Article Per Year (5 Year)
p-Index From 2020 - 2025
1.066
P-Index
This Author published in this journals
All Journal Jurnal Informatika Universitas Pamulang Advance Sustainable Science, Engineering and Technology (ASSET) Electron: Jurnal Ilmiah Teknik Elektro Jurnal Ilmiah Informatika dan Ilmu Komputer Advance Sustainable Science, Engineering and Technology (ASSET)
Alia, Putri Ariatna
Unknown Affiliation
Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Materials Science & Nanotechnology

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
Decision Support System Diagnosis Penyakit Stroke Menggunakan Metode Composite Performance Index (CPI) Febriana, Rusina Widha; Kriswibowo, Rony; Prayogo, Johan Suryo; Alia, Putri Ariatna; Pratama, Setya Budi
Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) Vol. 4 No. 2 (2025): Volume 4 Nomor 2 September 2025
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jima-ilkom.v4i2.56

Abstract

Stroke merupakan salah satu kondisi gawat darurat yang harus ditangani dengan cepat karena dapat mengakibatkan kefatalan. Stroke terjadi ketika asupan oksigen dan atau asupan nutrisi ke otak mengalami gangguan karena adanya penyumbatan pada pembuluh darah. Kondisi penyumbatan ini menyebabkan bagian dari sel-sel otak yang terdampak akan mengalami kerusakan sehingga tidak dapat berfungsi dengan baik. Stroke yang tidak tertangani dengan segera dapat memberikan efek negatif terhadap penderitanya, mulai dari kecacatan, kerusakan otak, hingga kematian. Penelitian ini mengusulkan penerapan metode Composite Peformance Index (CPI) dalam membangun Decision Support System (DSS) untuk membantu diagnosis tingkat peluang terjangkit stroke untuk dapat ditangani lebih lanjut. CPI diterapkan untuk melakukan penilaian dan menentukan peringkat dari beberapa alternatif penyebab stroke. Nilai indeks gabungan gejala stroke yang terbesar akan menampilkan pasien yang paling memungkinkan akan menderita stroke. Tujuan penelitian ini yaitu dengan mengetahui pasien yang mungkin mengalami stroke diharapkan dapat memberikan perawatan dan pengobatan yang sesuai, sehingga mampu menekan tingkat kerusakan otak dan mencegah terjadinya komplikasi. Diagnosis dilakukan dengan menerapkan metode CPI pada sistem menggunakan bahasa pemrograman python. Python adalah salah satu bahasa pemrograman yang banyak digunakan dalam pengembangan DSS, karena kemudahan pengkodeannya dan kepemilikan pustaka yang kaya. Hasil penelitian ini didapatkan perhitungan yang dilakukan secara manual dan sistem memiliki hasil yang sama, artinya sistem yang dibangun menghasilkan perhitungan yang valid. Berdasarkan studi kasus penelitian, nilai tertinggi pasien yang akan mengalami stroke berdasarkan nilai indeks gabungan metode CPI adalah sebesar 198.5 dengan keadaan pasien memiliki pola hidup sehat dan riwayat orang tua pernah mengalami stroke mini/TIA.
Implementation Artificial Intelligence with Natural Language Processing Method to Improve Performance of Digital Product Sales Service Alia, Putri Ariatna; Kartika Sari, Dian; Azis, Nur; Gunawan Sudarsono, Bernadus; Agus Sucipto, Purwo
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 Open Artificial Intelligence ChattGPT Integrated With Whatsapp Bot Alia, Putri Ariatna; Prayogo, Johan Suryo; Kriswibowo, Rony; Setyadi, Agung Teguh
Advance Sustainable Science, Engineering and Technology Vol 6, No 1 (2024): November-January
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i1.17909

Abstract

 The rapid development of internet technology has led to changes in human habits interms of seeking information. Now humans have a tendency to use smartphones to find information, especially by using the WhatsApp application. According to data compiled by creative agency we are social in 2023. Whatsapp is in the top position of the most used application, reaching 92%. Artificial intelligence is used as a tool to create remote services to customers because there are no restrictions on working time and can only be accessed using a smartphone. GPT (Generative Pre-training Transformer) chat technology has the ability to answer questions, as well as understand the context of the conversation and generate meaningful text like a remote conversation with humans. ChattGPT can provide information to users with these capabilities, especially in terms of health. In the research there is an integration process between Chattgpt and Whattsapp, by entering the API (Application Programming Interface) key Chattgpt into Whattsapp with the help of javascript programming language. So that the artificial intelligence system using ChattGPT can be implemented on whattapp.
Implementasi Black Box Testing dan Acceptance Testing Fitur SKKM pada Cybercampus.uam.ac.id Universitas Anwar Medika Kriswibowo, Rony; Prayogo, Johan Suryo; Febriana, Rusina Widha; Alia, Putri Ariatna
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.
Implementation Chatbot on Whatsapp Using Artificial Intelligence With Natural Language Processing Method Alia, Putri Ariatna; Febriana, Rusina Widha; Prayogo, Johan Suryo; Kriswibowo, Rony
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 kriswibowo, rony; Alia, Putri Ariatna; Prayogo, Johan Suryo; Febriana, Rusina Widha
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
Co-Authors Agus Sucipto, Purwo Azis, Nur Dian Kartika Sari Febriana, Rusina Widha Gunawan Sudarsono, Bernadus Kriswibowo, Rony Pratama, Setya Budi Prayogo, Johan Suryo Setyadi, Agung Teguh