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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Ilmiah Sinus Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Ittishal Educational Research Journal JURNAL REKAYASA INFORMASI SWADHARMA (JRIS) Postulat : Jurnal Inovasi Pendidikan Matematika Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Pengabdian Masyarakat Teknologi dan Pendidikan (MANTAP) Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA) Jurnal Ilmu Komputer dan Teknik Informatika Indonesian Applied Research Computing and Informatics
Dwi Remawati
Universitas Tiga Serangkai
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Public Health Social Sciences Other

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Rancang Bangun Web Profil Sekolah SD IT Al-Hikam Berbasis Wordpress Sebagai Bentuk Media Promosi Wijayanto, Hendro; Remawati, Dwi; Fitriani, Putri Asiska Nur
Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 6, No 2 (2023): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v6i2.4148

Abstract

Potensi sumber daya teknologi kian hari kian memberikan manfaat lebih bagi pengguna. Salah satunya teknologi website. Keberadaan website sangat penting untuk menunjang tersampaikannya maksud dan tujuan lewat media informasi yang dapat diakses oleh masyarakat luas. Selain itu website juga dapat digunakan untuk media promosi suatu produk tertentu. Sekolah Dasar IT Al-Hikam merupakan salah satu sekolah dasar di Kecamatan Banyudono Kabupaten Boyolali yang belum memiliki media website. Media website ini dirasa penting untuk penyampaian informasi kegiatan sekolah pada masyarakat. Dan yang paling utama adalah sebagai media pengenalan sekolah atau promosi ke masyarakat. Metode yang digunakan untuk perancangan dan pembuatan website adalah pengumpulan data, perancangan konsep, pembuatan website, implementasi, serta evaluasi. Diperoleh hasil berupa website sekolah yang dapat diakses oleh masyarakat di alamat  https://sditalhikam.wordpress.com. Website menampilkan informasi profil sekolah, kegiatan ekstrakurikuler sekolah, informasi penerimaan siswa baru, galeri kegiatan dan kontak sekolah. Dari hasil penilaian yang dilakukan oleh 39 responden dari guru dan karyawan, orang tua/wali serta masyarakat, diperoleh hasil rata-rata responden memberikan nilai Baik sebesar 50,6%, memberikan nilai Sangat Baik sebesar 32%, dan sisanya menilai Cukup untuk seluruh aspek penilaian.
Metode Naïve Bayes Untuk Prediksi Waktu Produksi Mebel di UD. Wali Barokah Kartasura Sukoharjo Jawa Tengah Abdul Dhohir Surya Kusuma, RM; Remawati, Dwi; Sandradewi, Kumaratih
Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA) Vol. 1 No. 1 (2024): Journal of Information Technology, Computer Engineering and Artificial Intellig
Publisher : Redtech Putra Benua

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Abstract

Wali Barokah is one of the industrial furniture craftsmen (furniture) with the main material using teak wood. The development of the times has made many furniture entrepreneurs appear, making the competition between furniture craftsmen increasingly tight. One way for customers not to be disappointed is that business voters must serve customers according to the specified time when transacting. The attributes that will be used in classifying the production time are the name of the item, the number of orders, the difficulty, the equipment, the number of workers. The method that will be used is the the method Naïve Bayes Classifier. Based on the results of the confusion matrix test on the nave Bayes method of the dataset that has been taken on the object of research, an accuracy rate of 80% is obtained or is included in the category Good. Meanwhile, Precision is 83% and Recall is 88%.
METODE K-MEANS CLUSTERING UUNTUK PEMETAAN GEDUNG OLAHRAGA RAGA BADMINTON DI SOLORAYA Prasetyo, Danar Aji; Remawati, Dwi; Nugroho, Didik
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 11, No 1 (2023): Jurnal TIKomSiN, Vol. 11, No. 1, April 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v11i1.730

