Article Per Year (5 Year)
p-Index From 2021 - 2026
2.17
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) snimed Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Indonesian Journal of Business Intelligence (IJUBI) Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jurnal Pengabdian Pelitabangsa Jurnal Pelita Pengabdian SAINTEK RESLAJ: Religion Education Social Laa Roiba Journal
Muhammad Najamuddin Dwi Miharja
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : SAINTEK

 1 
Implementasi Sistem Pengenalan Candi Kecil Di Yogyakarta Menggunakan Machine Learning Berbasis Cloud. Ahmad Fatih; Muhammad Najamuddin Dwi Miharja
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.96102

Abstract

In accordance with the national plan according to Presidential Regulation Number 58 of 2014 concerning the Spatial Plan for the Borobudur area, Borobudur is a national mainstay tourism area. As a result, data on visitors to Borobudur temple has increased greatly, the data for the last year of visitors to Borobudur temple every day can reach 55,000 people per day, especially during the national holiday season and school holidays, this has an impact on the condition of the temples and stupas which are increasingly exposed to friction between visitors. thus giving rise to new regulations regarding the daily visitor limit of only 1,250 per day. With the limitation of visitors to Borobudur temple, it is possible for tourists to change their tourist destinations to small temples around Yogyakarta which are less exposed by tourists, such as Sambisari temple, Gebang temple or Ijo temple and so on. one way to get to know more about the temples around Yogyakarta is to create a temple recognition system with the help of the implementation of cloud-based machine learning from nyckel.com, namely a platform as service for machine learning. from the test results on a dataset of 50 images with a distribution of 80 to 20. resulting in a confidence value of an average of 95% this number can prove that the temple recognition model with cloud-based machine learning can be used for temple recognition properly. Keywords: Recognation System, Machine Learning, Cloud
Implementasi Chatbot Deteksi Depresi Dini Pada Mahasiswa Dengan Phq-9 (Patient Health Questionnaire) Menggunakan NLP (Natural Language Processing). Muhammad Najamuddin Dwi Miharja; Shohibul Adhkar
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.103108

Abstract

One of the serious problems in public health according to the World Health Organization (WHO) is depression. According to WHO depression ranks fourth disease in the world. When someone experiences depression, it will have an impact on reduced productivity, especially for students. The Patient Health Questionnaire (PHQ-9) is a sequence of questions in the initial screening of depression to see the initial severity of depression. Chatbots are applications with artificial intelligence that can communicate with humans. Natural Language Processing is one of the subtopics of Artificial Intelligence, which is an application that can have the advantage of understanding human language normally. In this study, a chatbot service was implemented for Early Detection of Depression in Students with PHQ-9 (Patient Health Questionnaire) using NLP (Natural Language Processing). It was found that around 84% answered that chatbots can help for early detection of depression. Keywords: Chatbot, Natural language Processing (NLP), PHQ-9
Co-Authors . Ermanto Abdul Ghofir Aceng Badruzzaman Aceng, Aceng Badruzzaman Aditia, Sultan Aguswin, Ahmad Ahmad Fatih Ahmad Fauzi Annafi’ Franz Annisa Maulana Majid Dian Sulistyorini Wulandari Dina Faradilla Erlina Widayanti Fauzi Ahmad Muda Isarianto, Isarianto Muhammad Hamdan 'Ainulyaqin Muhammad Rifa'i, Anggi Nandhito Kuslesmana Perdana Ricardo Shohibul Adhkar Soma Setiawan Ponco Nugroho Syifa Aulia Tri Sasongko, Ananto Turmudi Zy, Ahmad Tyo Repsi Harta Sanjaya Yahya, Adibah