16 research outputs found
Classification of Patient Satisfaction Level on Health Services Using the C4.5 Algorithm
No full textQuality health services are related to patient satisfaction. Patient satisfaction can be used as a benchmark for improving the quality of health services. Problems often occur when implementing health techniques, such as service problems at the Restu Clinic. Patients and their families indicated that although the Restu Clinic was established with adequate facilities, it had not yet reached the maximum level of service. These indications include long waiting times for examinations, a lack of thoroughness by medical personnel, and services that are not timely. Service quality cannot be separated from the dimensions that are the core of quality services, which are expected to meet patient needs. Patient satisfaction is considered an important indicator of good quality. This research will only discuss four aspects of service quality, which are reliability, responsiveness, assurance, and empathy, from health workers at the Restu Clinic. The C4.5 algorithm is known to be superior in producing decision trees that efficiently solve discrete and numerical variables and provide satisfactory accuracy. Therefore, the author conducted a study to assess service quality using the C4.5 algorithm. This research aims to determine the factors that influence the quality of health services and to know patient satisfaction with health services at the Restu Clinic. Knowing the intensity of patient satisfaction with services at the Restu Clinic can improve the quality of optimal services and gain patients' trust in government agencies
Analisis Perbandingan Waktu Enkripsi Menggunakan Algoritma Message-Digest 5 (MD5) Dan Algoritma Affine Cipher Dalam Enkripsi Pesan
No full textKriptografi merupakan ilmu yang digunakan untuk menyamarkan pesan yang akan
dikirim/transmit oleh pengirim ke penerima pesan. Teknik untuk mengamankan pesan adalah
dengan mengenkripsi pesan tersebut menjadi tidak dapat dibaca secara utuh atau informasi sudah
diacak. Salah satu algoritma yang cukup banyak digunakan sampai saat ini yaitu algoritma MD5
yang hasil enkripsinya berupa hash dengan panjang 32 bit. Kemampuan algoritma MD5 diakui
sampai sekarang masih digunakan dalam melakukan enkripsi pada banyak aplikasi maupun
website. Algoritma affine cipher merupakan algoritma dengan tipe kunci simetris yang juga
sering digunakan dalam mengamankan pesan. Pada penelitian ini, penulis menganalisis kinerja
algoritma MD5 dan juga algoritma affine cipher berupa analisis waktu enkripsi berdasarkan
panjang pesan yang akan dienkripsi serta cipherteks yang dihasilkan untuk dari proses enkripsi
dari kedua algoritma tersebut
Analisis Kombinasi Message-Digest Algorithm 5 (MD5) dan Affine Block Cipher terhadap Serangan Dictionary Attack Untuk Keamanan Router Weblogin Hotspot
No full textCryptography is the science of disguising the messages so that only well known by the provider and the recipient. One of the algorithm that is quite a lot of used until this time is algorithm message-digest 5 or MD5. The output produced by the algorithm MD5 be hash. But this algorithm has many found weakness because the length of the bit is used. In this research, the authors analyze the performance of the algorithm MD5 and combine with affine algorithm block cipher for can reduce the weakness that exist on the algorithm MD5. The results obtained from this research is the affine algorithm block cipher have a good security level because it has the key length of value n of 255255255255 and have numbers relatively prima available as much as 117710117810.Kriptografi adalah ilmu yang digunakan untuk menyamarkan pesan yang akan dikirim oleh pengirim ke penerima pesan. Salah satu algoritma yang cukup banyak digunakan sampai saat ini yaitu algoritma message-digest 5 atau MD5. Output yang dihasilkan oleh algoritma MD5 berupa hash. Namun algoritma ini telah banyak ditemui kelemahannya karena panjang bit yang digunakan. Pada penelitian ini, penulis menganalisa kinerja dari algoritma MD5serta mengkombinasikan dengan algoritma affine block cipher untuk dapat mengurangi kelemahan yang ada pada algoritma MD5. Hasil yang diperoleh dari penelitian ini adalahalgoritma affine block cipher memiliki tingkat keamanan yang cukup baik karena memiliki panjang kunci yang bernilai n sebesar 255255255255 dan memiliki bilangan relatif prima yang tersedia sebanyak 117710117810.81 HalamanTesis Magiste
Islamophobia Sentiment Classification Using Support Vector Machine
No full textSentiment analysis is the process of understanding and classifying words into several categories. It is also known as opinion mining, which involves exploring opinions and emotions from text data. Sentiments can be classified into positive, negative, and neutral categories. Islam is a religion that has been in existence for centuries. Its teachings aim to foster peace and surrender to its creator, namely Allah SWT. The constructivist view of Islam has given rise to Islamophobia, which is the result of a long-standing construct that presents a negative image of Islam. Currently, Islamophobia is a growing issue that generates diverse views, especially on social media platforms. The analysis was conducted using the SVM algorithm and a dataset comprising 1000 tweets sourced from Twitter. The algorithm achieved an accuracy rate of 99.99% after testing, indicating its suitability for sentiment analysis. The error rate generated using MSE was 0.010, while the RMSE was 0.099
