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All Journal SISFOTENIKA JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Sistem Komputer & Kecerdasan Buatan Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Journal of Blockchain, Nfts and Metaverse Technology
Ira Diana Sholihati
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health

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Covid-19 Diagnosis Based Android Mobile Application using Certainty Factor Method Imanuel Sinuraya; Agung Triayudi; Ira Diana Sholihati
SISFOTENIKA Vol 10, No 2 (2020): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (412.948 KB) | DOI: 10.30700/jst.v10i2.968

Abstract

Expert Systems are part of a general category of computers known as intelligence. Created Expert System to work on a domain. To make it easier to conclude a problem, however, it requires efficient data to a certain part of basic knowledge, and human thinking procedures to implement knowledge on a given problem. In artificial intelligence, an expert system is a computer system that mimics the decision-making ability of humans who are experts in their fields. The main thrust of artificial intelligence is in the development of computer functions related to human intelligence, such as reasoning, learning, and problem solving, to build a knowledge-based system in the specific field of medicine in the domain for the purpose of diagnosing Covid-19 displayed on mobile devices, information that is quickly and precisely from an expert is needed, can be formulated a problem in the form of diagnosis Covid-19 through the application of an expert system in the form of input symptoms. This is what drives the creation of the Covid-19 diagnostic system using a certainty factor based on Android mobile application. 
Implementation of the Max-Miner algorithm for product recommendations in Café Lo Aja Ghulam Prasetyo Utomo; Agung Triayudi; Ira Diana Sholihati
SISFOTENIKA Vol 10, No 2 (2020): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/jst.v10i2.964

Abstract

Café Lo Aja is a company that sells food and drinks. The business process carried out by this company is buying goods from suppliers and selling products to customers. Sales transaction data will produce heaps of data that get bigger and bigger, so that it can cause new problems. The purpose of this research is to make an application to process a sales transaction data so that it can produce information about consumer purchasing patterns which will be used to help the Cafe Lo Aja to make business decisions. This study uses Cafe Lo Aja sales transaction data in 2019 with the Data Mining Market Basket Analysis method and the Max-Miner Algorithm. This research produces data which is an association rule from a collection of sales transaction data. So that by knowing the pattern of purchasing these products, the cafe manager can predict future market needs that can take into account what stock items must be reproduced and what items should be reduced because of the small percentage of interested ones. By knowing the results of the association, the manager can adjust the layout of the product menu to be better because products that are often purchased will be placed close together. Suggested application development that can be done in further research is the system can be developed into a mobile application, so consumers can order products on their smartphone devices.
MENGUKUR TINGKAT KEPUASAN PENGGUNA APLIKASI KEARSIPAN MENGGUNAKAN SYSTEM USABILITY SCALE DAN PIECES FRAMEWORK Ade Muhammad Nur Fauzi; Agung Triayudi; ira Diana Sholihati
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 7, No 1 (2022)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v7i1.2452

Abstract

Aplikasi Kearsipan adalah sebuah aplikasi yang dimiliki oleh himpunan mahasiswa sistem informasi (HIMASI) Universitas Nasional yang dipergunakan untuk mengelola berbagai dokumen – dokumen penting dan mengelola data – data para pengurus himpunan. Aplikasi kearsipan tersebut dibuat oleh divisi penelitian dan pengembangan. Untuk metode System Usability Scale (SUS) dan PIECES Framework adalah dua buah metode yang digunakan untuk mengukur tingkat kepuasan para pengguna aplikasi kearsipan HIMASI. Dengan mengetahui tingkat kepuasan para pengguna, maka kita juga dapat mengetahui apakah aplikasi tersebut telah layak digunakan dan berjalan dengan baik. pada metode System Usability Scale mendapatkan skor sebesar 79 dengan masuk kategori good dan grade B. Lalu pada metode pieces framework mendapatkan penilaian sebesar 3,996 maka dari itu masuk kategori puas. Dengan hasil kedua metode tersebut maka tingkat kepuasan para pengguna aplikasi kearsipan dinyatakan puas dan baik oleh para pengguna. Lalu dilanjutkan dengan melakukan pengujian sistem dengan menggunakan PageSpeed Insgihts. alat tersebut digunakan untuk melihat performance suatu aplikasi. rata - rata skor yang diberikan oleh PageSpeed Insight kepada aplikasi kearsipan sebesar 78 dengan skor tersebut menyatakan bahwa halaman yang ada pada aplikasi kearsipan telah memiliki performance yang baik.
Analisis Perbandingan Algoritma Jaringan Syaraf Tiruan pada Proses Identifikasi Gerak Bahu Fauziah Fauziah; Aris Gunaryati; Septi Andryana; Ira Diana Sholihati
Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan) Vol. 3 No. 1 (2019): Volume III - Nomor 1 - September 2019
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (70.372 KB)