Abstract

There are many Badminton Sports Buildings in the Soloraya area, including Sukoharjo Regency, Boyolali Regency, Klaten Regency, Wonogiri Regency, Karanganyar Regency, Sragen and Solo. Each Badminton Gymnasium has different conditions, starting from varying rental prices, as well as the various facilities offered by each Badminton Sports Hall. The purpose of this research is to help people in Soloraya find suitable badminton sports halls, an information system is needed that can explain the mapping of badminton sports halls in Soloraya. This study uses the K-Means and GIS methods to solve the problem of grouping badminton sports halls based on their categories. The result of this research is a geographic mapping information system to make it easier for people to find badminton courts that match the criteria of people in Soloraya.
SISTEM PAKAR DIAGNOSA PENYAKIT JAMUR (CRAYFISH PLAGUE) PADA LOBSTER AIR TAWAR MENGGUNAKAN METODE CERTAINTY FACTOR BERBASIS WEB Vivi Dian Pratiwi; Didik Nugroho; Sri Hariyati Fitriasih; Dwi Remawati
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 13, No 2 (2025): Jurnal Tikomsin, Vol 13, No.2, Oktober 2025
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v13i2.1018

Abstract

Crayfish plague, caused by the oomycete Aphanomyces astaci, is a deadly disease in crayfish/freshwater lobsters and poses a threat to lobster cultivation and sustainability. This study designed a web-based expert system to diagnose fungal disease (crayfish plague) in freshwater lobsters using the Certainty Factor (CF) method. Knowledge was gathered from observations at lobster farms and expert interviews. Seven symptoms were used and compiled as a rule base. The system was implemented using PHP and MySQL. The inference mechanism used a combination of expert and user CF, along with functional (black-box) and validity testing. The results showed a combined CF value for fungal diagnosis reached 0.9369 for the observed symptom combination. Seven scenarios tested yielded a 6/7 (85.7%) agreement. The expert system using the CF method is suitable for use as an early diagnosis tool for fungal diseases in freshwater lobsters, especially in local cultivation.
Digitalisasi Administrasi Pada PAUD Kenanga Desa Banaran Kecamatan Grogol Kabupaten Sukoharjo Melalui Pendampingan Teknologi Informasi Sandradewi, Kumaratih; Remawati, Dwi; Fitriasih, Sri Hariyati; Irawati, Tri
Jurnal Pengabdian Masyarakat Teknologi dan Pendidikan (MANTAP) Vol. 2 No. 3 (2025): Jurnal Pengabdian Masyarakat Teknologi dan Pendidikan (Jurnal Mantap)
Publisher : Redtech Putra Benua

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Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kapasitas guru PAUD dalam mengimplementasikan administrasi digital melalui pemanfaatan teknologi informasi. Fokus kegiatan mencakup tiga aspek utama, yaitu digitalisasi presensi siswa, pengembangan database siswa, dan pelatihan literasi digital bagi guru. Pendampingan dilakukan melalui sesi pelatihan, praktik langsung, dan bimbingan berkelanjutan. Hasil kegiatan menunjukkan peningkatan pemahaman dan keterampilan guru dalam menggunakan platform digital untuk administrasi harian. Program ini berkontribusi pada efisiensi kerja, ketepatan penyimpanan data, serta peningkatan layanan pendidikan di lingkungan PAUD.
Analysis of the Complexity of Heuristic Algorithms for Permutation Optimization in Large-Scale Computing Fitriasih, Sri Hariyati; Cynthia, Eka Pandu; Cynthia, Maulidania Mediawati; Cynthia, Dessy Nia; Remawati, Dwi
Jurnal Ilmu Komputer dan Teknik Informatika Vol. 2 No. 1 (2026): Januari 2026
Publisher : CV. Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/juikti.v2i1.79

