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All Journal Jurnal Informatika Jurnal Ilmiah KOMPUTASI Jurnal Pengabdian UntukMu NegeRI Journal of Information Technology and Computer Science Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini Journal of Information Technology and Computer Science (JOINTECS) Teknika: Engineering and Sains Journal Jurnal Sains dan Informatika Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOISIE (Journal Of Information Systems And Informatics Engineering) JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Jurnal Pengabdian Masyarakat IPTEKS Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Tekinkom (Teknik Informasi dan Komputer) Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Academia Open Indonesian Journal of Cultural and Community Development Indonesian Journal of Law and Economics Review Jurnal Penelitian Sekolah Tinggi Ilmu Kesehatan Nahdlatul Ulama Tuban Jurnal Teknik Informatika (JUTIF) Community Empowerment JPM: JURNAL PENGABDIAN MASYARAKAT Proceedings Series on Physical & Formal Sciences PELS (Procedia of Engineering and Life Science) Procedia of Social Sciences and Humanities Jurnal Algoritma Indonesian Journal of Islamic Studies Publikasi Pengabdian Masyarakat Komputer dan Teknologi (PUNDIMASKOT) JOINCS (Journal of Informatics, Network, and Computer Science) SAGA: Journal of Technology and Information Systems Jurnal Penelitian Innovative Technologica: Methodical Research Journal PEDAMAS (Pengabdian Kepada Masyarakat) SAINTEK Physical Sciences, Life Science and Engineering Indonesian Journal of Applied Technology Journal of Internet and Software Engineering Prosiding Seminar Nasional Unimus Advances in Cancer Science Journal of Electrical Engineering Manajemen Pelayanan Kesehatan IJHCS Smatika Jurnal : STIKI Informatika Jurnal
Uce Indahyanti
Universitas Muhammadiyah Sidoarjo
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Prediction Model of Voter Participation Using Naïve Bayes and Village Development Indicators: Model Prediksi Partisipasi Pemilih Menggunakan Naïve Bayes dan Indikator Pembangunan Desa Abidin, Husnul; Fitrani, Arif Senja; Setiawan, Hamzah; Indahyanti, Uce
Indonesian Journal of Cultural and Community Development Vol. 16 No. 2 (2025): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijccd.v16i2.1243

Abstract

Background: Electoral participation reflects the quality of democracy, particularly in rural communities with diverse socioeconomic structures. Specific Background: In Sidoarjo Regency, disparities in participation levels among villages suggest that local development factors play a crucial role. Knowledge Gap: Previous models only used demographic attributes without integrating the multidimensional Village Development Index (IDM) indicators. Aims: This study aims to construct a predictive model of voter participation using the Naïve Bayes classification algorithm based on IDM data. Results: By applying preprocessing, feature selection, and probabilistic classification to 48 attributes of IDM, the model achieved 78.65% accuracy, 79% precision, 76% recall, and 77% F1-score, revealing that education, health, and accessibility variables are key predictors. Novelty: Unlike prior research, this work combines social, economic, and ecological IDM dimensions with an open-source Python-based approach for transparent model validation. Implications: The findings demonstrate the feasibility of data-driven governance tools for mapping electoral participation and can support strategic planning to improve civic engagement in rural Indonesia.Highlights:• Uses IDM indicators to predict election participation• Naïve Bayes model achieves 78.65% accuracy• Supports data-driven democratic planning
Decision Tree Analysis for Predicting Voter Participation Using IDM Data: Analisis Pohon Keputusan untuk Memprediksi Partisipasi Pemilih Menggunakan Data IDM Yuwanto, Mahmud Adi; Fitrani, Arif Senja; Dijaya, Rohman; Indahyanti, Uce
Indonesian Journal of Cultural and Community Development Vol. 16 No. 2 (2025): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijccd.v16i2.1255

