Article Per Year (5 Year)
p-Index From 2021 - 2026
2.461
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Aisyah Journal of Informatics and Electrical Engineering METABASA Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Journal of Students‘ Research in Computer Science (JSRCS) Journal of Dinda : Data Science, Information Technology, and Data Analytics Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan East Asian Journal of Multidisciplinary Research (EAJMR) Knowbase : International Journal of Knowledge in Database Hortatori : Jurnal Pendidikan Bahasa dan Sastra Indonesia Jurnal Satya Informatika Educational Journal of Bhayangkara (EDUKARYA)
Siti Setiawati
Universitas Bhayangkara Jakarta Raya
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 17 Documents
Search

 1   2 
Penggunaan Deiksis dalam Novel Arah Langkah Karya Fiersa Besari Siti Setiawati; Dimas Pratama Rustianto; Asep Muhyidin
Hortatori : Jurnal Pendidikan Bahasa dan Sastra Indonesia Vol 7, No 1 (2023): Hortatori: Jurnal Pendidikan Bahasa dan Sastra Indonesia
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jh.v7i1.1797

Abstract

This research is a study of the use of deixis forms. This study aims to: (1) Describe the use of persona, space, and time deixis in the novel Direction Steps by Fiersa Besari. (2) Describe the relevance of the results of research data analysis to learning the Indonesian language and literature at the senior high school level. This study used a qualitative approach with a descriptive-analytic research design. The data sources in this study are words that contain deixis in the speech between characters in the novel Direction Steps by Fiersa Besari. This study's data collection techniques were tapping, speaking, and note-taking techniques. The results of this study found three forms of deixis, namely persona deixis, spatial deixis, and time deixis, with a total of 85 data findings. The 11 categories of derivatives are as follows: (1) 26 first persona singular, (2) 5 first persona plural, (3) 10-second persona singular, (4) 2-second persona plural, (5) 4 persona data third singular, (6) 3 plural third-person data, (7) 13 demonstrative data, (8) 12 locative data, (9) 4 past data, (10) 3 present data, and (11) 3 future data will comeKeywords: Deixis, qualitative, learning, speech.
APLIKASI PEMANTAU KESEHATAN KUCING BERBASIS ANDROID MENGGUNAKAN METODE FUZZY TSUKAMOTO M. Hadi Prayitno; Rakha Afif Arifin; Siti Setiawati
JURNAL SATYA INFORMATIKA Vol. 8 No. 02 (2023): SATYA INFORMATIKA
Publisher : FAKULTAS TEKNIK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59134/jsk.v8i2.536

Abstract

Kucing merupakan hewan peliharaan yang banyak dipelihara oleh masyarakat di Indonesia, namun banyak masyarakat yang masih menyepelekan dan mengabaikan kesehatan kucing. Kesehatan kucing maupun hewan peliharaan lain merupakan hak dari hewan peliharaan tersebut, dan merupakan kewajiban sebagai pemilik hewan peliharaan tersebut untuk memberikan kehidupan yang layak bagi hewan peliharaan yang mereka miliki. Dikarenakan penggunaan smartphone di Indonesia yang meningkat secara pesat, peneliti ini mengusulkan sebuah aplikasi untuk memantau kesehatan kucing menggunakan sistem operasi android yang dapat memudahkan pemantauan kesehatan kucing secara mandiri. Metode Fuzzy Tsukamoto dan metode pengembangan design thinking akan diterapkan dalam aplikasi ini. Metode Fuzzy Tsukamoto digunakan untuk melakukan perhitungan tingkat kesehatan nutrisi kucing, tingkat kesehatan mental kucing dan untuk mendiagnosis penyakit kucing. Metode pengembangan design thinking digunakan untuk melakukan pengembangan aplikasi ini. Hasil dari penelitian ini dapat membantu pemilik kucing untuk memeriksakan tingkat gizi pada kucing untuk menjaga gizi kucing tetap ideal, memudahkan pemilik kucing dalam mendiagnosis penyakit kucing. Hasil perhitungan tingkat terjangkit penyakit, yang dihasilkan berdasarkan data yang ada memberikan hasil berupa toxoplasmosis sebesar 43%, upper respiratory infection sebesar 20.8333%, feline panleukopenia virus sebesar 43.75%, ringworm sebesar 62.5% dan scabies sebesar 84.375%.
Sentiment Analysis of Application Reviews using the K-Nearest Neighbors (KNN) Algorithm Damar Wijati; Prima Dina Atika; Siti Setiawati; Rasim Rasim
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 1 (2024): March 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i1.9490