Abstract

Permutation optimization is a fundamental problem in large-scale computing that arises in various applications such as scheduling, resource allocation, and combinatorial decision-making. As the size of the solution space grows exponentially, conventional optimization methods often struggle to achieve acceptable performance within reasonable computational time. Heuristic and metaheuristic algorithms have therefore become widely adopted due to their flexibility and ability to provide near-optimal solutions for NP-hard problems. However, increasing data scale significantly impacts their computational complexity, making efficiency and scalability critical concerns.This study aims to analyze the computational complexity and performance characteristics of several heuristic algorithms applied to permutation optimization in large-scale computing environments. The research employs a quantitative experimental approach combined with theoretical complexity analysis. Greedy heuristic, simulated annealing, genetic algorithm, and adaptive heuristic methods are evaluated using synthetic permutation datasets with varying sizes. Performance is assessed based on execution time, memory usage, scalability, and solution quality. The results indicate that greedy heuristics offer the fastest execution and lowest memory consumption but tend to produce suboptimal solutions due to their local search strategy. Simulated annealing improves solution quality through probabilistic exploration, while genetic algorithms achieve the highest-quality solutions at the cost of substantial computational and memory overhead. Adaptive heuristic algorithms demonstrate a balanced performance by dynamically adjusting parameters during execution, achieving near-optimal solutions with reduced computational complexity. Overall, this research highlights the trade-offs between efficiency and solution quality among heuristic algorithms and emphasizes the potential of adaptive heuristic approaches for large-scale permutation optimization. The findings provide valuable insights for designing efficient and scalable optimization algorithms suitable for real-world large-scale computing applications.
Analisis Perilaku Penggunaan Smartphone dan Prediksi Kualitas Tidur Menggunakan Metode Statistik dan Machine Learning Kirana Wardana, Adam Candra; Remawati, Dwi; Susyanto, Teguh
Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA) Vol. 3 No. 1 (2026): Journal of Information Technology, Computer Engineering and Artificial Intellig
Publisher : Redtech Putra Benua

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Abstract

The rapid growth of smartphone and social media usage has reshaped daily digital behavior and raised increasing concerns regarding its potential impact on sleep patterns. This study investigates the relationship between digital usage behavior, psychological factors, and sleep outcomes using an integrated data science approach. A publicly available Social Media Mental Health Indicators dataset from Kaggle was utilized, comprising 5,000 observations that capture screen time, social media activity, digital interactions, psychological conditions, and sleep duration. Data analysis was conducted through a structured pipeline involving data preprocessing, exploratory data analysis, clustering, and supervised machine learning for classification and regression tasks. Exploratory analysis indicates consistent negative associations between screen-related variables and sleep duration. Clustering analysis reveals distinct behavioral groups characterized by different levels of digital engagement and sleep patterns. Furthermore, Random Forest models demonstrate reliable performance in both sleep quality classification and sleep duration prediction, highlighting their effectiveness in modeling complex and non-linear relationships. Feature importance analysis identifies screen time, social media intensity, and negative digital interactions as dominant contributors to sleep-related outcomes. These findings emphasize the value of combining statistical exploration and machine learning techniques to obtain a comprehensive understanding of how digital behavior relates to sleep, providing empirical support for data-driven evaluation of healthier digital habits.
Development of Personalized Recommendation System for Online Educational Content Based on Machine Learning Dwi Remawati; Khairunnisa; Afril efan Pajri; Kumaratih Sandradewi; Sri Hariyati Fitriasih
Indonesian Applied Research Computing and Informatics Vol. 1 No. 1: July (2025)
Publisher : PT. Teras Digital Nusantara

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Abstract

The rapid growth of online educational platforms has increased the demand for intelligent recommendation systems that can personalize learning content to match individual learner needs. However, traditional methods such as Content-Based Filtering (CBF) and Collaborative Filtering (CF) often struggle with issues like data sparsity, limited adaptability, and cold-start problems. This study aims to develop a personalized recommendation system for online educational content by integrating Singular Value Decomposition (SVD) with an adaptive feedback loop to improve recommendation relevance and learner engagement. The proposed machine learning-based method captures latent user-item interactions and dynamically updates recommendations based on real-time user feedback. Experimental evaluation using a dataset of simulated learner interactions demonstrates that the proposed model significantly outperforms baseline methods, achieving higher scores in Precision (0.57), Recall (0.53), F1-Score (0.55), Mean Reciprocal Rank (MRR: 0.52), and Engagement Rate (72.1%). These results suggest that combining matrix factorization with adaptive learning can substantially enhance the performance of educational recommender systems, leading to more accurate, timely, and engaging content delivery.
Penguatan Identitas Visual UMKM Abon Dua Saudara melalui Kegiatan Desain Spanduk Aditya Bagas Pratama; Remawati, Dwi; Vulandari, Retno Tri; Sandradewi, Kumaratih; Yudanto, Bramasto Wiryawan
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.984

