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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) IKRA-ITH Informatika : Jurnal Komputer dan Informatika IJID (International Journal on Informatics for Development) Jurnal Ilmiah Sinus TIN: TERAPAN INFORMATIKA NUSANTARA JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal Responsif : Riset Sains dan Informatika Decode: Jurnal Pendidikan Teknologi Informasi Journal Computer Science and Informatic Systems : J-Cosys KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Technologica SENTRI: Jurnal Riset Ilmiah Jurnal Keilmuan dan Keislaman INCOME: Indonesian Journal of Community Service and Engagement Journal of Artificial Intelligence and Digital Business Jurnal Saintifik JUSTIFY : Jurnal Sistem Informasi Ibrahimy Journal of International Multidisciplinary Research Journal of Data Analytics, Information, and Computer Science (JDAICS) Applied Information Technology and Computer Science (AICOMS) Cahaya Pengabdian Journal of Big Data Analytic and Artificial Intelligence Smatika Jurnal : STIKI Informatika Jurnal Jurnal Penelitian Sains Teknologi
Nova Tri Romadloni
Universitas Muhammadiyah Karanganyar
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Strategi Meningkatkan Pemahaman Informasi Media Sosial Untuk Pemilih Cerdas Bagi Kelompok Dasawisma Tri Romadloni, Nova; Erwinda Sam Anafih; Nisa Dwi Septiyanti; Saefudin
Journal of International Multidisciplinary Research Vol. 2 No. 1 (2024): Januari 2024
Publisher : PT. Banjarese Pacific Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62504/anqxmr55

Abstract

Pemilu merupakan momen penting dalam kehidupan demokrasi di Indoensia. Salah satu tantangan utama yang dihadapi adalah tingkat pemahaman informasi media sosial di kalangan pemilih, terutama pada tingkat dasawisma. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mengembangkan dan menerapkan strategi yang efektif dalam meningkatkan pemahaman informasi media sosial bagi kelompok dasawisma guna mendukung terbentuknya pemilih cerdas menjelang Pemilu. Metode penelitian ini mencakup identifikasi kebutuhan melalui studi awal di tingkat dasawisma, desain program pelatihan yang sesuai dengan kebutuhan, dan pelaksanaan kegiatan yang melibatkan partisipasi aktif dari anggota kelompok. Evaluasi dilakukan dengan mengukur tingkat pemahaman informasi media sosial sebelum dan setelah pelaksanaan kegiatan. Hasil kegiatan menunjukkan peningkatan yang signifikan dalam pemahaman informasi media sosial di kalangan kelompok dasawisma. Strategi yang melibatkan sesi pemaparan materi, diskusi interaktif, dan penerapan langsung di media sosial telah berhasil membangun kesadaran dan keterampilan dalam memahami serta menyaring informasi yang diterima. Kegiatan ini memberikan kontribusi dalam konteks peningkatan literasi politik di tingkat masyarakat dasawisma dan memberikan landasan bagi pengembangan strategi serupa di komunitas sejenis. Peningkatan pemahaman informasi media sosial diharapkan dapat membantu pemilih dalam membuat keputusan yang lebih informasional dan cerdas saat menghadapi Pemilu, yang pada gilirannya dapat memperkuat kualitas demokrasi di tingkat lokal. 
Komparasi Metode Klasifikasi Dalam Analisis Sentimen Ulasan Pengguna Aplikasi KRL Access Di Google Play Store Septiyanti, Nisa Dwi; Luthfi, Muhammad Irfan; Romadloni, Nova Tri
Journal Computer Science and Information Systems : J-Cosys Vol 4, No 1 (2024): J-Cosys - Maret 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53514/jco.v4i1.495