Abstract

General Background: Voter participation serves as a core indicator of democratic quality and civic awareness. Specific Background: In East Java’s Mataraman region, significant disparities in electoral participation highlight socioeconomic influences measurable through the Village Development Index (IDM). Knowledge Gap: No prior research integrates IDM-based indicators with machine learning methods for voter behavior prediction. Aims: This study develops a classification model using C4.5, Naïve Bayes, and SVM algorithms to predict voter participation based on IDM attributes. Results: The Decision Tree C4.5 algorithm achieved the highest accuracy (80.87%) and F1-score (0.88) compared to Naïve Bayes and SVM, identifying education and healthcare access as primary determinants of high participation. Novelty: The integration of IDM and C4.5 classification introduces a novel framework for data-driven political participation analysis. Implications: The model can assist policymakers and electoral bodies in targeting civic engagement initiatives within underrepresented regions. Highlights: C4.5 algorithm effectively predicts voter engagement. Education and health access influence participation. Data-driven policy enhances democratic quality.
Implementasi Aplikasi Perpustakaan Mini Mandiri At-Taqwa Urangagung Sidoarjo Rahmawati, Yunianita; Findawati, Yulian; Indahyanti, Uce; Fitroni, Arif Senja
Jurnal Pengabdian UntukMu NegeRI Vol. 7 No. 1 (2023): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v7i1.4830

Abstract

Perpustakaan Mini Mandiri At-Taqwa didirikan untuk memberikan bahan bacaan pada warga perumahan Bhayangkara pada khususnya dan warga sekitar perumahan pada umumnya. Pendataan buku dan anggota dilakukan secara manual sehingga dibutuhkan suatu aplikasi pendataan buku secara otomatis sehingga dibuatlah aplikasi Perpustakaan Mini Mandiri At-Taqwa. Fitur aplikasi ini diantaranya Input Kategori Buku, Input Data Buku, Input Data Anggota, Input Data Petugas, Cari Data Buku, dan Laporan Buku. Aplikasi ini dapat membantu pencatatan dan pencarian data buku, anggota, dan petugas secara otomatis.
TOPIC MODELING IN COVID-19 VACCINATION REFUSAL CASES USING LATENT DIRICHLET ALLOCATION AND LATENT SEMANTIC ANALYSIS Malihatin S, Ulfah; Findawati, Yulian; Indahyanti, Uce
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.951

Abstract

COVID -19 vaccination is a program provided by the Indonesian government to minimize the spread of the virus. The COVID-19 vaccination program in Indonesia goes hand in hand with issues that are circulating, causing controversy and rejection of vaccination on social media, especially Twitter. There are many factors that influence vaccine rejection on Twitter, to summarize frequently discussed topics and find out hidden topics, this study uses the Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA) methods from 1797 Twitter scrapping data. Both models require a set of words that have been converted into a matrix, so before conducting LDA topic modeling, the dataset will undergo a bag of word (BOW) calculation. Meanwhile, in LSA topic modeling, the existing dataset will undergo word weighting of frequently occurring words using Term Frequency - Inverse Document Frequency (TF-IDF). This study was conducted to find and summarize hidden information in the form of frequently discussed topics, thus understanding public opinions related to the COVID -19 vaccination refusal case. LDA and LSA methods will display topics based on the probability and mathematical calculations of word occurrences in each topic in the document. The topics that appear will be further analyzed through coherence score by applying a limit of 20 topics to display the best value. Further modeling experiments are carried out to display topics through LDA and LSA models, this study takes 6 topics with the highest coherence values including the right of individuals to choose whether to be vaccinated or not (0.484607), the Ribka Tjiptaning controversy (0.473368), rejection of the COVID-19 vaccine by groups represented by public figures (0.463631), punishment for non-compliance in the form of fines (0.324924), and halal certification (0.312521).
Sarcasm Detection in News Headline Dataset with Ensemble Deep Learning Method: Deteksi Sarkasme Pada Dataset News Headline Dengan Metode Ensemble Deep Learning Mochamad Alfan Rosid; Siti Nur Haliza; Yulian Findawati; Uce Indahyanti
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 6 No. 2 (2023): November
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v6i2.1628