Abstract

The rapid development of technology in the modern era requires micro, small, and medium enterprises (MSMEs) to adapt in order to remain competitive, particularly in the area of marketing and information dissemination. Abon Dua Saudara MSME, which has operated for over twenty years in the food processing sector, faces challenges related to limited promotional media, resulting in low public awareness of its products. This community service activity aims to strengthen the visual identity of Abon Dua Saudara MSME through the design and development of promotional banners using CorelDraw. The method employed in this program includes needs assessment, design training, and direct assistance in creating effective and visually appealing banners. The activity focuses on improving participants’ skills in utilizing digital design tools to produce promotional media that are informative, attractive, and aligned with the business identity. The results of this program indicate an improvement in the MSME’s capability to create independent promotional materials, as well as an enhanced visual identity that supports broader market reach. In conclusion, the implementation of banner design activities contributes positively to strengthening the branding and promotional effectiveness of Abon Dua Saudara MSME. This initiative is expected to increase public awareness and support the sustainability and growth of the business.
PERBANDINGAN METODE SUPPORT VECTOR MACHINE DAN K-NEAREST NEIGHBOR DALAM ANALISIS SENTIMEN ULASAN APLIKASI MyXL Nugroho, Raka Aji; Remawati, Dwi; Susyanto, Teguh; Saptomo, Wawan Laksito Yuly
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 14, No 1 (2026): Jurnal Tikomsin, Vol 14, No.1, April 2026
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v14i1.1062

Abstract

Sentiment analysis is an essential tool for understanding user perceptions of mobile applications, especially when reviews are unstructured text. This study aims to analyze user reviews of the MyXL application using Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) and to compare their performance in classifying sentiments into positive, negative, and neutral categories. The dataset was obtained from Google Play Store via Kaggle and underwent text preprocessing, including case folding, removal of numbers and punctuation, tokenization, stopword removal, normalization, and stemming. Features were transformed into numerical representations using TF-IDF, and the data was split into training (70%) and testing (30%) sets. Evaluation using accuracy, precision, recall, and F1-score showed that SVM outperformed KNN with an accuracy of 0.743 versus 0.64, particularly in classifying neutral reviews. KNN exhibited higher misclassification in positive and negative classes, while SVM was more stable but tended to be biased toward the neutral class. These results provide insights for application developers to better understand user satisfaction and guide service improvement and feature development.
Co-Authors Abdul Dhohir Surya Kusuma, RM Abdullah Ahmad Ma'shum Aditya Bagas Pratama Ady Prabowo, Iwan Afril efan Pajri Ahmad Muhariya Ahyar, Khoirul Ajeng Dhanty Yoshima Aji Pratama Wisnu Wardana Amin Joko Susilo Bagus Cahyo Putro Baktiar Setiyaji Bebas Widada Bramasto Wiryawan Yudanto Bramastyo Wiryawan Yudhanto Charles Parningotan Haratua Simanjuntak Cynthia, Dessy Nia Cynthia, Maulidania Mediawati Dicky Jordan Aji Putra Didik Nugroho Didik Nugroho, Didik Dziky Ridhwanullah Effendi, Rohmat Irvan Eka Pandu Cynthia Firman Dwi Wahyudi Fitriani, Putri Asiska Nur Haqiqi, Arif Naofal Hendro Wijayanto Heru Budi Kusumo Iwan Ady Prabowo Khairunnisa Kirana Wardana, Adam Candra Kriswantoro Budi Satrio Kumaratih Sandradewi Kumaratih Sandradewi Kumaratih Sandradewi Kustanto Kustanto Lestari, Zannuba Anugrah Indah Muhammad Hasbi Mujirahayu Meyliana, Nirma Nugroho, Raka Aji Okky Puspa Ningrum paulus harsadi Prasastya Dwi Pamungkas Prasetyo, Danar Aji Putri Pertiwi, Ina Raden Arie Febrianto Raharja, Bayu Dwi Restu Utami, Widya Retno Tri Vulandari Ruvyanto Dwi Nugroho Saptomo, Wawan Laksito Yuly Septiana, Anisa Dwi Setiyowati Sri Hariyati Fitriasih Sri Hariyati Fitriasih Sri Hariyati Fitriasih Sri Hariyati Fitriasih, Sri Hariyati Teguh Susyanto Teguh Susyanto Tri Irawati Tri Irawati Tri Irawati Tri Irawati, Tri Tulus Wahyuno Vivi Dian Pratiwi Wawan Laksito Yuly Saptomo Widada, Bebas Widianto, Septian Cahyo Wijayanto, Hendro Yustina Retno Wahyu Utami