bobot Ikan Bandeng Menggunakan Segmentasi Citra Biner Musakkir Musakkir; Ingrid Nurtanio; Zahir Zainuddin
Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI) Vol 7 No 1 (2024): Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Lamappapoleonro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57093/jisti.v7i1.181

Abstract

Penelitian ini bertujuan Untuk menentukan estimasi bobot ikan bandeng melalui citra, telah dibuat suatu sistem untuk melakukan segmentasi pada citra ikan bandeng. prosesnya di mulai dengan menginput citra digital ikan bandeng kemudian dikonversi ke citra grayscale dan citra biner menggunakan metode threshold kemudian dilakukan penghalusan citra menggunakan metodemorfologi closing. prediksi bobot ditentukan dengan menggunakan metoderegresi linear sederhana dengan persamaan regresi untuk data yang menggunakan metode morfologiclosing Y=-183,16+0,000268X menghasilkannilai error rata-rata sebesar 1,277% dan persamaan regeresi data tanpa metode morfologi closing Y=-152,04 +0,000275X menghasilkan nilai error rata-rata 3,611%.
Expert System For Major Selection Determination At Universitas Muhammadiyah Sinjai Nurhikmayana Janna; Ingrid Nurtanio; Imran Taufiq
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 1 (2023): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v13i1.41

Abstract

The choice of major is very important to support the success of students in completing their studies well and on time. However, this is an important issue because, based on research by the Indonesia Career Center Network (ICCN) in 2017, 87 % of Indonesian students admit that the majors they chose do not suit their interests. And 71.7 % of workers have a profession that is not in accordance with their education. The obstacle faced by prospective students when choosing a major is that they do not know their interests, talents, and potential. Therefore, a system was created that could provide suggestions for majors that match the interests of prospective students. An expert system with the forward chaining method is used in the system. The method used in making this expert system application is the forward chaining method. This expert system process accepts the choices that are already available and have been filled in by the user. And the results of this expert system provide a solution for selecting majors based on the interests of prospective students. So that prospective students can determine the right major. From the results of the implementation and trials that have been carried out by researchers, a probability value is obtained that reaches 100 %, indicating that the system is functioning properly, and as many as 94 % of respondents stated that they strongly agree that the use of this application can help make it easier to determine majors at Universitas Muhammadiyah Sinjai.
Penerapan Game untuk Belajar Matematika Menyenangkan di Panti Asuhan Al-Khaerat Makassar ., Indrabayu; Warni, Elly; Nurtanio, Ingrid; Yohannes, Chystoporus; Alimuddin, A.Ais Prayogi; Bustamin, Anugrahyani; Areni, Intan Sari; Muslimin, Zaenab; Yusuf, Mukarramah; Mokobombang, Novy Nur R.A; Nurdin, Winati Mutmainnah; Anisah, Siti Nur
JURNAL TEPAT : Teknologi Terapan untuk Pengabdian Masyarakat Vol 6 No 2 (2023): Let us Collaborate for Community Issues
Publisher : Faculty of Engineering UNHAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25042/jurnal_tepat.v6i2.414

Abstract

Mathematics is one of the important subjects in the educational curriculum, but it is often considered difficult and boring by some children. This can be an obstacle in their learning process and academic development. Therefore, in an effort to help increase interest and achievement in learning mathematics and develop children's potential and talents, we as a service team from the Department of Informatics Engineering, Faculty of Engineering, Hasanuddin University feel the need to contribute by holding mathematics game socialization activities at Al-Khaerat Makassar Orphanage. The community service carried out at the Al-Khaerat Makassar Orphanage aims to provide new insights for students related to digital learning methods and materials within the scope of mathematics learning with a fun and interactive approach, it is hoped that students can feel more interested and enthusiastic in learning mathematics. The implementation of community service is divided into two stages, namely the socialization stage of learning methods by utilizing technology, in this case smartphones and the training stage of using mathematical educational game applications. The results of the analysis through pre-test and post-test questionnaires show that the use of the Mathology Game application has a significant impact on students mathematics learning in three main aspects, namely: comfort, easy, and understanding of the material.
Systematic Literature Review: Deep Learning Pada Citra Sinar-X Paru Untuk Klasifikasi Penyakit Leonard, Calvin Rinaldy; Nurtanio, Ingrid; Bustamin, Anugrayani
Techno.Com Vol. 23 No. 3 (2024): Agustus 2024
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v23i3.10961