Abstract

Sarcasm, a prevalent linguistic device, is frequently used in public discourse, often causing offence and distress to the listener. The complexity inherent in detecting sarcasm is a significant and ongoing challenge in the field of sentiment analysis research. The widespread use of this phenomenon in diverse conversational contexts further complicates its identification in data sets full of human interactions. Deficiencies in methodologies for distinguishing such statements adversely affect the performance of sentiment analysis, especially in distinguishing negative, positive or neutral sentiments. Inaccuracies in sarcasm detection can affect the classification results of sentiment analysis. Therefore, sentiment analysis seeks to categorise sarcastic sentences that, despite appearing positive, actually contain negative meanings. This research aims to build a deep learning ensemble stack model. The basic deep learning methods used are Bidirectional Gated Recurrent Unit (BiGRU) and Convolutional Neural Network (CNN). LightGBM is used to perform stack ensemble of deep learning methods. The dataset used comes from the Kaggle website and consists of English headlines. The findings show that the stack ensemble method outperforms BiGRU and CNN, evidenced by an accuracy rate of 91.2% and an F1 score of 90.2%. Therefore, from the above discussion, it can be concluded that the LightGBM method emerges as the optimal solution for sarcasm detection
Analysis of the Predicted Number of HIV/AIDS Spreads in Sidoarjo Regency using Multiple Linear Regression Method Azizah, Risma Nur; Indahyanti, Uce
Advances in Cancer Science Vol. 1 No. 1 (2024): April
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/acsc.v1i1.3

Abstract

The Office of Communication and Information of East Java Province, which includes Sidoarjo Regency, is one of the data sources used to determine the fourth-highest number of HIV/AIDS cases in Indonesia. The aim of this study is to forecast an annual increase in the number of HIV/AIDS patients in Sidoarjo Regency. The Sidoarjo District Health Office is the private source of data used in this study. The information utilized spans the years 2020–2022, and it contains attributes with projected results of positive HIV/AIDS patients. The estimated number for 2023 is 795,667; for 2024, it is 934,167; and for 2025, it is 1072,667. Because there are numerous attribute data sets obtained, quick miner processes the data using multiple linear regression as the chosen approach. The root mean squared error (RSME) validation test yielded a performance score of 0.816 for the multiple linear regression model, indicating that a smaller prediction result indicates greater validity.
Web-Based Student Violation Management with Real-Time Notifications Transforms School Discipline: Manajemen Pelanggaran Siswa Berbasis Web dengan Notifikasi Waktu Nyata Mengubah Disiplin Sekolah Krisfianto, Moh Ifan; Indahyanti, Uce
Indonesian Journal of Law and Economics Review Vol. 19 No. 3 (2024): August
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijler.v19i3.1196