Abstract

Peningkatan penggunaan aplikasi transportasi umum, seperti KRL Access, menciptakan kebutuhan untuk memahami sentimen pengguna terhadap aplikasi tersebut. Analisis sentimen dapat menjadi alat efektif dalam memahami persepsi dan kepuasan pengguna. Penelitian ini mengisi kesenjangan dengan mengeksplorasi pengaruh berbagai algoritma klasifikasi dan langkah-langkah data preprocessing terhadap analisis sentimen ulasan pengguna KRL Access. Penelitian ini memberikan pandangan yang melibatkan pertanyaan-pertanyaan kritis tentang pengaruh algoritma klasifikasi (Naïve Bayes, Random Forest, Logistic Regression, Supervised Machine Learning [SVM], dan K-Nearest Neighbors [KNN]) terhadap hasil analisis sentimen. Selain itu, penting untuk memahami kontribusi langkah-langkah data preprocessing (case folding, data filtering, tokenization, stemming, dan removing stopwords) terhadap akurasi dan keandalan analisis sentimen. Hasil penelitian menunjukkan bahwa setiap algoritma memiliki kelebihan dan kelemahan masing-masing. Naïve Bayes menonjol dalam precision, sementara Random Forest memberikan keseimbangan yang baik antara precision dan recall. Langkah-langkah data preprocessing, terutama tokenization dan stemming, berkontribusi signifikan terhadap kualitas analisis sentimen. Visualisasi sentimen melalui wordcloud memberikan gambaran intuitif, menyoroti kepuasan pengguna atas akses informasi jadwal KRL Access, tetapi juga masalah dalam pendaftaran dan login. Kesimpulan penelitian menekankan pentingnya pemilihan algoritma dan data preprocessing yang sesuai untuk analisis sentimen yang akurat. Temuan ini dapat mendukung pengembangan aplikasi yang lebih responsif dan sesuai dengan kebutuhan pengguna, menciptakan pengalaman pengguna transportasi umum yang lebih baik. Dalam penelitian mendatang, disarankan untuk memperluas cakupan dataset dan eksplorasi lebih lanjut terhadap teknik data preprocessing dan penggunaan fitur tambahan
ANALISIS DAMPAK CACHE PROGRESSIVE WEB APPS TERHADAP KONSUMSI BATERAI ANDROID Kurniawan, Wakhid; Romadloni, Nova Tri; Noor Bintang, Rauhulloh Ayatulloh Khomeini
Jurnal Informatika dan Teknik Elektro Terapan Vol 13, No 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6221

Abstract

Penggunaan aplikasi web berkembang pesat, terutama di Android yang menguasai 46,18% pangsa pasar global. Pengguna menginginkan akses cepat, namun sering menghadapi koneksi lambat dan pemuatan ulang aset tanpa cache, yang dapat meningkatkan konsumsi baterai. Salah satu faktor yang diduga berpengaruh adalah penggunaan cache dalam aplikasi. Progressive Web Apps (PWA) menjadi relevan karena memanfaatkan service worker untuk menyimpan cache. PWA menawarkan keunggulan seperti akses tanpa koneksi, pemrosesan latar belakang, dan notifikasi push, memberikan pengalaman serupa aplikasi native. Penelitian ini menganalisis dampak cache PWA terhadap konsumsi baterai Android. Metode yang digunakan bersifat kuantitatif dengan eksperimen empiris. Sebanyak 33 situs PWA dipilih menggunakan Google Lighthouse. Data ukuran cache dikumpulkan, dan laporan bug dihasilkan selama 3 menit untuk mengukur konsumsi daya. Analisis dilakukan menggunakan uji Paired Sample T-Test dengan SPSS, membandingkan konsumsi baterai saat cache kosong dan terisi. Penelitian ini bertujuan memberikan wawasan mengenai pengaruh cache terhadap konsumsi daya, sehingga strategi dapat dikembangkan untuk meningkatkan efisiensi energi dan pengalaman pengguna.
PERBANDINGAN KINERJA ALGORITMA KLASIFIKASI PADA REVIEW PENGGUNA APLIKASI NETFLIX KHOMEINI NOOR BINTANG, RAUHULLOH AYATULLOH; Romadloni, Nova Tri
Jurnal Informatika dan Teknik Elektro Terapan Vol 13, No 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6303

