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All Journal Bina Insani ICT Journal Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Teknologi Terpadu JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Education Transportation and Business
Sri Dewi
Universitas Negeri Medan
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Neuroscience Transportation

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Analisis perbandingan Algoritma Support Vector Machine, Naive Bayes dan Regresi Logistik untuk Memprediksi Donor Darah Hendriyana Hendriyana; Ichwanul Muslim Karo Karo; Sri Dewi
Jurnal Teknologi Terpadu Vol. 8 No. 2 (2022): December, 2022
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v8i2.581

Abstract

Blood supplies and stocks are urgently needed. Regular donations from healthy volunteers are the only way to keep up with the blood supply. This research aims to develop and evaluate a machine-learning algorithm to predict whether a volunteer will donate or not. The machine learning algorithms are Naïve Bayes, Logistic Regression, and Support Vector Machine (SVM). This study also applies the process of normalizing data with a Z-score to standardize the dataset scale. The dataset is sourced from the Hsin-Chu City Blood Transfusion Service, Taiwan, and stored in the UCI repository. The evaluation methods are accuracy, precision, recall, and F-1 score. The research results with the Naïve Bayes algorithm were 89.90%, Logistic Regression 82.59%, and SVM 94.79%. The normalization process using the Z-Score method contributes positively to improving the performance of the classification model. Based on this performance, it provides predictive results for volunteers who will return to donate blood to offer blood reserves to those in need.
Hoax Detection on Indonesian Tweets using Naïve Bayes Classifier with TF-IDF Ichwanul Muslim Karo Karo; Romia Romia; Sri Dewi; Putri Maulidina Fadilah
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3317

Abstract

Twitter is one of the most popular social media platforms in the world nowadays. Twitter users in Indonesia are the fifth largest in the world and are always active in expressing themselves and getting information through tweets. A hoax is a lie created as if it were true. Hoaxes are also often spread via tweets. The spread of hoaxes is extremely dangerous because it can cause social discord and even misunderstanding. Therefore, hoaxes must be resisted. This study aims to build a system to detect hoaxes on Indonesian tweets. The objective of this research is to identify hoax Indonesian tweets by using the Naïve Bayes classifier with Term Frequency Inverse Document Frequency (TF-IDF). This study collects and annotates tweets from hoax tweets post which sent by a user account. This study also applied several text preprocessing techniques to provide datasets. To provide the best hoax prediction model, this work splits datasets into training and testing datasets. There are four experimental scenarios that refer to splitting the dataset. The experimental results showed that the hoax prediction model using Naïve Bayes with TF-IDF had 64% accuracy and recall, 69% and 67% precision, and a F1-score respectively. This result is also superior to the hoax prediction model when using the Naïve Bayes classifier without the TF-IDF. It means that TF-IDF has made a positive contribution to improving model performance. Finally, this research contributes by detecting news with a proclivity for hoaxes and filtering what is classified as hoaxes or not.
Penerapan Metode Forward Chaining pada Sistem Pakar Diagnosa Penyakit Tanaman Kelapa Sawit Sri Dewi
Bahasa Indonesia Vol 10 No 1 (2023): Bina Insani ICT Journal (Juni) 2023
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/biict.v10i1.2301

Abstract

Sitem Pakar adalah sistem berbasis komputer yang dirancang untuk dapat meniru keahlian seorang pakar dalam memecahkan masalah. Metode yang digunakan dalam perancangan sistem pakar ini adalah metode Forward Chaining. Metode Forward Chaining merupakan suatu metode penalaran yang dimulai dari fakta untuk mendapatkan kesimpulan. metode Forward Chaining digunakan dalam sistem pakai ini sehingga dapat mendiagnosa penyakit tanaman kelapa sawit dan dapat memberikan solusi serta cara pengendalian penyakit tanaman kelapa sawit yang terserang penyakit berdasarkan gejala-gejala yang dipilih oleh user. Ada 5 jenis penyakit tanaman kelapa sawit dan 19 gejala penyakit tanaman kelapa sawit dengan 11 rule yang diterapkan dalam sistem pakar yang dirancang. Hasil prosedur ini akan menghasilkan fakta - fakta penyakit tanaman kelapa sawit dan solusi yang ditawarkan sistem untuk selanjutnya dilakukan penanganan pada tanaman kelapa sawit.
Perbandingan Kinerja Algoritma Naive Bayes dan Random Forest dalam Analisis Sentimen Publik Terhadap Batas Usia Calon Presiden dan Wakil Presiden di Twitter Mei Lammi Malau; Steviana Viviola Wicesti Nasution; Putri Tasya Agustina; Sri Dewi; Fanny Ramadhani
Journal of Education Transportation and Business Vol 1, No 2 (2024): Desember 2024
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/jetbus.v1i2.4187