Abstract

General background: The digital age has significantly impacted education, posing challenges in managing student behavior and addressing rule violations, necessitating more efficient solutions. Specific background: Educational institutions are exploring the use of web-based systems with real-time notifications to improve efficiency in recording and communicating student violations. Knowledge gap: Despite the advancements in technology, many schools have yet to fully adopt integrated digital systems for managing student violations, and the effectiveness of real-time notification systems has not been fully explored. Aims: This study aims to design and develop a web-based application for managing student violations, integrated with WhatsApp notifications, to improve efficiency, accuracy, and communication between schools and parents. Results: Using the Extreme Programming (XP) methodology, the system was developed iteratively, allowing for rapid adjustments based on user feedback. The system successfully reduced errors in violation recording and accelerated communication with parents, facilitating faster responses to student misconduct. Novelty: The web-based violation management system incorporates real-time WhatsApp notifications, offering a more efficient and trustworthy communication channel between schools and parents. Implications: The system enhances both the management of student behavior and the engagement of parents, and it serves as an innovative model for other educational institutions to adopt for more effective administration and improved educational outcomes. Highlights: Efficiency: Reduces errors in managing student violations. Communication: Enhances parent-school connection via real-time WhatsApp notifications. Adaptability: XP methodology supports rapid adjustments and iterative development. Keywords: Web-based system, student violations, real-time notifications, WhatsApp integration, Extreme Programming
OPTIMALISASI LAHAN SEMPIT UNTUK BUDIDAYA TANAMAN OBAT KELUARGA DAN PEMBUATAN KOMPOS DI DESA BLIGO KECAMATAN CANDI KAPUBATEN SIDOARJO Rahmawati, Yunianita; Farihah, Anis; Indahyanti, Uce
PEDAMAS (PENGABDIAN KEPADA MASYARAKAT) Vol. 3 No. 05 (2025): SEPTEMBER 2025
Publisher : MEDIA INOVASI PENDIDIKAN DAN PUBLIKASI

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

Abstract

Pengabdian masyarakat ini mengkaji pemanfaatan lahan sempit untuk budidaya Tanaman Obat Keluarga (TOGA) di Desa Bligo, Kecamatan Candi, Kabupaten Sidoarjo, yang memiliki keterbatasan lahan akibat tingginya kepadatan penduduk dan pembangunan infrastruktur. pengabdian masyarakat bertujuan memberikan solusi inovatif dengan memanfaatkan ruang sempit secara efektif melalui penanaman TOGA. Metode yang digunakan mencakup sosialisasi kepada masyarakat, pembuatan rak tanaman, tong komposer untuk pengolahan sampah organik, dan penanaman bibit TOGA dengan teknik vertikultur dan polibag. Hasil pengabdian masyarakat menunjukkan bahwa pemanfaatan lahan sempit ini tidak hanya meningkatkan kesadaran masyarakat mengenai pentingnya TOGA tetapi juga memberikan manfaat ekonomi dan kesehatan. Penanaman TOGA pada rak-rak di depan rumah warga mampu mengoptimalkan lahan terbatas sekaligus memperindah lingkungan. Evaluasi kegiatan menunjukkan keberhasilan dalam penerapan metode ini, dengan kendala yang dapat teratasi dan peningkatan partisipasi warga melalui pemberian penghargaan. Studi ini menyimpulkan bahwa pemanfaatan lahan sempit untuk TOGA memberikan dampak positif bagi masyarakat, terutama dalam aspek kesehatan dan lingkungan.
Pengembangan Game 2D “Cat Collection Coin” Berbasis Single Player Menggunakan Metode Finite State Machine untuk Manajemen State Karakter Awalludin, Krisna; Busono, Suhendro; Indahyanti, Uce; Rahmawati, Yunianita
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.22-2.2424

Abstract

Penelitian ini bertujuan untuk mengembangkan game 2D berjudul "Cat Collection Coin" berbasis single player dengan mengimplementasikan metode Finite State Machine (FSM) untuk mengelola perilaku karakter secara sistematis. FSM memungkinkan setiap karakter dalam game memiliki transisi keadaan yang terstruktur, seperti diam, berjalan, melompat, dan menyerang, berdasarkan input pemain dan kondisi permainan. Game ini dikembangkan menggunakan Godot Engine, yang menyediakan dukungan optimal untuk pengembangan game 2D. Penelitian ini juga membahas bagaimana FSM diterapkan pada berbagai level permainan untuk menciptakan alur permainan yang responsif dan menantang. Hasil perancangan menunjukkan bahwa penggunaan FSM mampu meningkatkan modularitas logika permainan serta memberikan pengalaman bermain yang lebih dinamis. Implementasi ini menjadi solusi efektif dalam mengelola kompleksitas perilaku karakter pada game 2D berbasis single player.
Pemberdayaan Kelompok UMKM Terdampak Covid Melalui Pendampingan Ekonomi Kreatif Berbasis Teknologi Azizah, Nuril Lutvi; Indahyanti, Uce; Latifah, Fitri Nur; Sumadyo, Sasmito Bagus
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 5 No 2 (2021): Volume 5 Nomor 2 Tahun 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v5i2.15374