Abstract

Paru-paru merupakan organ vital dalam tubuh manusia. Paru-paru mengangkut oksigen ke dalam tubuh dan mengeluarkan karbondioksida keluar dari tubuh. Proses pertukaran oksigen dan karbon dioksida ini membuat paru-paru rentan terjangkit oleh virus, bakteri dan jamur. Paru-paru dapat terjangkit berbagai jenis penyakit seperti pneumonia, tuberkulosis, kanker, ataupun covid-19. Dalam proses diagnosa penyakit tersebut, seringkali terjadi perbedaan diagnosa antar dokter. Melalui tantangan tersebut, diperlukan sistem pembelajaran mesin yang dapat menjadi pihak ketiga untuk melakukan klasifikasi kondisi. Salah satu metode modern yang dapat digunakan yaitu Metode deep learning. Convolutional Neural Network adalah salah satu dari banyaknya metode deep learning dan CNN telah terbukti menghasilkan akurasi yang tinggi dalam memproses gambar. Banyaknya penelitian yang telah menggunakan metode CNN dalam mengolah citra sinar-X paru menjadi dorongan untuk mencari gap dengan menggunakan metode SLR (Systematic Literature Review). Diagram PRISMA juga digunakan dalam memilih dan mendokumentasikan 93 paper yang relevan hingga menghasilkan 22 paper yang sesuai dengan lingkup penelitian yang menggunakan subjek sinar-X paru dan menggunakan metode deep learning CNN. Hasil yang diperoleh adalah informasi terkait dataset yang digunakan, hanya 1 dari 22 paper yang menggunakan data primer, sisanya adalah data sekunder. Selain itu, transfer learning menjadi pilihan terpopuler dalam mengembangkan sistem klasifikasi paru.   Kata kunci: Deep Learning, Paru-paru, Sinar-X, SLR, PRISMA
Application of Artificial Neural Network and Gray Level Co-occurrence Matrix to detect blood glucose levels through the skin of the hands. Umar, Usman; Syarif, Syafruddin; Nurtanio, Ingrid; Indrabayu, Indrabayu
Jurnal Teknologi Elekterika Vol. 19 No. 2 (2022): Nopember
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v6i2.3756

Abstract

Increased glucose in the blood can cause a buildup so that it cannot be absorbed by all of the body's cells, this problem can cause various disorders in the body's organs. To avoid problems, it is necessary to check the blood glucose level regularly. Monitoring blood sugar levels is currently still using invasive techniques that are painful, non-invasive monitoring is needed. This study develops a non-invasive method to predict blood glucose through image processing. For investigation, several invasive images and glucose levels were taken. Types of samples based on age classification, 20-60 years. For accuracy and simple analysis, 37 images of participants as volunteers, samples were evaluated and investigated under the gray level co-occurrence matrix (GLCM). In this study, an artificial neural network (ANN) was used for all training and hand texture testing to detect glucose levels. The performance of this model is evaluated using Root Mean Square Error (RMSE) and correlation coefficient (r). Clarke Error Grid Analysis (EGA) variance was used in this investigation to determine the accuracy of the method. The results showed that the RMSE was close to the standard value, the regression coefficient was 0.95, and the Clarke EGA analysis: 81.08 % was in the A zone. So that the blood glucose prediction model using the GLCM-ANN method is feasible to apply.
Co-Authors A. Ais Prayogi Alimuddin A. Marimar Muchtamar A.Ais Prayogi Abdul jalil Adnan Adnan Adnan Adnan Adnan Adnan Ady W Paundu Ady Wahyudi Ady Wahyudi Paundu Ady Wahyudi Paundu Ahmad Rifaldi Ais P Alimuddin Ais Prayogi Alimuddin Alif Tri Handoyo Alimuddin, A.Ais Prayogi Amil A Ilham Amil A Ilham Amil A. Ilham Amil Ahmad Ilham Amil Ahmad Ilham Amirullah, Indrabayu Andani Achmad Ansar Suyuti Anugrayani Bustamin Anugrayani Bustamin Anugrayani Bustamin Anugrayani Bustamin Areni, Intan Sari Astri Oktianawaty Aswandi, Andi Syam Aulia Darnilasari Bustamin, Anugrahyani Bustamin, Anugrayani Chandra Wisnu Nugroho Christoforus Yohanes Elly Warni elly warni Elly Warni Febriansyah, Muhammad Firmansyah J Kusuma Fransisca J Pontoh Hazriani, Hazriani I Ketut Eddy Purnama Ida Ayu Putu Sri Widnyani Ida R Sahali Imran Taufiq Indra Bayu Indrabayu - Indrabayu . Indrabayu Indrabayu Indrabayu Indrabayu Intan Sari Areni Intan Sari Areni Intan Sari Areni Iqra Aswad Iqra Aswad Jayanti Yusmah Sari Leonard Maramis Leonard, Calvin Rinaldy Lika Purwanti M Alief F Imran Mahdaniar, Mahdaniar Marindah, Tyanita Puti Mauridhi Hery Purnomo Mochamad Hariadi Mokobombang, Novy Nur R A Mokobombang, Novy Nur R.A Muh. Alief Fahdal Imran Oemar Muh. Syahlan Natsir Muhammad Indra Abidin Muhammad Niswar Muhammad Nizwar Mukarramah Yusuf Mukarramah Yusuf Musakkir Musakkir Musyfirah, Kamtina Naufal Khalil Novy NRA Mokobombang Nur Hikmah Nurdin, Arliyanti Nurdin, Winati Mutmainnah Nurhikmayana Janna Palantei, Elyas Paundu, Ady Wahyudi Rahmat Hardian Putra Rieka Zalzabillah Putri RIFALDI, AHMAD Riny Yustica Dewi Rizka Irianty Siska Anraeni Syafruddin Syarif Usman Umar Yohannes, Christoforus Yohannes, Chystoporus Yusuf, Mukarramah Zaenab Muslimin Zaenab Muslimin Zahir Zainuddin Zahir Zainuddin Zulkifli Tahir