SENTIMENT ANALYSIS WITH A CASE STUDY OF PRACTICE CARD ON TWITTER SOCIAL MEDIA USING NAIVE BAYES METHOD

-In early March 2022, Indonesia experienced a coronavirus pandemic which caused COVID-19 to enter for the first time. Since then, all sectors have been affected by the COVID-19 pandemic, not only health, the economic sector has also been seriously affected by this pandemic. In overcoming employment problems, the government makes a policy of the Pre-Employment Card program. The Pre-Employment Card Program is one of the government's efforts to expand job opportunities and to increase competitiveness which later became one of the social assistance for the community to overcome the Covid-19 pandemic. The  implementation of the Pre-Employment Card program received pros and cons from the community, one of which was on Twitter social media. The results of the sentiment analysis of the pre-employment card program are mostly positive. The test results show that the Naïve Bayes Classifier method is successful in classifying sentiment with the highest accuracy value of 96%, the highest precision value of 98%, and the highest recall value of 96%, and AUC of 96%

IMAGE BACKGROUND PROCESSING FOR COMPARING ACCURACY VALUES OF OCR PERFORMANCE

Optical Character Recognition (OCR) is an application used to process digital text images into text. Many documents that have a background in the form of images in the visual context of the background image increase the security of documents that state authenticity, but the background image causes difficulties with OCR performance because it makes it difficult for OCR to recognize characters overwritten by background images. By removing background images can maximize OCR performance compared to document images that are still background. Using the thresholding method to eliminate background images and look for recall values, precision, and character recognition rates to determine the performance value of OCR that is used as the object of research. From eliminating the background image with thresholding, an increase in performance on the three types of OCR is used as the object of research

Faktor Pengaruh Niat Pengguna Dalam Menggunakan Aplikasi Pendaftaran Pasien Online Pada RSUD Banyumas

Based on the development of technology and information at this time, registrations carried out by patients both in hospitals or clinics, industry and health centers and other health industries have often been carried out using application media which will make it easier for patients to register online. From the development of technology, researchers interesting in conducting a study on the factors that influence the intention to use an online patient registration application in Banyumas Regency, especially in Banyumas Hospital. This study uses the Technology Acceptance Model and SEM modeling. Based the results of data analysis, 6 hypotheses were accepted between the hypothesis of technology use attitudes towards behavioral intentions to use, perceptions of ease of use towards attitudes to technology use, perceptions of ease of use to perceived usefulness, perceptions of service availability. on perceptions of ease of use, perceptions of service availability to perceptions of usefulness, and perceptions of usefulness on attitudes towards technology uses.   Keywords: patient registration, hospital, technology acceptance model, smartPLS   Abstrak   Berdasarkan semakin berkembangnya teknologi dan informasi di masa sekarang ini, pendaftran yang dilakukan oleh pasien baik dirumah sakit atau klinik, industry serta puskemesmas dan industry kesehatan lainnya telah sering dilakukan menggunakan media aplikasi yang nantinya akan memudahkan pasien untuk melakukan pendaftaran secara online. Dari adanya perkembangan teknologi maka dalam hal ini tertarik melakukan sebuah penelitian tentang faktor-faktor yang mempengaruhi niat untuk menggunakan aplikasi registrasi pasien secara online di Kabupaten Banyumas khusunya pada RSUD Banyumas. Penelitian ini menggunakan metode Technology Acceptance Model dan pemodelan SEM. Berdasarkan hasil analisis data, maka diterima 6 hipotesis antara hipotesis sikap penggunaan teknologi terhadap niat perilaku menggunakan, persepsi kemudahan penggunaan terhadap sikap penggunaan teknologi, persepsi kemudahan penggunaan terhadap kegunaan yang dipersepsikan, persepsi ketersediaan layanan. terhadap persepsi kemudahan penggunaan, persepsi ketersediaan layanan hingga persepsi kegunaan, serta persepsi kegunaan terhadap sikap terhadap penggunaan teknologi.   Kata kunci: Pendaftaran pasien, rumah sakit, Technology Acceptance Model, SmartPL