Abstract

Product reviews play a crucial role in evaluating user satisfaction and overall performance. Vidio, one of the over-the-top (OTT) media platforms, offers a wide range of entertainment content, including movies, TV shows, sports events, music shows, lifestyle programs, and more, accessible through its application. Users have the opportunity to provide reviews and feedback on their experience with the Vidio application. Therefore, this research was conducted to analyze user sentiment towards the Vidio application on the Google Play Store platform using the K-Nearest Neighbors (KNN) method. Data for sentiment analysis were randomly selected from the Vidio application based on the most relevant reviews. A total of 3,000 data were analyzed, with 2,238 data in the negative class, 508 data in the neutral class, and 254 data in the positive class. This research used the K-Nearest Neighbors (KNN) method for classifying reviews based on negative, neutral, and positive classes, and the Multiclass Confusion Matrix for model evaluation. With a data split of 70% for training data 30% for testing data, and several n_neighbors of 10 data, the results in an accuracy of 81.6%, precision of 79%, recall of 81.6%, and F1-Score of 77%.
Metode Naïve Bayes dan Support Vector Machine untuk Mengolah Sentimen Ulasan dan Komentar di Platform Digital Herlawati; Dwi Budi Srisulistiowati; Syafira Cessa Agustin; Prilia Hashifah Syafina; Nida Rachmatin; Siti Setiawati
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/dby15h32

Abstract

This study analyzes sentiment from user Reviews of the FLO app, Taman Mini Indonesia Indah (TMII), and public comments on infidelity cases on Instagram, using Naïve Bayes and Support Vector Machine (SVM) algorithms. FLO, an app that helps users track reproductive health, was analyzed based on 1,393 Reviews on Google Play Store. Of these, 796 Reviews expressed positive sentiment, while 597 were negative. Although both Naïve Bayes and SVM achieved an accuracy of 74%, SVM performed better in recall (74%) and precision (71%). For TMII Reviews, the analysis involved 1,616 Google Reviews, with 1,263 showing negative sentiment, indicating complaints about facilities and services, and 353 expressing positive sentiment. SVM outperformed Naïve Bayes, achieving an accuracy of 85% and an f1-score of 87%, compared to Naïve Bayes’ 82% accuracy and 83% f1-score. Additionally, the analysis of 1,200 public comments on Instagram accounts @lambe_turah and @awreceh.id revealed 918 negative comments and 282 positive ones. SVM once again demonstrated superior performance with an accuracy of 91%, precision of 87%, recall of 96%, and an f1-score of 92%, surpassing Naïve Bayes, which achieved an accuracy of 86%. These findings confirm that SVM is more effective for sentiment classification across various digital Platforms, including social issues and service evaluations. The results can be applied to develop public opinion analysis systems that support strategic decision-making and enhance service quality based on user feedback.
Sistem Informasi Navigasi Wisata Kota Jakarta untuk Menentukan Rute Tercepat Menggunakan Algoritma Dijkstra Berbasis Web Muhammad Rizki Syaumi; Achmad Noeman; Siti Setiawati; Prio Kustanto
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/c9by2m49

Abstract

This study aims to design a web-based tourism navigation information system using Dijkstra’s algorithm to determine the fastest rout in Jakarta City. The proposed navigation system assists tourist in planning their trips more efficiently by providing real-time information on the fastest routes, travel distances, and estimated traviel times. By implementing Dijkstra’s algorithm, the system calculates the optimal route based on the starting location from the user’s device and destination data stored in the database. This research employs the waterfall system development method, which inludes the stages of analysis, design, implementation, and testing. The testing results demonstrate that the system accurately provides the fastest routes, enhancing convenience and travel efficiency for tourist.
MEMANFAATKAN PLATFORM MEDIA SOSIAL YOUTUBE UNTUK TUJUAN PELATIHAN GUNA MENINGKATKAN PENGETAHUAN DAN PEMAHAMAN ANAK SEKOLAH DASAR TENTANG HUKUM KEAMANAN SIBER Siti Setiawati; Adi Muhajirin; Tri Ginanjar Laksana
Educational Journal of Bhayangkara Vol. 6 No. 1 (2026): Juli 2026
Publisher : Program Studi Pendidikan Guru Sekolah Dasar Fakultas Ilmu Pendidikan Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/28vyng29

