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LITERATURE REVIEW: LUNG DISEASE DETECTION BASED ON X-RAY USING ARTIFICIAL INTELLIGENCE Ariatna Alia, Putri
Jurnal Rekayasa Sistem Informasi dan Teknologi Vol. 1 No. 2 (2023): November
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jrsit.v1i2.152

Abstract

According to a WHO survey in 2019, 4 of the 10 most common diseases that kill people are lung disease. Lung disease is a significant problem for all of us, but until now there has not been found an effective drug to detect it earlier, so that in general lung disease is diagnosed in a severe condition. One example of a lung disease taken as a sample is pneumonia. This research aims to develop a method that is faster and more accurate in detecting individuals infected with pneumonia by using Artificial Intelligence, especially by using Convolutional Neural Network (CNN) architecture in its learning. The research method used in this study is literature review, in which related articles are collected and processed using the Mendeley application. The criteria used in the selection of articles were articles published in 2020 which discussed the use of Artificial Intelligence in treating pneumonia. Based on the collection and discussion of several existing studies, it can be concluded that by using an Artificial Intelligence system, pneumonia detection in individuals can be carried out through pattern analysis on Lung X-ray results with a high degree of accuracy, using existing training data
Literature Review: Manajemen Layanan Teknologi Informasi dengan Framework Information Technology Infrastructure Library (ITIL) di Indonesia Prayogo, Johan Suryo; Alia, Putri Ariatna; Setyadi, Agung Teguh; Setyawan, Agung Budi
Jurnal Rekayasa Sistem Informasi dan Teknologi Vol. 1 No. 2 (2023): November
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jrsit.v1i2.212

Abstract

Penerapan Framework Information Technology Infrastructure Library (ITIL) dalam Manajemen Layanan Teknologi Informasi (ITSM) di Indonesia. Melalui tinjauan tren penelitian terkini, sehingga memperoleh manfaat. Penelitian ini memberikan wawasan penting untuk pemahaman lebih lanjut tentang efektivitas Information Technology Infrastructure Library (ITIL) dalam mendukung pengelolaan sistem layanan teknologi informasi di lingkungan bisnis Indonesia. Manfaat penerapan Information Technology Infrastructure Library (ITIL) tergambar melalui peningkatan dalam sistem pelayanan kepada pelanggan dam penanganan keluhan dari pelanggan dapat diselesaikan dengan waktu yang lebih cepat. Information Technology Infrastructure Library (ITIL) membantu organisasi untuk lebih responsif terhadap perubahan teknologi dan pasar, menghasilkan lingkungan IT yang lebih adaptif. Tren penelitian menyoroti perkembangan terbaru dalam penerapan Information Technology Infrastructure Library (ITIL) di berbagai sektor industri di Indonesia. Hasil penelitian menunjukkan bahwa semakin banyak organisasi yang menggunakan pendekatan Information Technology Infrastructure Library (ITIL) untuk meningkatkan sistem pelayanan kepada pelanggan, penanganan keluhan dari pelanggan dapat diselesaikan dalam waktu yang lebih cepat. Keywords:, Information Technology Infrastructure Library, Manajemen Layanan TI.
PERANCANGAN DESAIN UI/UX KURSUS ONLINE BERBASIS MOBILE MENGGUNAKAN METODE DESIGN THINKING Suryo Prayogo, Johan; Kriswibowo, Rony; Febriana, Rusina Widha; Alia, Putri Ariatna; Setyawan, Agung Budi
Journal of Information Systems Management and Digital Business Vol. 2 No. 2 (2025): Januari
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jismdb.v2i2.1904

Abstract

Pada era digital saat ini, Pendidikan berbasis teknologi menjadi solusi untuk meningkatkan aksesibilitas dan kualitas pembelajaran. Serena Sarana Teknologi sebagai perusahaan yang bergerak di bidang teknologi informasi berupaya untuk menyediakan kursus online berbasis mobile yang dapat memenuhi kebutuhan pembelajaran masyarakat. Penelitian ini bertujuan untuk merancang desain UI/UX kursus online yang intuitif dan user friendly. Metode yang digunakan pada penelitian ini adalah Design Thinking, yaitu metode yang berpusat kepada pengguna. Metode Design Thinking mempunyai 5 tahapan, yaitu emphatize, define, ideate, prototyping dan test. Pada tahap emphatize, yaitu peneliti harus berempati untuk menggali informasi dari pengguna. Pada tahap ini peneliti menggunakan in-depth interview untuk mendapatkan pain point, user persona dan user journey map. Pada tahap define adalah menentukan tantangan/challenge menggunakan How Might we. Setelah itu adalah memprioritaskan tantangan/challenge menggunakan Challenge Metrix dan memprioritaskan ide solusi tersebut menggunakan Solution Metrix. Membuat konsep desain lo-fidelity atau wireframe berdasarkan ide solusi yang sudah diprioritaskan. Setelah membuat wireframe (desain lo-fi) lalu membuat desain hi-fidelity berdasarkan desain wireframe yang sudah dibuat. Pada tahap prototype adalah menyelesaikan desain akhir yang nantinya akan dilakukan pengujian kepada pengguna. Desain pada prototype akan dilakukan pengujian kepada pengguna pada tahap test. Metode yang digunakan untuk pengujian adalah System Usability Scale (SUS). Peneliti akan membagikan kuisioner SUS kepada 20 responden. Hasil pengujian pada penelitian ini adalah prototipe desain Kursus Online mendapatkan nilai 78.125, nilai tersebut menyatakan bahwa tingkat penerimaan pengguna pada desain prototipe UI/UX Kursus Online Serena Course adalah acceptable dan berada pada grade B.
Implementation Artificial Intelligence with Natural Language Processing Method to Improve Performance of Digital Product Sales Service Putri Ariatna Alia; Dian Kartika Sari; Nur Azis; Bernadus Gunawan Sudarsono; Purwo Agus Sucipto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.521

