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All Journal Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB SAINTEK
A. Yudi Permana
Universitas Pelita Bangsa
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering

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Knowledge Management System Sharing Record Teknisi Berbasis Android Pada PT. CNC Part Teknika A. Yudi Permana; Ananto Tri Sasongko; Rita Purnamasari
Jurnal SIGMA Vol 13 No 2 (2022): Juni 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Abstract Reports contain facts about news, information, notifications, and forms of activities relating to accountability. Job reports that have not been properly documented are also an obstacle for the company when a technician resigns, making it difficult to distribute the knowledge possessed by the old technician to the new technician. Knowledge Management System is one way to identify, select, disseminate and disseminate important information and expertise in an organization as an effort to develop productivity and work performance so as to increase the competitiveness of the organization. The development of information systems is fast, accurate and up to date available in the plat form, such as Android. In this case, PT. CNC Part Teknika which is engaged in the field of General Trading and Service, still uses a manual system for making information job report. One example of the report method they used paper for media report. However, this reporting method is easily lost and damaged. This research aimed to design application knowledge management system job report based on android system. In designing this application using the XP (Extreme programing) and UML (Unified Modeling Language) methods. This is expected to documenting the knowledge of technicians in handling service and help facilitate the process of making reports is up to date for technician at PT. CNC Part Teknika. This application is useful for technician workers of PT. CNC Part Teknika using a database that can be used easily and quickly. Keywords: Reports, Knowledge Management System, android, General Trading and Service, UML.
Perancangan Aplikasi Untuk Menganalisis Penyakit Menggunakan Pengobatan Tanaman Herbal Dan Cara Mengolahnya Dengan Certainty Factor Berbasis Android A. Yudi Permana
Jurnal SIGMA Vol 11 No 3 (2020): September 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Applications regarding diseases and herbal plants do not have a diagnostic system that can assist the selection process. Most of the processes used have not used disease analysis / diagnosis. Most of them provide information about diseases or about herbal plants directly. So often users have to look for diseases or plants first to find the information. The method used in designing information systems for diseases and herbal plants is a structured programming method using UML diagrams. When building this application, it takes software such as Apache as a web server, MYSQL as a database, Eclipse. The steps taken are analyzing the needs required by the application, designing according to the needs analysis, building an application program in accordance with the previously made designs, and testing the application. The results of this thesis will present that a disease information system and herbal plants can be developed using Eclipse and MYSQL database. This application that has been built can help the process of analyzing / diagnosing diseases and providing information about what herbal plants can be used as medicine and how to process these plants so that they are really easy for the user to consume. Keyword: Disease and Herbal Plants, Android, Eclipse, Apache
Komparasi Algoritma Naïve Bayes Dan K-Nearest Neighbor Dalam Melihat Analisis Sentimen Terhadap Vaksinasi Covid-19 A. Yudi Permana; Hendri Noviyani
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.128134

Abstract

Twitter is often used to deliver messages in the form of public opinion or opinion about the topic that is being reported. The government's policy to vaccinate has received various comments, ranging from praise, criticism, suggestions, and even hate speech. With so many twitter users who express their opinion, it can be used to find information. However, its use requires proper analysis, so that the resulting information can help many parties in making decisions or choices. Therefore, in this study, we tried to analyze sentiment on Covid-19 vaccination using the Naïve Bayes and K-Nearest Neighbor algorithms using the Cross Validation technique. The purpose of this study is to find out whether the Naïve Bayes and K-Nearest Neighbor algorithms in classifying produce optimal accuracy, to determine the sentiments of twitter users towards the Covid-19 vaccination and how much influence preprocessing has to measure accuracy on the classification. Based on the research that has been carried out, it can be concluded that the application of preprocessing for sentiment analysis on Covid-19 vaccination using the Naïve Bayes and K-Nearest Neighbor algorithms accompanied by the use of the Cross Validation technique got quite good results. The Naïve Bayes algorithm produces an accuracy of 77.62% and the K-Nearest Neighbor algorithm produces an accuracy of 76.43. Then for the positive response rate of the community to the Covid-19 vaccination, it was 55.63%. Keywords: Comparison, Naïve Bayes, K-Nearest Neighbor, Sentiment Analysis,Vaccination, RapidMiner
Co-Authors Ananto Tri Sasongko Hendri Noviyani Rita Purnamasari