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All Journal Syntax Jurnal Informatika Seminar Nasional Informatika (SEMNASIF) International Journal of Artificial Intelligence Research Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Faktor Exacta JOURNAL OF APPLIED INFORMATICS AND COMPUTING Conference on Innovation and Application of Science and Technology (CIASTECH) Petir Digital Zone: Jurnal Teknologi Informasi dan Komunikasi MIND (Multimedia Artificial Intelligent Networking Database) Journal Building of Informatics, Technology and Science Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TIN: TERAPAN INFORMATIKA NUSANTARA Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) DECODE: Jurnal Pendidikan Teknologi Informasi Scientific Student Journal for Information, Technology and Science Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Jurnal Informatika: Jurnal Pengembangan IT Jurnal Komtika (Komputasi dan Informatika)
Hanny Hikmayanti Handayani
Teknik Informatika, Universitas Buana Perjuangan, Karawang
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Journal : Building of Informatics, Technology and Science

 1 
Analisis Sentimen Ulasan Aplikasi Identitas Kependudukan Digital Menggunakan Algoritma Logistic Regression dan K-Nearest Neighbor Setiawan, Bagus; Baihaqi, Kiki Ahmad; Nurlaelasari, Euis; Handayani, Hanny Hikmayanti
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5389

Abstract

The government has launched the latest innovation in data collection in the realm of population data which relies on digital technology through mobile applications using photos or QR codes which aims to reduce the use of physical prints of identity cards and the availability of blank KTPs with the aim of simplifying the administrative process and no longer requiring population documents. printing or saving in physical format such as an KTP file. In implementing the population identity application, some people feel anxious due to limited internet access, lack of knowledge about the application, as well as concerns about the security and privacy of identity data in digital format. This research aims to conduct sentiment analysis on reviews of digital population identity applications by comparing logistic regression and k-nearest neighbor algorithms. The dataset was taken using the Google Play Scraper library in Python which got 1700 raw data taken from 12-February to 26 March 2024 and then pre-processed and got 1108 clean data. The results of this research show that the comparison between the logistic regression algorithm and k-nearest neighbor algorithm shows that the k-nearest neighbor algorithm is better than the logistic regression algorithm with an accuracy result of 80.43%, a difference of 3.60% compared to k-nearest neighbor. So it can be concluded that the digital population identity application is still considered poor in its use because it has a negative sentiment of 73.9% and it can be seen in this research that the comparison results of the k-nearest neighbor algorithm prove that its performance is better than logistic regression
Implementasi Metode Resampling Dalam Menangani Data Imbalance Pada Klasifikasi Multiclass Penyakit Thyroid Nugraha, Najmi Cahaya; Hikmayanti, Hanny; Indra, Jamaludin; Juwita, Ayu Ratna
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5652

Abstract

It is estimated that at least 17 million Indonesians suffer from thyroid disorders. Interestingly, nearly 60% of those living with a thyroid disorder do not receive a diagnosis. Thus, it is necessary to carry out research that applies methods to predict thyroid disease. Before applying prediction methods, it is crucial to implement classification methods to obtain an accurate prediction model. However, to achieve optimal classification results and to avoid inaccuracies, a balance in the used data is required. Data imbalance is a condition where the ratio between classes in the data is uneven, which can result in the generated model becoming biased. The main objective of the research is to present a solution that can improve the accuracy of early detection of thyroid diseases through addressing data imbalance and implementing appropriate classification algorithms. The research methodology began with the collection and analysis of a dataset consisting of 9172 data points. Preprocessing was then performed, resulting in 5321 training data points and 1331 test data points. The testing phase employed 7 different classification algorithms with 7 different resampling methods and evaluation using a confusion matrix. This research achieved the highest accuracy rate of 98%, obtained from the combination of the Random Forest Algorithm and the Random Over Sampling method. It can be concluded that the combination of the Random Forest Algorithm with the Random Over Sampling resampling method can improve early detection accuracy for thyroid diseases.
Co-Authors AA Sudharmawan, AA Ahmad Fauzi Ahmad Fauzi Ajie, Prasetyo AL-MUDZAKIR, TOHIRIN Alif Kirana Amril Mutoi Siregar Andri Safari Anis Fitri Nur Masruriyah Anis Fitri Nurmasruriyah Anton Romadoni Junior April Lia Hananto Arfian Pua Meno Aries Suharso Arif Nurman Arphilia Nur Rani Ayu Ratna Juwita Bagus Setiawan Baihaqi, Kiki Ahmad Banafshah Shafa Bilawa, Firdho Akbar Carudin . Chorirotun Cholifah Cucu Sri Cahyanti Deden Wahiddin Devi Fitrianah Dina Wulan Nurjanah Dinar Sugiri Dinda Resna Amalia Dwi Sulistya Kusumaningrum Dwi Vina Wijaya Dwiki Jatikusumo Emilia, Cici Enoh Suhada Fadmadika, Fadilla Faisal, Sutan Fauzi Ahmad Muda Firdaus, Thoriq Janati Fitri Nur Masruriyah, Anis Garno . Genta Kusuma Atmaja Heri Hermawan Hilda Fitriana Dewi Indra, Jamaludin Jannah, Malika Dakhola Jayidan, Zirji Juwita, Ayu Ratna Lestari, Santi Arum Puspita Mudzakir, Tohirin Al Muhamad Enoh Suhada Nai Siti Jenab Nazori AZ Nita Fitriyani Nofita Sari Nova Wulandari Nugraha, Najmi Cahaya Nunung Nurjanah Nurlaelasari, Euis Pajar Arifin Pratama, Adi Rizky Rafikoh, Zahra Anggun Rahmat Rahmat Rahmat, R Ramadhan, Naufal Cahya RAMDANI, MUHAMAD IKBAL Ricky Steven Chandra Ridwan, Ridwan Rohana, Tatang Sandi Susanto Saputra, Arbi Niandi Saruni Dwiasnati Septiany, Eva Senia Setyawan Widyarto Siregar, Amril Mutoi suhliyyah Sukmawati, Cici Emilia Sutan Faisal Tri Vicika, Vikha Wahiddin, Deden Wicaksana, Yusuf Eka Yana Cahyana Yogi Firman Alfiansyah