Abstract

Pada pemilu di tahun 2024 ini, terdapat pro dan kontra terkait perubahan batas usia calon presiden dan wakil presiden yang memicu perdebatan di kalangan masyarakat khususnya perdebatan yang terjadi pada media sosial seperti X(twitter). Penelitian ini akan membandingkan dua algoritma machine learning yaitu Naive Bayes dan Random Forest untuk melihat kinerja yang lebih baik dalam mengklasifikasikan sentimen. Penelitian ini bertujuan untuk mengukur sentimen publik terhadap perubahan kebijakan perubahan batas usia calon presiden dan wakil presiden pada  media sosial X(twitter) dengan menggunakan teknik analisis sentimen. Penelitian ini membandingkan kinerja algoritma Naive Bayes dan Random Forest dalam analisis sentimen publik terkait batas usia calon presiden dan wakil presiden di Indonesia, menggunakan data X (Twitter). Data sentimen yang dianalisis berasal dari 500 tweet pengguna X (Twitter) menggunakan kata kunci "Putusan MK Usia Capres". Proses praproses meliputi cleaning, case folding, normalisasi, tokenisasi, penghapusan stopword, stemming kemudian fitur teks diekstraksi menggunakan metode TF-IDF. Hasil dari penelitian ini menunjukan bahwa algoritma Random Forest memiliki kinerja yang lebih baik dan tingkat akurasi yang lebih tinggi dari algoritma Naive Bayes dengan nilai akurasi 50.00%.
Sistem Informasi Travel Haji dan Umroh Berbasis Website Erika Putri Fadluna; Sri Dewi; Deswita Ananda; Nur Rizkah Khoiriyah Pohan
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 2 (2025): April 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i2.8954

Abstract

Abstrak - Perkembangan teknologi informasi telah mendorong transformasi sistem pelayanan pada berbagai sektor, termasuk industri perjalanan haji dan umrah. Penelitian ini mengembangkan sebuah sistem informasi manajemen berbasis web yang dirancang untuk meningkatkan efisiensi dan akurasi proses pendaftaran serta pengelolaan data calon jamaah. Metodologi yang digunakan meliputi identifikasi masalah, studi literatur, observasi langsung, analisa kebutuhan sistem, perancangan model menggunakan UML, dan pembuatan prototipe melalui metode prototyping. Implementasi sistem mencakup fitur-fitur seperti halaman homepage, form login, formulir pendaftaran, pengelolaan data jamaah, dan pengelolaan pembayaran, yang diuji melalui serangkaian pengujian untuk memastikan validitas dan kesesuaian fungsionalitasnya. Hasil penelitian menunjukkan bahwa sistem berbasis web ini mampu mengatasi keterbatasan sistem manual, meningkatkan kecepatan serta akurasi pengolahan data, dan memberikan kemudahan akses bagi calon jamaah. Dengan demikian, sistem ini diharapkan dapat meningkatkan profesionalisme penyelenggaraan dan daya saing layanan haji dan umrah di era digital.Kata kunci: Teknologi Informasi, Sistem Informasi Manajemen, Haji dan Umrah, Pendaftaran Online, Prototyping, UML Abstract  - The advancement of information technology has driven the transformation of service systems across various sectors, including the Hajj and Umrah travel industry. This research develops a web-based management information system designed to improve the efficiency and accuracy of the registration process and the management of prospective pilgrims' data. The methodology employed includes problem identification, literature review, direct observation, system requirements analysis, model design using UML, and prototype development through the prototyping method. The system implementation features components such as a homepage, login form, registration form, management of pilgrim data, and payment management, which are tested through a series of evaluations to ensure functionality validity and adequacy. The study's results indicate that this web-based system is capable of overcoming the limitations of manual systems, enhancing the speed and accuracy of data processing, and providing easier access for prospective pilgrims. Thus, this system is expected to improve the professionalism of service provision and the competitiveness of Hajj and Umrah services in the digital era.Keywords: Information Technology, Management Information System, Hajj and Umrah, Online Registration, Prototyping, UML
Co-Authors Deswita Ananda Erika Putri Fadluna Hendriyana Hendriyana Ichwanul Muslim Karo Karo Mei Lammi Malau Nur Rizkah Khoiriyah Pohan Putri Maulidina Fadilah Putri Tasya Agustina Ramadhani, Fanny Romia Romia Steviana Viviola Wicesti Nasution