Article Per Year (5 Year)
p-Index From 2021 - 2026
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All Journal International Journal of Information Engineering and Science Journal of Engineering, Electrical and Informatics
Untung Surapati
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Design of a Web-Based Instagram Content Management System to Support Brand Awareness for SR12 Herbal Cosmetics Products Untung Surapati; Agus Tanti Rahayu; Tatinia Arda Rizqi Amalia; Lusi Noviani
International Journal of Information Engineering and Science Vol. 3 No. 1 (2026): February : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i3.83

Abstract

PT. SR12 Herbal Cosmetics is a company engaged in the field of herbal and skin care. Founded in 2015 by Toni Firmansyah, S. Farm., Apt. and Asrianty Salam, S. Farm. This company has a vision to provide benefits to many people through the herbal and skin care products they produce. SR12 Herbal Cosmetics products are formulated based on research from certified scientists, and have been tested at the Sucofindo Laboratory, are free of mercury and hydroquinone, and have been registered with the Indonesian Food and Drug Supervisory Agency (BPOM RI). SR12 Herbal Cosmetics has several factories in West Java Province and has an extensive distribution network with hundreds of distributors and tens of thousands of partners throughout Indonesia. The goal to be achieved is to produce a management information system model including a management information system for PT SR12 Herbal Cosmetics. The research object chosen is a company in the field of cosmetics and skin care which has its head office in Gunung Sindur, West Java. This selection aims to form a management information system design model that is able to produce relevant and timely information for planning, controlling, decision making and evaluating the performance of activities. For the Web-Based Instagram Content Management Information System Design project to Support SR12 Herbal Cosmetics' Brand Awareness, I used Agile (Scrum) due to the dynamic nature of digital marketing and potential changes to the Instagram API or business needs. This allowed SR12 to get core functionality faster and provide iterative feedback, ensuring the system built was truly relevant to their brand awareness needs.
Implementation of the Naive Bayes Algorithm and Support Vector Machine for Public Sentiment Analysis towards the Ratification of the Job Creation Bill on Twitter Untung Surapati; Sopan Adrianto; Erno Sumantri; Melinius Nopianto
Journal of Engineering, Electrical and Informatics Vol. 2 No. 1 (2022): Februari : Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i1.202

Abstract

The test design of the Public Sentiment Analysis on the Ratification of the Job Creation Bill with the RapidMiner Studio application. The initial stage is to collect data in the form of tweets of Twitter users and then put it into a CSV file, the data obtained will be divided into training data and test data. Furthermore, the training data will be labeled consisting of 2 types of labels, namely Positive and Negative labels, then the data will be cleaned from unneeded words such as Mention or Hastag, then the data will go through several stages in the Preprocessing stage to convert raw data into data that is ready to be processed. Furthermore, each word will be weighted with the TF-IDF method. The final result of the comparison with these two test methods, namely the prediction of Public Sentiment Towards the Issue of Determining the Job Creation Bill based on data obtained from Twitter and implemented by the SVM (Support Vector Machine) method, showed an accuracy value of 96.52%. Of the 605 test data, 492 data were predicted as Negative Sentiment and 112 data as Positive Sentiment and the Naive Bayes Method showed an accuracy value of 49.67%. Of the 605 test data, 492 data were predicted as Negative Sentiment and 112 data as Positive Sentiment.
Classification of Favorite Book Borrowing Data at the STIKOM CKI Library Using the Decision Tree Algorithm Yuma Akbar; Untung Surapati; Sutisna Sutisna; Yansen Yansen
Journal of Engineering, Electrical and Informatics Vol. 2 No. 1 (2022): Februari : Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i1.3663

Abstract

The library on the STIKOM CKI campus as a means of providing information and has a complete collection of learning media books, but the data processing system for borrowing and returning favorite books in the library is currently still manual, that is, all data collection processes are written on book cards, although it is quite good but the process is rather slow and requires quite a long time because in the process of searching the data must be checked per page one by one so that the data processing is less effective and efficient. To overcome this, it is necessary to develop an application using the decision tree algorithm method which can make it easier to collect borrowing data and return favorite books that are more effective and efficient and display integrated output of student reports that have not returned so that data processing is more accurate and can speed up officer performance. library. Submitting a favorite book lending classification application can make it easier to access loans and returns anywhere and anytime. So that data processing is more accurate and can speed up librarian performance.
Co-Authors Agus Tanti Rahayu Akbar, Yuma Erno Sumantri Lusi Noviani Melinius Nopianto SOPAN ADRIANTO Sutisna Sutisna Tatinia Arda Rizqi Amalia Yansen Yansen