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna aplikasi Netflix yang diperoleh dari Google Play Store menggunakan metode web scraping dengan Python di Google Colab. Data ulasan diproses melalui tahap pembersihan teks, tokenisasi, penghapusan stopword, dan stemming, serta direpresentasikan menggunakan metode Term Frequency-Inverse Document Frequency (TF-IDF). Lima algoritma klasifikasi, yaitu Logistic Regression, Naive Bayes, Decision Tree, Random Forest, dan Support Vector Machine (SVM), dibandingkan untuk menentukan algoritma terbaik dalam klasifikasi sentimen positif, negatif, dan netral. Evaluasi dilakukan berdasarkan akurasi dengan pembagian data latih dan data uji sebesar 90:10. Hasil pengujian menunjukkan bahwa Logistic Regression dan Random Forest memiliki akurasi tertinggi sebesar 76%, diikuti oleh SVM sebesar 74%, Decision Tree sebesar 73%, dan Naive Bayes dengan akurasi terendah sebesar 71%. Temuan ini memberikan kontribusi bagi penelitian di bidang analisis sentimen serta dapat menjadi referensi bagi pengembang aplikasi dalam meningkatkan pengalaman pengguna berbasis data.
Analisis Kualitas Website Pesona Karanganyar Menggunakan Metode WebQual 4.0 Tri Romadloni, Nova; Hana Mulia, Pamela; Nova Ellyanza, Marcellina; Nurul Iksani, Salma; Rianti , Ria; Rahmawati, Aderima
Applied Information Technology and Computer Science (AICOMS) Vol 2 No 2 (2023)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v2i2.1263

Abstract

The Pesona Karanganyar website serves as an information platform accessible to all users without limitations. This official website provides comprehensive information about tourism destinations, events, and available facilities. It aims to deliver an informative and interactive experience for users, making it easier for them to plan trips and explore the beauty of Karanganyar. To provide excellent service to potential visitors, it is crucial to enhance the website's quality by assessing user satisfaction, identifying existing issues, and considering improvements for future development. This study evaluates the quality of the Pesona Karanganyar website using the WebQual 4.0 method. Data collection was conducted through surveys using a Google Form questionnaire based on WebQual dimensions, involving a total of 60 respondents. The validity and reliability of the data were tested as prerequisites. Data analysis involved calculating scores and averages for each indicator. The results of this analysis indicate that the usability, information quality, and interaction quality variables of the Pesona Karanganyar website are of good quality. These findings suggest that the Department of Tourism, Youth, and Sports of Karanganyar Regency should regularly evaluate the website's maintenance and development to improve the quality of its services.
Uncovering Insights in Spotify User Reviews with Optimized Support Vector Machine (SVM) Tri Romadloni, Nova; Kurniawan, Wakhid
IJID (International Journal on Informatics for Development) Vol. 14 No. 1 (2025): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

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

Abstract

The rapid growth of user-generated reviews on platforms like Spotify necessitates efficient analytical techniques to extract valuable insights.  This study employs a Support Vector Machine algorithm, optimized using Forward Selection, Backwards Elimination, Optimized Selection, Bagging, and AdaBoost, to effectively classify user reviews. A dataset of approximately 10,000 Spotify reviews was compiled from diverse online sources, ensuring a representative sample. The analysis reveals sentiment patterns across positive, negative, and neutral categories, with positive reviews dominates the landscape. These patterns help highlight Spotify’s strengths while identifying areas for improvement. However, the SVM algorithm faces challenges in classifying minority classes, particularly negative sentiments, due to class imbalance. To address this, advanced optimization techniques are utilized to enhance classification precision and recall. Preprocessing steps, including data cleansing, tokenization, stemming, and stopword removal, refine the dataset, while TF-IDF converts text into numerical features for effective feature selection. The results show that the Optimized Selection method achieves the highest accuracy of 84.5%, outperforming other approaches. This research contributes significantly to developing balanced sentiment analysis models. Future studies may explore deep learning techniques to further improve classification accuracy and mitigate current limitations in data representation.
ANALYSIS OF SERVICE QUALITY ASSESSING CUSTOMER SATISFACTION WITH THE MAXIM APPLICATION THROUGH SERVICE QUALITY Mukhlis, Mukhlis; Romadloni, Nova Tri
Journal of Data Analytics, Information, and Computer Science Vol. 1 No. 1 (2024): January
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jdaics.v1i1.423