Sentiment Analysis on TikTok Discourse Surrounding the 2024 North Sumatra Gubernatorial Election Using Support Vector Machine Algorithm
No full textThis study aims to analyze public sentiment towards the 2024 North Sumatra gubernatorial election by leveraging social media data, specifically TikTok, which has become a major platform for political discourse in Indonesia. The two competing candidate pairs, Bobby Nasution–Surya and Edy Rahmayadi–Hasan Basri, have sparked widespread online discussions that range from enthusiastic support to harsh criticism. These interactions have a significant impact on public opinion formation and may influence electoral outcomes. To address this phenomenon, this research implements a sentiment classification model using the Support Vector Machine (SVM) algorithm with a polynomial kernel, known for its effectiveness in handling high-dimensional textual data. A total of 2,100 TikTok comments were collected using scraping techniques via Python. The data then underwent several preprocessing stages, including case folding, cleaning, normalization, tokenizing, slangword removal, stopword removal, and stemming. Feature extraction was conducted using the TF-IDF method, followed by lexicon-based sentiment labeling into positive and negative classes. The classification model achieved an accuracy of 82%, with a positive sentiment precision of 0.81, recall of 0.96, and F1-score of 0.88. For negative sentiment, the precision was 0.86, recall 0.51, and F1-score 0.64. These findings indicate that the model performs well in identifying explicit positive sentiments but faces challenges in recognizing complex negative expressions such as sarcasm or implicit criticism. The results provide valuable insights into digital political behavior and demonstrate the potential of machine learning-based sentiment analysis as a tool for monitoring public perception in real time during elections
PERANCANGAN SISTEM INFORMASI DISPOSISI SURAT MASUK BERBASIS WEB PADA KANTOR BADAN PENDAPATAN DAERAH KOTA MEDAN
No full textTeknologi informasi sangat diperlukan untuk menunjang proses kerja dan pelayanan masyarakat. Salah satu jenis teknologi informasi yang digunakan pada instansi pemerintah adalah website. Setiap perusahaan atau instansi memiliki berbagai sarana yang dapat membantu instansi memberitahukan informasi kepada pihak lain. Salah satunya dengan menggunakan surat. Penerimaan dan disposisi surat merupakan layanan masyarakat yang harus ditingkatkan pada Badan Pendapatan Daerah Kota Medan. Maksud dari riset ini adalah menciptakan sebuah platform berbasis web yang dapat mempermudah atasan dalam mengirimkan surat kepada bawahannya. Proses disposisi ini akan mengirimkan pemberitahuan kepada karyawan terkait dan memungkinkan pengguna untuk mengaksesnya secara langsung melalui sistem informasi berbasis situs web. Pada penelitian ini, peneliti merancang teknologi informasi seperti sistem informasi berbasis web untuk menjadi solusi dalam mengatasi kendala pengelolaan surat secara manual serta membantu Meningkatkan efisiensi dan produktivitas dalam memproses surat masuk dan disposisi menjadi fokus utama dalam penelitian ini. Pendekatan yang diambil melibatkan pemanfaatan metode kualitatif dan penerapan metode pengembangan waterfall
Sentiment Analysis of Loudspeaker Regulations in Houses of Worship on Social Media Using Support Vector Machine Algorithm
No full textSocial media is an online platform where users can share content or interact with each other through discussions and debates that involve sentiments, such as agreement or disagreement on various topics. User sentiments on social media can be utilized in multiple ways, such as to gauge public opinion regarding the issuance of Circular Letter Number SE 05 of 2022 by the Ministry of Religious Affairs, which provides guidelines for the use of loudspeakers in mosques and prayer rooms. Due to the high volume of comments on social media regarding this circular, a sentiment analysis system is necessary. The sentiment analysis system in this research employs the Support Vector Machine (SVM) algorithm to classify comments as positive or negative. A total of 350 comments were collected from each social media platform—Facebook, Twitter, YouTube, and Instagram—about the issuance of the circular. These comments were divided into 250 for training data and 100 for testing data on each platform. The training data from all platforms were combined, resulting in a total of 1000 training data. Based on system testing using the Support Vector Machine algorithm, the accuracy achieved was 72%. This result reflects the system's capability to analyze sentiments related to the guidelines for using loudspeakers in mosques and prayer rooms as stated in the circula
Klasifikasi Pengaruh Negatif Game online Bagi Remaja Menggunakan Algoritma Naïve Bayes
No full textPenelitian ini bertujuan untuk mengklasifikasikan pengaruh negatif game online bagi remaja menggunakan algoritma Naïve Bayes. Data diperoleh dari 265 siswa/siswi SMA Negeri 2 Padang Bolak dan diklasifikasikan ke dalam tiga tingkat: Ringan, Sedang, dan Parah. Sebanyak 250 data digunakan untuk pelatihan dan 15 data untuk pengujian. Hasil pengujian menunjukkan bahwa 12 dari 15 data berhasil diklasifikasikan dengan benar (akurasi 80%). Precision dan recall tertinggi terdapat pada kelas Ringan dan Sedang, sementara kelas Parah tidak terdeteksi. Naïve Bayes efektif untuk klasifikasi ringan dan sedang, namun perlu perbaikan untuk kelas parah