SISTEM INFORMASI PENJUALAN TIKET MASUK WISATA JEMBATAN CINTA BERBASIS WEB

Abstract— The use of technology in the tourism industry is becoming increasingly crucial considering changes in consumer behavior that tend to rely on digital platforms to make transactions. To analyze the effectiveness and reliability of facilitating the process of purchasing tickets online. In addition, it also includes an evaluation of the level of user satisfaction with this web-based system and its impact on increasing visits to the Cinta Bridge tourist attraction. Through surveys of tourists using a web-based ticket sales system, interviews with tour managers, and analysis of ticket transaction data documented in the system. Research participants include tourists, managers, and other related parties. The data were obtained and analyzed using statistical methods and qualitative analysis to gain a thorough understanding of the impact of the Web-Based Bridge Tourism Entrance Ticket Sales Information System. Demonstrating that managing ticket stock and arranging visit schedules more efficiently is also a positive result for the development of the technology-based tourism industry by proving the benefits of the Web-Based Bridge of Love Entrance Ticket Sales Information System. The results of this study can be the basis for the development and implementation of similar systems in other tourism destinations. In addition, the research is considered to provide valuable insights for related parties in optimizing the use of technology to improve user experience and operational efficiency in the tourism secto

Pengaruh modal, tingkat pendidikan dan teknologi terhadap pendapatan umkm di kabupaten purbalingga

Usaha Mikro, Kecil dan Menengah (UMKM) mempunyai peran penting dan strategis dalam pembangunan ekonomi nasional. Meskipun UMKM telah diakui memiliki peran dalam perekonomian nasional, namun dalam proses berjalannya usaha masih terdapat kendala dan hambatan yang dihadapi oleh pelaku UMKM. Kendala tersebut antara lain keterbatasan modal usaha, keterbatasan sumber daya manusia (SDM) dan keterbatasan teknologi. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh modal, tingkat pendidikan dan teknologi terhadap pendapatan UMKM yang ada di Kabupaten Purbalingga. Penelitian ini menggunakan teknik pengambilan sampel Simple Random Sampling dan pengumpulan data menggunakan kuesioner yang disebarkan kepada responden yaitu pemilik UMKM. Teknik analisis data menggunakan regresi linier berganda. Hasil penelitian menunjukkan bahwa faktor modal dan teknologi memiliki pengaruh yang signifikan terhadap pendapatan usaha, sehingga semakin besar modal yang dimiliki dan semakin tinggi penggunaan teknologi suatu usaha maka akan semakin besar pula pendapatan usahanya. Sedangkan tingkat pendidikan dinyatakan tidak memiliki pengaruh yang signifikan terhadap pendapatan usaha

Peramalan Data Kunjungan Wisatawan Mancanegara ke Indonesia menggunakan Fuzzy Time Series

Wisatawan mancanegara memegang peranan penting terhadap pertumbuhan ekonomi dari sektor pariwisata. Untuk meningkatkan kunjungan wisatawan mancanegara perlu dilakukan pembangunan yang berkelanjutan pada sektor pariwisata. Pembangunan yang dilakukan harus sejalan dengan tren pertumbuhan kunjungan wisatawan mancanegara agar pembangunan tepat sasaran, efektif dan efisien. penelitian ini bertujuan untuk meramalkan kunjungan wisatawan mancanegara ke Indonesia menggunakan metode Fuzzy Time Series. Data historis yang digunakan adalah data kunjungan wisatawan mancanegara ke Indonesia periode Januari Tahun 2013 sampai dengan Desember Tahun 2017 dari Badan Pusat Statistik (BPS). Implementasi Fuzzy Time Series pada data historis menghasilkan Mean Absolute Percentage Error (MAPE) sebesar 4,42 % dengan tingkat kesalahan tertinggi sebesar sebesar 18,05% pada Januari 2014 dan kesalahan terendah sebesar 0,04% pada Mei 2017. Hasil tersebut menunjukan bahwa penggunakan Fuzzy Time Series pada peramalan data kunjungan wisatawan mancanegara ke Indonesia memiliki hasil yang sangat baik

IDENTIFICATION OF HERBAL PLANT BASED ON LEAF IMAGE USING GLCM FEATURE AND K-MEANS

Medicinal plants are one of the groups of plants that have enormous benefits for humans because they can help the medical process for healing disease. Herbal plants can be used as ingredients for medicines, medicines produced from herbal plants are also natural. Lack of knowledge of herbal plants causes people to prefer chemical-based medicines to help cure their diseases, even though chemical-based drugs have side effects on human health. This study aims to identify types of herbal plants based on the extraction of contrast, correlation, energy, and homogeneity features as well as shape recognition based on metric and eccentricity values. The method used in this research is GLCM features and K-means clustering. In this study, the data used consisted of 352 data divided into 320 training data and 32 testing data. This research succeeded in identifying and classifying herbal plant species using GLCM features and K-means clustering segmentation with an average accuracy value of 85.94%