Abstract

Di era digital saat ini, baik individu maupun organisasi telah memberikan penekanan signifikan pada prioritas keamanan siber. Meningkatnya ancaman kejahatan siber menuntut pemahaman kita tentang pentingnya pelatihan dan pengetahuan keamanan siber. Media sosial adalah teknologi yang dapat digunakan untuk mencapai tujuan ini. Studi ini menggunakan metodologi kualitatif untuk meneliti teori sosial dari para insinyur komunikasi. Data dikumpulkan melalui penggunaan wawancara semi-terstruktur dan tinjauan pustaka. Analisis mencakup interpretasi data kualitatif dan kategorisasi. Studi ini dilakukan dengan kepatuhan ketat terhadap prinsip-prinsip etika, yang meliputi memperoleh izin dari responden, menjaga privasi dan kerahasiaan mereka, dan mengurangi kemungkinan bias dari para peneliti. Studi ini bertujuan untuk meneliti keuntungan menggunakan YouTube sebagai platform media sosial untuk meningkatkan kesadaran keamanan siber. Studi ini juga ingin mengeksplorasi manfaat menggunakan YouTube dan memberikan teknik untuk mengembangkan program pelatihan melalui YouTube. Melalui penggunaan platform media sosial, khususnya YouTube, kita memiliki kemampuan untuk menyediakan materi yang menarik dan relevan, mengadvokasi kesadaran keamanan melalui inisiatif media sosial, dan terlibat dalam kemitraan dengan tokoh-tokoh berpengaruh dan profesional di bidang keamanan siber. Untuk menjamin keberhasilan dan efektivitas program pelatihan dan kesadaran keamanan siber, sangat penting untuk mematuhi protokol yang telah ditetapkan dan memasukkan acara keamanan siber ke dalam platform media sosial. Manfaatkan media sosial untuk meningkatkan pengaruhnya dalam mempromosikan kesadaran keamanan siber.
Implementation of Genetic Algorithm for Automatic Course Scheduling Optimization Rakhmi Khalida; Situmorang; Dwi; Siti Setiawati
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10260

Abstract

Course scheduling in vocational high schools (SMK) constitutes a complex combinatorial optimization problem involving multiple hard and soft constraints related to teacher availability, class allocation, and time-slot distribution. Although Genetic Algorithms (GA) have been extensively applied in educational timetabling, existing studies largely emphasize standalone optimization or desktop-based solutions, with limited analytical evaluation of refinement strategies and system-level applicability. This study addresses this gap by empirically evaluating a hybrid GA–Local Search (LS) approach embedded within a web-based scheduling framework. GA is utilized as a global search mechanism to generate feasible schedules that satisfy all hard constraints, while LS is applied as a post-optimization phase to improve solution quality by reducing soft constraint violations. Experiments were conducted using real scheduling data from SMK Yadika 13 Bekasi, involving 3 subjects, 3 teachers, 4 classes, and 12 time slots within a single-day scenario. Although limited in scale, this configuration was deliberately selected to enable transparent analysis of the optimization dynamics and refinement impact of the proposed hybrid approach. The results show that the pure GA produces five soft constraint violations, mainly due to suboptimal placement of cognitively demanding subjects and uneven subject distribution. After applying LS, violations were reduced to two cases, with the fitness value improving from 0.873 to 0.946 and only a marginal increase in computation time (5–7 seconds). These findings demonstrate that local refinement significantly enhances schedule quality beyond conflict-free feasibility. This study contributes scientifically by providing an empirical assessment of GA–LS hybridization for soft-constraint optimization and by establishing a scalable web-based framework that supports future extensions to full-week scheduling and adaptive academic systems
Co-Authors Achmad Noeman Adi Muhajirin Asep Muhyidin Bungaran Saing, Bungaran Damar Wijati Dimas Pratama Rustianto Dwi Dwi Budi Srisulistiowati Fata Nidaul Khasanah Herlawati Herlawati Ismaniah Ismaniah Khairunnisa Fadhilla Ramdhania Kustanto , Prio Lisa Adhani lisa adhani M. Hadi Prayitno Mayadi Mayadi Muhammad Rizki Syaumi Nida Rachmatin Nurjamilah, Ai Siti Priatna , Wowon Prilia Hashifah Syafina Prima Dina Atika R Wisnu Prio Pamungkas Rakha Afif Arifin Rakhmi Khalida Rasim Rasim Rizki Alamsyah Situmorang Syafira Cessa Agustin Tb Ai Munandar Tri Ginanjar Laksana Widodo, Hernowo