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All Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknik Informatika (JUTIF) Jurnal Algoritma
Irawan, Carti
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education

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Sentiment Analysis of Social Media Platform Reviews Using the Naïve Bayes Classifier Algorithm Saepudin, Sudin; Widiastuti, Selviani; Irawan, Carti
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 2 (2023): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i2.1650

Abstract

The Covid-19 pandemic has caused significant changes in people's lifestyles which are further strengthened by the rapid development of technology. This has resulted in increased use of the internet and accelerated dissemination of information through social media platforms. Not only for self-expression, social media can also be a means of communication, information, education, and even used as a marketing tool. Several social media platforms have recently been popular and widely used, the number of users is increasing from year to year, and each user can provide a rating review of the application. To find out public opinion on social media platforms, sentiment analysis will be carried out on several social media platform applications on the Google Play Store, namely Twitter, Instagram and Tiktok which will later be used as material for evaluating these applications. In this study, the dataset was taken based on ratings from user reviews on the Google Play Store using the NBC (Naïve Bayes Classifier) method with the Python programming language. Based on testing of 1000 comment review data from each application, it was found that the majority gave positive sentiment (Twitter 57.2%, Instagram 74.1%, Tiktok 83.9%), and negative sentiment (Twitter 42.8%, Instagram 25.9%, Tiktok 16.1%) with an accuracy rate of 85.6% for the Twitter application, 83.6% for the Instagram application, and 84.8% for the Tiktok application.
Sentiment Analysis of Social Media Platform Reviews Using the Naïve Bayes Classifier Algorithm Saepudin, Sudin; Widiastuti, Selviani; Irawan, Carti
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 12 No. 2 (2023): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i2.1650

Abstract

The Covid-19 pandemic has caused significant changes in people's lifestyles which are further strengthened by the rapid development of technology. This has resulted in increased use of the internet and accelerated dissemination of information through social media platforms. Not only for self-expression, social media can also be a means of communication, information, education, and even used as a marketing tool. Several social media platforms have recently been popular and widely used, the number of users is increasing from year to year, and each user can provide a rating review of the application. To find out public opinion on social media platforms, sentiment analysis will be carried out on several social media platform applications on the Google Play Store, namely Twitter, Instagram and Tiktok which will later be used as material for evaluating these applications. In this study, the dataset was taken based on ratings from user reviews on the Google Play Store using the NBC (Naïve Bayes Classifier) method with the Python programming language. Based on testing of 1000 comment review data from each application, it was found that the majority gave positive sentiment (Twitter 57.2%, Instagram 74.1%, Tiktok 83.9%), and negative sentiment (Twitter 42.8%, Instagram 25.9%, Tiktok 16.1%) with an accuracy rate of 85.6% for the Twitter application, 83.6% for the Instagram application, and 84.8% for the Tiktok application.
IMPLEMENTATION OF THE K-MEANS CLUSTERING ALGORITHM IN ANALYZING PUBLIC SATISFACTION REGARDING PUBLIC SERVICES (STUDI CASE: BALAI PENGUJIAN STANDAR INSTRUMEN TANAMAN INDUSTRI DAN PENYEGAR) Alifah, Atika Juhaedah; Saepudin, Sudin; Irawan, Carti
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2125

Abstract

With the development of today's modern era, publik service is an important and very necessary thing because it is one of the benchmarks for seeing publik trust and satisfaction with the services provided by an agency. One of the agencies that carries out publi services is the Balai Pengujian Standar Instrumen Tanaman Industri dan Penyegar (BPSI TRI), a government agency under the Ministry of Agriculture. There are a lot of people who will receive services in 2023. Therefore, publik service officers find it difficult to determine publik satisfaction in order to optimize the services provided. To determine community satisfaction, data mining calculations were carried out using the K-Means clustering algorithm method with Community Satisfaction Index (IKM) data in 2023 using 3 (three) categories including unsatisfactory (C1), satisfactory (C2) and very satisfactory) and 2 attributes, namely the behavior of service officers (U7) as well as handling complaints, suggestions and input (U8) then carried out calculations using Microsoft Excel and got the results that C1 (unsatisfactory) 14 respondents, C2 (satisfactory) 39 respondents and C3 (very satisfactory) 98 respondents. Meanwhile, from the results of calculations using python testing, the results showed that C1 (unsatisfactory) was 9 respondents, C2 (satisfactory) was 39 respondents and C3 (very satisfactory) was 103 respondents.
Analisis Motivasi Kinerja Pegawai Kecamatan Cibitung Menggunakan Metode Analytical Hierarchy Process (AHP) Andrean, Okta Teza; Saepudin, Sudin; Irawan, Carti; Mupaat
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2429

Abstract

This study aims to analyze the factors that influence the performance motivation of Cibitung Subdistrict employees using the Analytical Hierarchy Process (AHP) method with a total of 22 subdistrict employee respondents. The three main criteria analyzed include work environment, rewards, and leadership. Data were obtained through a paired comparison questionnaire, which was then processed using the AHP method to determine the priority weight of each criterion. The results show that leadership is the dominant factor (0.666), followed by rewards (0.601) and work environment (0.534). The Consistency Ratio (CR) value of 0.00086 indicates that the respondents' assessments are consistent. These findings are expected to serve as a basis for policy-making to improve employee performance in the environment.
IMPLEMENTASI WEB SCRAPING DAN ETL UNTUK PEMBUATAN PETA INTERAKTIF SEBARAN DESTINASI WISATA GEOPARK CILETUH MENGGUNAKAN PYTHON Dinata, Fajar Sukarsa; Saepudin, Sudin; Irawan, Carti
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7548

Abstract

Ciletuh-Palabuhanratu Geopark has rich geological and cultural diversi-ty, but information related to its tourist destinations is still limited. The information available on the official website is scattered on various pages, so users have to open many pages to get complete data about each destination. This research aims to build an interactive map that integrates all tourist destination information in one platform. The web scraping method is used to collect data from the official Ciletuh Ge-opark website. The data obtained is then visualized in an interactive map using Folium, with features of colored markers, marker clusters, and informative popups. The results showed that web scraping can be used effectively to collect and present tourist information in an inte-grated manner. The resulting interactive map allows users to access des-tination information in a single view, making data search easier for tourists and stakeholders. This research contributes to the development of digital-based tourism information systems, improves data accessibil-ity, and supports sustainable ecotourism planning in Ciletuh Geopark.
Co-Authors Alifah, Atika Juhaedah Andrean, Okta Teza Dinata, Fajar Sukarsa Mupaat Saepudin, Sudin Widiastuti, Selviani