Abstract

Technological advancement has impacted every facet of human existence, including transportation. The internet plays a major role in people's daily lives these days. This study aims to investigate the effects of service quality principles on user satisfaction through empirical testing. Utilizing SPSS 23, data from surveys given to Maxim users will serve as a data source for testing the hypothesis. The partial analysis results back up the problem formulation by showing that the variables Emphaty (X4), Reliable (X1), Responsiveness (X2), Assurances (X3), and Tangible (X5) all have a small but positive effect on how satisfied Maxim application users are. Conversely, the concurrent study reveals a 51% positive impact on Maxim app users' enjoyment from the factors Resilience (X1), Responsiveness (X2), Assurances (X3), Emphaty (X4), and Tangibles (X5).  Keywords: Maxim, Service quality, SPSS
Pemberdayaan Literasi Digital Siswa melalui Kegiatan Lokakarya Kolaboratif Disarpus Karanganyar Kurniawan, Wakhid; Romadloni, Nova Tri; Bintang, Rauhulloh Ayatulloh Khomeini Noor; Ardiansyah, Muhammad
Cahaya Pengabdian Vol. 2 No. 1 (2025): Juni 2025
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/cp.v2i1.191

Abstract

The rapid development of the digital era demands that the younger generation possess strong digital literacy skills. Digital literacy is not merely the ability to operate digital devices but also involves understanding ethics, security, and the capacity to critically evaluate information. This community service activity aimed to empower high school students in understanding and applying digital literacy through a workshop organized by the Department of Archives and Library (Disarpus) of Karanganyar Regency, in collaboration with lecturers from the Informatics Department of Universitas Muhammadiyah Karanganyar (UMUKA). The workshop was designed using a participatory approach and covered four pillars of digital literacy: hardware, software, digital ethics, and cybersecurity. Key topics included the dangers of cyberbullying, hoaxes, phishing, and best practices for protecting personal data, including the introduction of two-factor authentication (2FA) and Single Sign-On (SSO) technology. The activities included simulations, quizzes, and interactive discussions to enhance student engagement. The results showed a significant improvement in students’ understanding and awareness of the importance of being wise and safe in digital spaces. This program serves as an effective collaborative model between government institutions and higher education in enhancing students’ digital competencies. It is expected that similar initiatives can be replicated in other regions as a contribution to strengthening national digital literacy resilience.
Cerdas Digital dengan Artificial Intelligence: Solusi Teknologi untuk Pelayanan dan Keamanan Publik Tristanti, Novi; Fanani, Galih Pramuja Inngam; Romadloni, Nova Tri; Efendi, Burhan; Setiani, Hani
Cahaya Pengabdian Vol. 2 No. 1 (2025): Juni 2025
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/cp.v2i1.207

