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All Journal Electron: Jurnal Ilmiah Teknik Elektro Jurnal Ilmiah Informatika dan Ilmu Komputer Advance Sustainable Science, Engineering and Technology (ASSET)
Alia, Putri Ariatna
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Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering

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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 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.
Co-Authors Agus Sucipto, Purwo Azis, Nur Dian Kartika Sari Febriana, Rusina Widha Gunawan Sudarsono, Bernadus Kriswibowo, Rony Pratama, Setya Budi Prayogo, Johan Suryo