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All Journal Jurnal Ilmiah Informatika Komputer InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Informatics for Educators and Professional : Journal of Informatics Information Management For Educators And Professionals (IMBI) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer JURNAL MANAJEMEN INFORMATIKA (JUMIKA) Jurnal Teknologi Informasi dan Multimedia Jurnal Accounting Information System (AIMS) E-Link: Jurnal Teknik Elektro dan Informatika REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer AMMA : Jurnal Pengabdian Masyarakat Jurnal Informatika: Jurnal Pengembangan IT Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal)
Irfan Ali
STMIK IKMI Cirebon
Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Other

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Prediksi Jumlah Produksi Sablon Tahun Menggunakan Algoritma Regresi Linear di Nolbas SVNR Muhammad Fadhilah; Martanto Martanto; Irfan Ali
INTERNAL (Information System Journal) Vol. 6 No. 1 (2023)
Publisher : Masoem University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Nolbas svnr is a business engaged in the clothing industry which refers more to t-shirt screen printing. This business carries out its activities based on customer orders received through orders from individuals, shops, and schools. With the many types of screen printing that are made, the number of orders received and executed by Nolbas Svnr increases. Screen printing production at Nolbas Svnr is always changing every year. The main objective of this research is to obtain a predictive model for the amount of screen printing production using the Linear Regression method based on the number of orders obtained each year. The results that can be obtained in research can help for the supply of raw materials, the amount of raw materials, paint and so on. This study uses the linear regression method to process sales data using attributes such as year, customer name, price of goods, price of materials and the number of orders. of 0.5601. The results of the constant values ??and regression coefficients are used to predict the amount of screen printing production in 2023 at Zerobas SVNR and the predicted value is 3391. Evaluation of the multiple linear regression model shows an MAE value of 3.7247, an MSE value of 17.8633 and an R2 score of 87% .
PENERAPAN ALGORITMA SUPPORT VECTOR MACHINE UNTUK ANALISIS SENTIMEN ULASAN PELANGGAN TOKO LIVIA CIREBON DI SHOPPE Syaeful Annas; Nana Suarna; Irfan Ali; Heliyanti Susana
Jurnal Ilmiah Informatika Komputer Vol 29, No 3 (2024)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2024.v29i3.13109

Abstract

Analisis sentimen adalah proses yang bertujuan untuk memahami opini pelanggan dengan mengklasifikasikan ulasan menjadi sentimen positif, netral, atau negatif. Penelitian ini bertujuan untuk mengembangkan model analisis sentimen berbasis algoritma Support Vector Machine (SVM) terhadap ulasan pelanggan Toko Livia Cirebon di platform Shopee. Pendekatan penelitian dilakukan secara kuantitatif, dengan tahapan meliputi pengumpulan data, pra-pemrosesan teks (cleansing, normalisasi slang, tokenisasi, penghapusan stopword, dan stemming), pelabelan menggunakan Inset Lexicon, transformasi data teks menjadi vektor numerik dengan metode TF-IDF, pelatihan model SVM, serta evaluasi performa menggunakan metrik akurasi, precision, recall, dan F1-score. Model yang dikembangkan mencapai akurasi sebesar 91% dengan performa terbaik pada sentimen positif (F1-score 95%), meskipun performa pada kategori netral dan negatif masih memerlukan peningkatan. Hasil penelitian ini menunjukkan bahwa algoritma SVM efektif untuk analisis sentimen dalam e-commerce, memberikan wawasan strategis bagi pemilik usaha untuk menyusun strategi pemasaran dan meningkatkan kualitas layanan.
Optimalisasi Layanan Kesehatan di Puskesmas Melalui Pengembangan Chatbot Berbasis Web Menggunakan Flowise AI Mulyawan Mulyawan; Raditya Danar Dana; Agus Bahtiar; Irfan Ali
Jurnal Teknologi Informasi dan Multimedia Vol. 6 No. 3 (2024): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i3.617

Abstract

The development of a web-based chatbot service for Puskesmas presents a potential solution to improve the accessibility and efficiency of healthcare services. This research uses Flowise AI, a chatbot development platform that leverages machine learning technology to support dynamic information processing and provide accurate and relevant responses to users. Flowise AI is integrated with Langchain Retriever to further enhance dynamic information processing, ensuring accurate and relevant responses to users. Using the Rapid Application Development (RAD) methodology, the chatbot development follows a fast-paced cycle, enabling early prototyping and continuous user feedback. The chatbot is tested using Black Box Testing to verify functionality and System Usability Scale (SUS) to evaluate usability. The test results show that the chatbot is able to provide accurate responses to patient queries, especially on relevant health topics, with an SUS score of 75, which falls within the "good" category. This score reflects that the chatbot is easy to use and acceptable to users. This technology allows the chatbot to provide more accurate, relevant, and contextual responses to patient inquiries, while dynamically accessing information from various sources, thereby improving the efficiency and effectiveness of healthcare services.
Co-Authors Ade Irma Purnamasari Ade Rizki Rinaldi Agus Surip Agus Surip Anwar Pauji Aria Pratama Arif Rinaldi Dikananda Candi Prabowo Cep Lukman Rohmat Cep Lukman Rohmat Cep Lukman Rohmat Deffan Febrian Dirmanthara Dian Ade Kurnia Dita Rizki Amalia Edi Tohidi Ega Salsa Nugraha Farid Ali Ma'ruf Farids Al Ma’ruf Faujatun Hasanah Gifthera Dwilestari Hegarmanah Muhabatin Heliyanti Susana Iin Iqbal Agis Junizar Kaslani Kokom Komariah Lian Siliayani Lutfi Hakim Martanto . Muhamad Aji Pratama Muhammad Abdurohman Muhammad Aji Pratama Muhammad Fadhilah Mulyawan Mulyawan . Nadia Putri Gantara Nana Suarna Nining Rahaningsih Odi Nurdiawan Raditya Danar Dana Ranu Husna Riko Saputra Siti Aisyah Syaeful Annas Tati Suprapti Tio Prasetiya Tio Prasetya Utami Aryanti Uyu Nuraeni Yuniar Niar