Abstract

Improving the performance of digital product sales services is the main focus of the company's attention in the face of increasingly fierce competition in the online market. In order to optimize these services, Artificial Intelligence (AI) technology with the Natural Language Processing (NLP) method is an attractive option. This research aims to find out how the application of AI with Natural Language Processing (NLP) can contribute to improving the performance of digital product sales services. The methods used in this research include collecting data on customer interactions via WhatsApp that have implemented artificial intelligence with the Natural Language Processing (NLP) method. The data is then analyzed using Natural Language Processing (NLP) techniques to understand the needs, preferences, and problems faced by customers. Natural Language Processing (NLP) assists the chatbot in correcting incoming questions if they do not match the database on the question. Differences that can be helped by Natural Language Processing (NLP) if there is inappropriate capitalization, excessive conjunctions. The results show that the application of AI with Natural Language Processing (NLP), can enable companies to be more responsive to customer needs and improve overall customer satisfaction. With in-depth analysis of customers' natural language data, companies can provide more relevant services and empower sales teams to provide faster and more accurate responses. This can be seen from the quality of service results which have a point of 4.1, this value indicates a good response from customers so that the system is considered to have improved sales services by buyers.
Implementation Artificial Intelligence with Natural Language Processing Method to Improve Performance of Digital Product Sales Service Putri Ariatna Alia; Dian Kartika Sari; Nur Azis; Bernadus Gunawan Sudarsono; Purwo Agus Sucipto
Advance Sustainable Science Engineering and Technology Vol. 6 No. 3 (2024): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i3.521

Abstract

Improving the performance of digital product sales services is the main focus of the company's attention in the face of increasingly fierce competition in the online market. In order to optimize these services, Artificial Intelligence (AI) technology with the Natural Language Processing (NLP) method is an attractive option. This research aims to find out how the application of AI with Natural Language Processing (NLP) can contribute to improving the performance of digital product sales services. The methods used in this research include collecting data on customer interactions via WhatsApp that have implemented artificial intelligence with the Natural Language Processing (NLP) method. The data is then analyzed using Natural Language Processing (NLP) techniques to understand the needs, preferences, and problems faced by customers. Natural Language Processing (NLP) assists the chatbot in correcting incoming questions if they do not match the database on the question. Differences that can be helped by Natural Language Processing (NLP) if there is inappropriate capitalization, excessive conjunctions. The results show that the application of AI with Natural Language Processing (NLP), can enable companies to be more responsive to customer needs and improve overall customer satisfaction. With in-depth analysis of customers' natural language data, companies can provide more relevant services and empower sales teams to provide faster and more accurate responses. This can be seen from the quality of service results which have a point of 4.1, this value indicates a good response from customers so that the system is considered to have improved sales services by buyers.
The Impact of Website Interactivity on Users’ Speed in Finding Information: Evidence from Indonesia’s Top 5 Universities Setyadi, Agung Teguh; Mufid, Mohammad Robihul; Alia, Putri Ariatna; Fahruddin, Agus; Kriswibowo, Rony
International Journal of Computer and Information System (IJCIS) Vol 6, No 3 (2025): IJCIS : Vol 6 - Issue 3 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i3.245

Abstract

University websites serve as primary sources of information for prospective students and the general public. This study aims to examine the relationship between website interactivity and the efficiency of information retrieval at five of the top ten Indonesian universities according to the QS World University Rankings 2025: ITB, UGM, IPB, ITS, and UI. A total of 30 participants from various universities in Surabaya were asked to complete three types of information search tasks on two different university websites. The time taken to complete each task was recorded using a stopwatch. After completing the tasks, participants completed a questionnaire evaluating their perceptions of the websites' interactivity and ease of use. A Two-Way ANOVA revealed significant effects of university website, task type, and their interaction on task completion time. The findings highlight the crucial role of website structure and interactivity in enhancing users’ efficiency when searching for information. A significant interaction effect was found between website interactivity and task completion time (F = 4.395, p < .05).
Comparative Study of Normalization Methods for DEMNAS Elevation Data to Grayscale Representation for 3D Terrain Visualization Yohan Kartiko, Erik; Teguh Setyadi, Agung; Alfanio Atmoko, Rizky; Suryo Prayogo, Johan; Ariatna Alia, Putri
International Journal of Multidisciplinary Sciences and Arts Vol. 4 No. 3 (2025): International Journal of Multidisciplinary Sciences and Arts, Article July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v4i3.6717

Abstract

This study presents a comprehensive comparative analysis of seven normalization techniques applied to DEMNAS (Digital Elevation Model Nasional) elevation data for grayscale image conversion, essential in 3D terrain visualization and 3D printing. The methods compared are Min-Max Scaling, Z-Score Scaling, Logarithmic Transformation, Square Root, Power (Gamma), Sigmoid, and Arctangent normalization. Using QGIS and Python, elevation data were transformed into grayscale images with pixel values ranging from 0 to 255, representing topographic variation. Visual, statistical, and histogram-based analyses reveal that Min-Max scaling and Arctangent normalization provide the most balanced grayscale distribution and topographic contrast. Logarithmic and Gamma methods emphasize lower elevations, while Z-Score and Sigmoid are more centered around mean values. This study confirms that normalization choice significantly affects terrain visualization quality and should be tailored to specific data characteristics and application contexts.