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All Journal Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Mantik Jurnal Kajian Ilmiah
Siti Nur Khasanah
STMIK Nusa Mandiri
Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Sentimen Analisis Publik Terhadap Joko Widodo terhadap wabah Covid-19 menggunakan Metode Machine Learning Sisferi Hikmawan; Amsal Pardamean; Siti Nur Khasanah
Jurnal Kajian Ilmiah Vol. 20 No. 2 (2020): Mei 2020
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (532.285 KB) | DOI: 10.31599/jki.v20i2.117

Abstract

Abstract Analyzing public sentiment towards a government policy is no longer impossible, the process of analyzing with data mining is a method that is often used. The Data Mining method is always related to the dataset, with the keywords "Jokowi" and "Covid" twitter allowing us to make tweets in it to be used as a dataset. In data mining for sentiment analysis, techniques such as transform, tokenize, stemming, classification, etc. are very influential on its accuracy. Gata Framework is used for preprocessing, and Rapidminer is also used to analyze and compare three classification methods namely Naive Bayes, Support Vector Machine, and k-NN. And the best value is obtained, the Support Vector Machine with an accuracy of 84.58%, precision 82.14% and recall 85.82%. Keywords: Covid, Jokowi, SVM, K-NN, Naive Bayes Abstrak Menganalisa sentimen publik terhadap suatu kebijakan pemerintah merupakan cara yang tidak lagi mustahil, proses analisa dengan data mining merupakan metode yang sering digunakan. Metode Data Mining selalu berkaitan dengan dataset, dengan kata kunci “Jokowi” dan “Covid” twitter memungkinkan kita menjadikan tweet didalamnya untuk dijadikan dataset. Dalam data mining untuk sentimen analisis, dilakukan teknik seperti transform, tokenize, stemming, classification, dan lain-lain sangat berpengaruh pada akurasinya. Gata Framework digunakan untuk preprocessing, dan Rapidminer juga digunakan untuk menganalisa dan membandingkan tiga metode klasifikasi yaitu Naive Bayes, Support Vector Machine, dan k-NN. Dan dihasilkan nilai terbaik yaitu Support Vector Machine dengan accuracy 84.58%, precision 82.14% dan recall 85.82%. Kata kunci: Covid, Jokowi, SVM, K-NN, Naive Bayes
Service Information System Animal Product Testing at Bogor's Quality Testing & Certification Center for Animal Products (BPMSPH) Sandra Jamu Kuryanti; Siti Nur Khasanah; Eko Yulianto
Jurnal Mantik Vol. 5 No. 1 (2021): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol5.2021.1257.pp35-40

Abstract

The Bogor Animal Product Quality & Certification Testing Center (BPMSPH) in carrying out the testing service process still uses the system of meeting directly with service users to carry out tests and use paper media for recording service user data. Services and data processing like this require considerable effort and time, the risk of damage to paper as a medium for recording service user data is also a problem. Therefore, a web-based animal product testing service information system design was made at the Bogor Animal Product Quality & Certification Testing Center (BPMSPH) which uses the waterfall model as a software development method and the data collection techniques used consist of observations, interviews and literature studies. This designed system provides online testing services where service users can fill out test forms anywhere without having to go directly to BPMSPH. Hopefully this web-based testing service system can make it easier for service users to carry out tests at the Bogor Animal Product Quality & Certification Testing Center (BPMSPH).
Perancangan E-Commerce Berbasis Web Pada PT. Touch Technology Indonesia Ahmad Saubani; Esron Rikardo Nainggolan; Siti Nur Khasanah
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 2 No. 4 (2019): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Sales in this case in the form of product sales is one of the important activities for the development of the company and is a very important aspect for the company. Problems a rising in the company regarding the promotion and sales, because it still uses manually, visit home for promotion and provide brochures on the road side, System design used with a waterfall methode, while the data collection techniques use research methods with observation, interviews, and library studies. And database application development tools use MySQL and PHP programming language by using Laravel framework. The purpose of this research is to design a sales system evenly and ease of transaction customers without having to come to physical stores directly. The result of this research is to provide an alternative sales and promotion. It is application created can create increase in company sales.
Co-Authors Ahmad Saubani Amsal Pardamean Eko Yulianto Esron Rikardo Nainggolan Sandra Jamu Kuryanti Sisferi Hikmawan