Abstract

Community dedication is carried out with the aim of increasing the sales turn over of cloth mask at the UMKM Tanjung which is related in the sales of goods or shops. The method used in this services activity is through partial assistance and training. Partial assistance is carried out by providing guidence and training to improve skills in making mask innovations into painting maks. Creative economy assistance is carried out by making technology-based painting masks. Masks are designed using the basic graphic design sketch application on masks, so mask sketches can be custom ordered according to the wishes of potential buyers. Painting mask can also be a differentiator from other masks that are sold in the market, thus masks have different characteristics from other masks sold in the market. The result obtained are an incrase in the selling value of painting mask and and an increase in skills in the group of UMKM Tanjung. It can be concluded that the mentoring and training activities receive positive responses from the group based on the result.
Co-Authors Abidin, Husnul Ade Eviyanti Ade Eviyanti Aditya, M. Fahrul Rizki Afidah, Dewi Nur Aisha Hanif Alfinda Ayu Hadikasari Anis Farihah, Anis Ariansyah, Achmad Arif Senja Fitrani Arif Senja Fitroni Aris Hendra Prayoga Astutik, Ika Ratna Indra Awalludin, Krisna Azizah, Risma Nur Azmuri Wahyu Azinar Berlian Putri Pertiwi Busono, Suhendro Cecep Kusmana Cholifah, Cholifah Cholifah, Cholifah Cindy Cahyaning Astuti Dafit Setiawan Jaya Damasta, Ifanda Reza Deby Kurniawan Armananda Dewi Komala Sari Edi Widodo, Edi Eko Agus Suprayitno Eriyanto, Sandi Eko Fahmawati, Zaki Nur Fahmi, M. Yusril Fery Febbyanto Firdausi Usqi Salsabilah Firmansah, Noval Fitri Nur Latifah Fitroni, Arif Senja Hadikasari, Alfinda Ayu Hamzah Setiawan Ika Ratna Indra Astutik Irwan Alnarus Kautsar Khubro, Jamaluddin Jumadil Krisfianto, Moh Ifan Krisnaningsih, Diah Kurniawan, Wildan Lely Ika Mariyati Lily Puspa Dewi Maghfiroh, Alfiah Malihatin S, Ulfah Mauliana, Metatia Intan Metatia Intan Mauliana Moch. Aji Bagus Firmansyah Mochamad Alfan Rosid Mochammad Donni Kurniawan Muhammad Arsyad Dhani Muhammad Syamsuddin Nisak , Umi Khoirun Novia Ariyanti Nuril Lutvi Azizah Pertiwi, Berlian Putri Prayugah, Indra Putra, Rolando Jordan Permana Rafiiqa, Tasya Ramdansyah, Adiffanani Ratih Puspitasari Rohman Dijaya Rolando Jordan Permana Putra Setiawan, Hamzah Siti Nur Haliza Suhendro Busono Suhendro Busono Sukarjadi Sukarjadi Sumadyo, Sasmito Bagus Sumarno Sumarno Suryani, Siti Dwi Suseno Ardiansyah Syahrul Ibnu Rafi Tutut Anjarsari Umi Khoirun Nisak Usabili, Syaikhina Vevy Liansari via nabila banda Wahyu Santoso Yahya Anugerah Dwi Khurrota A'yunan Yoyok Supriyono Yulian Findawati Yulius Hari Yunianita Rahmawati Yunianita Rahmawati, Yunianita Yuwanto, Mahmud Adi Zaki Nur Fahmawati Zamorano, Ifan