Abstract

Artificial intelligence (AI)-based digital technology presents both opportunities and challenges for village security officers, particularly Village Supervisory Non-Commissioned Officers (Bhabinkamtibmas), in addressing the spread of hoaxes and meeting the demands for fast and efficient public services. The low level of digital literacy and practical skills in utilizing AI at the village level prompted the implementation of a community service program titled “Digital Intelligence with Artificial Intelligence: Technological Solutions for Public Service and Security.” This program aimed to enhance Bhabinkamtibmas’s understanding and ability to apply AI in public service and village security. The method used was a combination of theoretical and practical training for 30 Bhabinkamtibmas participants, covering three main topics: chatbot utilization for public services, face recognition for security support, and AI-based hoax content detection. Effectiveness was evaluated through pretest and posttest assessments. The results showed an average improvement of 40%, with posttest scores reaching 85% for chatbot usage, 80% for face recognition, and 75% for hoax detection. These findings demonstrate that practice-based training effectively improves Bhabinkamtibmas’s digital literacy and technical skills. In conclusion, this program successfully equips Bhabinkamtibmas as digital literacy agents capable of leveraging AI to strengthen public services and village security, contributing to the development of an adaptive Smart Policing ecosystem in the digital era.
The Influence of Service Quality in the Issuance of SKCK on Public Satisfaction at Jatiyoso Police Section Handoko, Frendy Prasetyo; Samsi, Samsi; Martomo, Yitno Puguh; Romadloni, Nova Tri
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2536

Abstract

This study aims to determine the influence of service quality on public satisfaction in the issuance process of Police Certificate of Good Conduct (SKCK) at Jatiyoso Police Sector. The background of this research is the urgency of public service quality as a performance indicator of government institutions, particularly in the police sector. This research employed a quantitative method with a descriptive correlational approach. Data was collected through questionnaires distributed to 146 SKCK applicants at Jatiyoso Police Section. Service quality was measured using five Servqual dimensions: Tangibles, Reliability, Responsiveness, Assurance, and Empathy. The analysis revealed that all dimensions positively affected public satisfaction, with Assurance and Empathy being the most dominant. Public satisfaction was categorized as high, as reflected in their willingness to reuse and recommend the service. The study recommends enhancing human resources, strengthening infrastructure, and implementing a continuous service evaluation system.
Co-Authors Adi Jufriansah Ammar Shafiy Audy Trinugroho Listyawan Avianti, Risqi Nur Azmi Khusnani Budilaksono, Sularso Burhan Efendi Cucut Hariz Pratomo Cucut Hariz Pratomo David Febrianto Desi Lajar Sari Edwin Ariesto Umbu Malahina Efendi, Burhan Erwinda Sam Anafih Fanani, Galih Pramuja Inngam Fatimah Hasna Karima Hana Mulia, Pamela Handoko, Frendy Prasetyo Hani Setiani Hendri Setiawan Hilman F Pardede IMAM SANTOSO Irwan Akib Kurniaji, Ganno Tri Buana Kurniawan, Wakhid Lenny Puspita Dewi Mariyanto Mariyanto Mariyanto Miswanto Muhammad Ardiansyah Muhammad Irfan Luthfi Muhammad Qolbi Shobri Muhammad Syahriandi Adhantoro Muhammad Yusuf Ariyadi Mukhlis Mukhlis Mulia, Pamela Hana Mulyawati, Theana Lativa Nashiruddin, Abid Naufal Ishartono Nawwar, Nabil Abiyu Nisa Dwi Septiyanti Nova Ellyanza, Marcellina Nugraheni, Anidhya Siwi Nur Hayati Nurul Iksani, Salma Osniman Paulina Maure Pratomo, Cucut Hariz Primananda, Masdicka Maulana Rahmawati, Aderima Rauhulloh Ayatulloh Khomeini Noor Bintang Resi Intan Penatari Rianti , Ria Rika Putri Utami Saefudin Salma Nurul Ikhsani Samsi Samsi Sari, Desi Lajar Setyawati, Yayuk Sholefah, Wahyu Putri Sya’bani, Nur Hayati Tanti Diyah Rahmawati Tristanti, Novi Wahyu Putri Sholefah Wakhid Kurniawan Wakhid Kurniawan Wiwit Supriyanti YAN ADITYA PRADANA Yayu Sri Rahayu Yitno Puguh Martomo