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All Journal Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) Edsence: Jurnal Pendidikan Multimedia Jurnal Abdi Insani JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Industrial Research Workshop and National Seminar
Wulan, Sri Ratna
Jurusan Teknik Komputer Dan Informatika, Politeknik Negeri Bandung
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Other

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Journal : JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)

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Deteksi Intensi Chatbot Berbahasa Indonesia dengan Menggunakan Metode Capsule Network Fatharani Fatharani; Khoirunnisa Putri Kania; Jonner Hutahaean; Sri Ratna Wulan
Journal of Information System Research (JOSH) Vol 3 No 4 (2022): Juli 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (349.19 KB) | DOI: 10.47065/josh.v3i4.1821

Abstract

Intent detection is a process of classifying customer intention from given sentence or chatting. One of the uses of intent detection is in a chatbot. With intent detection, the chatbot can detect the customer intent. However, currently the use of intent detection has not been implemented by most companies in Indonesia. A good intent detection method for chatbots is one that is able to classify user intentions accurately and quickly. This study aims to perform intent detection of messages from the Indonesian language chatbot dataset obtained from customer conversations of PT. Kazee using the Capsule Network(CapsNet) method. With this research, it is hoped that the chatbot of PT. Kazee can respond to customers more appropriately. On this study we conducted experiments and analyze the use of Capsule Network (CapsNet) method in detecting the intent of PT. Kazee customers conversation. The dataset of the experiments contains questions about PT. Kazee. There are two types of datasets—a dataset with six intentions and a dataset with 18 intentions. We compare the result of this experiment with the BERT intent detection model we used previously. The experiment show that the execution time of CapsNet method is faster than that of BERT. However, BERT is still superior to the CapsNet for the ability to respond appropriately. The CapsNet method can be considered for use on chatbots that are more concerned with execution speed.
Studi Komparatif Fungsionalitas, Performance dan User experience pada Website Geopark Bambang Wisnuadhi; Asri Maspupah; Sri Ratna Wulan; Muhammad Rizqi Sholahuddin; Siti Dwi Setiarini; Lukmannul Hakim Firdaus
Journal of Information System Research (JOSH) Vol 3 No 4 (2022): Juli 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (417.753 KB) | DOI: 10.47065/josh.v3i4.1879

Abstract

Indonesia has great natural resources. UNESCO recognized at least six geoparks, and Indonesia will continue to develop more geoparks in the future. However, currently, Indonesia's geoparks are not widely known. One of the reasons is that the existing websites do not pay attention to performance guidelines, information, economics, and search engine optimization even though the website is a vital marketing medium so that geoparks can be promoted widely and effectively. A comprehensive study of the website contents is required to build a good geopark website. In addition, it is also necessary to study user experience when visiting web pages. This study aims to find the standard website content on the geopark website and compare existing website performance and user experience. This study compares three geopark websites. The three websites include the Ciletuh-Palabuhanratu, Hongkong geopark, and Cliff of Fundy Geosite website. Three indicators are used: website performance, user experience, and what information should be on the geopark website. These three indicators are essential as an attraction for website visitors so they can enjoy the content of the website and they can stay longer so that the visitors can turn into potential geopark tourists. Good website performance is supported by consistent ease of providing information and speed in providing information to website visitors. In comparison, the user experience visiting the website relates to the interactive visual design, organization, and navigation structure of the website framework and the completeness of the content. We use performance and user experience metrics as evaluation tools for the three selected websites. As a result, the general availability of information is as follows: information about geoparks, UNESCO, list of tourist attractions, activities, itinerary, tourist accommodation, education, contacts, language choices, news articles, pamphlets, maps, and virtual tours. In terms of performance, the three websites have slow speeds, but in cumulative layout shifts, they have good scores.
Implementasi Sistem Identifikasi Senjata Real Time Menggunakan YOLOv7 dan Notifikasi Chat Telegram Muhammad Rizqi Sholahuddin; Firas Atqiya; Sri Ratna Wulan; Maisevli Harika; Sofy Fitriani; Yusuf Sofyan
Journal of Information System Research (JOSH) Vol 4 No 2 (2023): January 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i2.2774

Abstract

This research produces an application that can send automatic notifications in the form of a chat on the Telegram platform when a weapon object is detected on CCTV. This application was created utilizing computer vision technology and artificial intelligence, in particular YOLOv7. As demonstrated by the mAP@0.5 value of 0.837 after 50 epochs of training, this application can detect weapon objects such as people, pistols, and knives with a reasonable degree of accuracy. This application is also linked to the telepot library, which enables it to send chats on the Telegram platform. These applications can aid in enhancing security and safety in a variety of environments and have numerous practical applications in fields such as public safety, law enforcement, and others. However, there are still deficiencies in this study that can be addressed in future research, such as the small number of training epochs and the size of the dataset.
Co-Authors Ade Chandra Nugraha Ade Hodijah Akhmad Bakhrun Ani Rahmani Asri Maspupah Cholid Fauzi Dzakira Fabillah Fatharani Fatharani Firas Atqiya Hashri Hayati Joe Lian Min Jonner Hutahaean Khoirunnisa Putri Kania Lukmannul Hakim Firdaus Maisevli Harika Muhammad Riza Alifi Muhammad Rizqi Sholahuddin Santi Sundari Siti Dwi Setiarini Sofy Fitriani Urip Teguh Setijohatmo Wisnuadhi, Bambang Yusuf Sofyan