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All Journal Jurnal Informatika Universitas Pamulang Electron: Jurnal Ilmiah Teknik Elektro
Johan Suryo Prayogo
Universitas Anwar Medika
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

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Implementation Chatbot on Whatsapp Using Artificial Intelligence With Natural Language Processing Method Putri Ariatna Alia; Rusina Widha Febriana; Johan Suryo Prayogo; Rony Kriswibowo
ELECTRON Jurnal Ilmiah Teknik Elektro Vol 5 No 1: Jurnal Electron, Mei 2024
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/electron.v5i1.134

Abstract

According to research conducted by we are social in 2023, internet users aged 16 - 64 years 92.1% use whatsapp as a long-distance communication medium. That this is the reason why business conversations switch to using whatsapp social media. In the business process, meetings between buyers and sellers are needed so that buyers can ask about the products they will buy before the goods are purchased by the buyer. Whatsapp is one of the solutions to this problem, but the meeting is virtual. The questions asked by several buyers about the items they want to buy are usually almost the same so the chatbot comes as a solution so that the seller does not have to answer repeatedly for the same questions asked by different buyers. Previous services used admin assistance to answer buyer questions, but this was considered less efficient because buyers could not receive answers to questions quickly, because the admin had another line of work, namely packing goods.  Chattbot can answer questions in real time, so that buyers can receive information directly without waiting. The research method used is the Waterfall System Development Life Cycle (SDLC) which has four stages, namely analysis, design, coding and testing and uses the User Acceptance Testing (UAT) application testing technique. The results of the questionnaire sent to buyers stated that the service using the chatbot average index of 3.71.These results show the Chatbot system is very feasible and effective in helping customers obtain the information needed.
Implementation of Text Processing Techniques on Citizen Opinions Regarding Floods in Surabaya Rony Kriswibowo; Putri Ariatna Alia; Johan Suryo Prayogo; Rusina Widha Febriana
ELECTRON Jurnal Ilmiah Teknik Elektro Vol 5 No 1: Jurnal Electron, Mei 2024
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/electron.v5i1.148

Abstract

An analysis of residents opinions on flooding in Surabaya is essential to identify their perceptions and aspirations towards this disaster. This can facilitate the making of appropriate flood mitigation policies. The current problem is that it is difficult to retrieve data from X in the form of both users and tweets automatically. So that in some studies that use tweet data becomes less efficient in the data collection process. This research confirmed the use of messages to determine highly impactful disaster zones and showed how tweets can be used to identify oscillations in disaster intensity over time. The topic of this research is to apply the Data Crawling method to obtain datasets on social media X. Then the next method is text preprocessing using Wordcloud, Matplotlib, (NTLK) Natural Language Toolkit, and Sastrawi libraries. In natural language processing, the data to be extracted includes unstructured or “arbitrary” data. In normal dialect preparing (NLP), the information to be extracted includes unstructured or "self-assertive" information.  For future purposes (assumption examination, subject modeling, etc.), such information must be changed over into organized data. The discoveries of the think about can help the organization in comprehending the necessities and inclinations of the people with respect to surges. This article demonstrates how Artificial Intelegence may be applied to text data analysis in order to provide insightful findings. the outcomes of this research can help the government in making more effective policies to overcome flooding in Surabaya
Implementasi Black Box Testing dan Acceptance Testing Fitur SKKM pada Cybercampus.uam.ac.id Universitas Anwar Medika Rony Kriswibowo; Johan Suryo Prayogo; Rusina Widha Febriana; Putri Ariatna Alia
Jurnal Informatika Universitas Pamulang Vol 8 No 4 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i4.36904

Abstract

The Student Activity Credit System or abbreviated as (SKKM) recognizes and recognizes the existence of student activities in its development. However, Cybercampus still finds many errors with the SKKM feature, this can be seen from the fact that some students do not understand the SKKM feature. Students have difficulty inputting documents that must be uploaded, then there are some students who cannot access the SKKM feature. Based on existing problems, it is necessary to test applications to minimize functions that do not meet expectations. The scope of Testing is the system and based on the problem that many students do not understand the system, acceptance Testing is needed. Researchers tested the SKKM feature using Black Box Testing to identify which functions were damaged, interface errors, data structure errors, performance errors, initialization errors, and termination errors. Next, the second method uses the Acceptance test to test students' level of understanding and acceptance of the SKKM features on Cybercampus. The results of Black Box Testing showed that there were 12 test scenarios and 1 test scenario that was not suitable. Researchers provide recommendations for system improvements to improve system quality. then by using Acceptance Testing with 3 variables, namely Perceived Ease of Use, Perceived Usefulness, and Acceptance of IT. Then the conclusion from the overall Acceptance Testing was 75%. The conclusion of this research is that the features function as expected well and no major errors were found, so that the SKKM menu on cybercampus.uam.ac.id can be used immediately.
Co-Authors Putri Ariatna Alia Rony Kriswibowo Rusina Widha Febriana