Abstract

The research related to the analysis of Range of Motion on human movements continues to evolve along with the development of image processing techniques related to human motion can be used to assess the motion done whether it is appropriate. The stage among others is to perform motion acquisition and then convert motion video into multiple image frames. The second phase performs the image processing process consisting of the development phase segmentation algorithm, consisting of background subtraction, grayscale, filtering, threshold, dilation, erosion to silhouette formation. Artificial Neural Network is a concept of learning used and implemented using computer programs and able to complete many calculation processes during the learning process and is system Information processors that have similar characteristics to the human neural network. Results of calculations made from neural network algorithms get an accuracy value of 92.67% using Back propagation of neural networks and 68.13% using; a radialbased neural network function to determine 3 motions are adduction, hyperextension, and extension. DOWNLOAD FILE : FULL TEXT
Implementation of the Double Diamond Method in User Experience Design of Health Service Application (Homecare) Rian, Rian Hidayat; Agung Triayudi; Ira Diana Sholihati
SaNa: Journal of Blockchain, NFTs and Metaverse Technology Vol. 2 No. 1 (2024): February 2024
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/sana.v2i1.272

Abstract

The rapid development of technology at present is almost utilized in every aspect of life, including education, economy, social, and health. However, the equal distribution of this technology has not been fully implemented, especially in the field of health. According to data from Databoks in 2022, 71% of the population has never accessed health services online. This serves as the basis for the creation of the User Interface (UI) and User Experience (UX) for health service applications (homecare) using the Double Diamond method, which is divided into four stages: discover, define, develop, and deliver. Data collection in this research is conducted through literature studies, interviews, and observations. Additionally, usability testing is performed using the System Usability Scale (SUS), with a testing result of 83.3%, categorized as excellent. This can contribute to a positive user experience for the users.
Web Sosialisasi Deteksi Anomali Kapal Menggunakan Kecerdasan Buatan Sari Ningsih; Panca Dewi Pamungkasari; Babag Purbantoro; Asif Awaludin; Deni Yulian; Ira Diana Sholihati; Lili Dwi Yulianto; Erina Rahmazani; Muhammad Zahran Alfarizi
Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial Vol. 3 No. 1 (2026): Februari : Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karya.v3i1.2972

Abstract

The rapid development of Artificial Intelligence (AI) technology has opened significant opportunities to support maritime monitoring systems, particularly in detecting anomalies in ship movements that may indicate illegal or abnormal activities. However, the understanding and utilization of this technology among the general public and maritime stakeholders remain limited. This Community Service Program aims to conduct socialization and dissemination of knowledge on AI-based ship anomaly detection through the development and utilization of an interactive and informative web-based socialization platform. This activity is the result of collaboration between a team of lecturers from the Faculty of Communication and Informatics Technology (FTKI) and the National Research and Innovation Agency (BRIN). The implementation methods include the design of web-based educational content, presentation of fundamental AI concepts and ship anomaly detection, as well as visual simulations of ship movement data analysis results. The web-based socialization platform serves as an educational medium to enhance users’ understanding of the benefits, working mechanisms, and potential applications of AI technology in maritime surveillance. The results indicate an improvement in participants’ understanding of ship anomaly detection concepts and the role of artificial intelligence in supporting maritime security and safety. This PKM activity is expected to promote technological literacy, strengthen synergy between academia and research institutions, and serve as a model for practical and sustainable web-based technology socialization
Co-Authors Ade Muhammad Nur Fauzi Agung Triayudi Aris Gunaryati Asif Awaludin Babag Purbantoro Deni Yulian Erina Rahmazani Fauziah Fauziah Ghulam Prasetyo Utomo Imanuel Sinuraya Lili Dwi Yulianto Muhammad Zahran Alfarizi Panca Dewi Pamungkasari Rian, Rian Hidayat Sari Ningsih Septi Andryana