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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 JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal Responsif : Riset Sains dan Informatika Decode: Jurnal Pendidikan Teknologi Informasi Journal Computer Science and Informatic Systems : J-Cosys 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 Journal of International Multidisciplinary Research Journal of Data Analytics, Information, and Computer Science (JDAICS) Applied Information Technology and Computer Science (AICOMS) Cahaya Pengabdian Jurnal Penelitian Sains Teknologi
Nova Tri Romadloni
Universitas Muhammadiyah Karanganyar
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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.
Klasifikasi Citra Buah Menggunakan Algoritma K-Nearest Neighbour (KNN) dan Metode Euclidean Distance Tristanti, Novi; Romadloni, Nova Tri; Sya’bani, Nur Hayati
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.v4i3.3243

Abstract

Pengolahan citra digital merupakan salah satu bidang penting dalam computer vision yang berfokus pada interpretasi citra untuk memperoleh informasi bermakna, khususnya dalam proses identifikasi dan klasifikasi objek berbasis karakteristik visual. Penelitian ini bertujuan mengembangkan sistem klasifikasi otomatis untuk membedakan jenis buah dengan menerapkan algoritma K-Nearest Neighbor (KNN) menggunakan pendekatan Euclidean Distance pada lingkungan MATLAB. Prosedur penelitian dilaksanakan melalui beberapa tahapan utama, meliputi pre-processing, ekstraksi ciri, normalisasi histogram, serta klasifikasi. Pada tahap pre-processing, citra yang menjadi dataset terlebih dahulu dikonversi ke bentuk grayscale, dilanjutkan dengan proses noise reduction dan binarisasi guna meningkatkan kualitas citra serta memperjelas fitur objek. Tahap ekstraksi ciri kemudian dilakukan untuk memperoleh informasi visual yang relevan, sedangkan normalisasi histogram berfungsi menstandarkan distribusi intensitas piksel agar proses klasifikasi menjadi lebih optimal. Hasil pengujian menunjukkan bahwa sistem mampu melakukan pengenalan citra buah dengan tingkat akurasi rata-rata sebesar 93,3%. Capaian ini mengindikasikan bahwa kombinasi metode ekstraksi fitur dengan algoritma KNN cukup efektif dalam mengelompokkan citra berdasarkan kemiripan karakteristik visualnya. Secara praktis, sistem ini berpotensi diterapkan dalam proses sortasi buah secara otomatis pada sektor pertanian maupun industri pengolahan hasil pangan. Meskipun demikian, pengembangan lebih lanjut masih diperlukan, misalnya melalui penambahan variasi dataset, peningkatan kualitas citra, serta penerapan algoritma klasifikasi yang lebih adaptif agar sistem mampu bekerja secara optimal pada kondisi citra yang lebih kompleks dan bervariasi.
CLASSIFICATION OF SMS SPAM WITH N-GRAM AND PEARSON CORRELATION BASED USING MACHINE LEARNING TECHNIQUES Romadloni, Nova Tri; Septiyanti, Nisa Dwi; Pratomo, Cucut Hariz; Kurniawan, Wakhid; Bintang, Rauhulloh Ayatulloh Khomeini Noor
SENTRI: Jurnal Riset Ilmiah Vol. 3 No. 2 (2024): SENTRI : Jurnal Riset Ilmiah, February 2024
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v3i2.2252

Abstract

The Short Message Service (SMS) has garnered widespread popularity due to its simplicity, reliability, and ubiquitous accessibility.This study aims to enhance the efficacy of SMS classification by refining the classification process itself. Specifically, it strives to streamline the process by diminishing feature dimensions and eliminating inconsequential attributes. The textual data undergoes preprocessing, which involves employing the N-Gram technique for feature representation, followed by meticulous feature selection utilizing Pearson Correlation. The study employs 5 of classification algorithms. Notably, the findings underscore that the optimal outcomes emerge from the fusion of the N-Gram methodology with feature selection through Pearson Correlation. Among these, the Support Vector Machine methodology stands out, exhibiting a remarkable 91.41% enhancement in accuracy without feature selection, a further improvement to 91.96% through N-Gram utilization, and a final performance of 70.80% following the inclusion of weighted correlation. However, it is imperative to acknowledge the limitations inherent in the model's generalizability, primarily stemming from the utilization of a relatively modest dataset. Despite the efficacy of Pearson correlation and N-gram-based feature selection in curbing data dimensionality and enhancing processing efficiency, certain pertinent features may have been overlooked, or the chosen attributes might not be optimally suited for specific classifications.
Penyuluhan Cerdas Literasi Digital dalam Menghadapi Penyebaran Berita Hoaks pada Anggota Bhayangkari Tri Romadloni, Nova; Supriyanti, Wiwit
INCOME: Indonesian Journal of Community Service and Engagement Vol 2 No 2 (2023)
Publisher : EDUPEDIA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56855/income.v2i2.402

Abstract

The wide and rapid spread of hoax news via the internet, social media or other digital platforms has become a serious problem in society, including among Bhayangkari members. This community service has the goal of making digital literacy smart in helping Bhayangkari members deal with the spread of hoax news. This training aims to provide the understanding and skills needed to recognize, analyze, and respond wisely to hoax news. This counseling process is an experimental pretest-posttest given to Bhayangkari members. The results show that digital literacy smart counseling has a positive impact on increasing the knowledge and skills of Bhayangkari members in dealing with the spread of hoax news. This is about knowledge about hoax news, the ability to verify information, and awareness of the consequences of spreading hoax news. Bhayangkari members from the Jatiyoso branch who attended counseling were more skeptical of unverified information, were more careful in disseminating information, and were more active in checking the truth of news before believing it.
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.
Perbandingan Algoritma Klasifikasi Terhadap Review Aplikasi Maxim Menggunakan Teknik Klasifikasi Machine learning Romadloni, Nova Tri; Mulia, Pamela Hana; Supriyanti, Wiwit
Technologica Vol. 5 No. 1 (2026): Technologica
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/technologica.v5i1.268

Abstract

Perkembangan teknologi telah membawa dampak besar terhadap sistem transportasi publik, salah satunya dengan munculnya layanan ojek online yang memungkinkan pemesanan melalui aplikasi digital. Salah satu layanan transportasi daring yang cukup populer adalah Maxim, yang telah diunduh lebih dari 50 juta kali. Ulasan pengguna terhadap aplikasi ini menjadi sumber informasi penting untuk menilai pengalaman mereka serta sebagai dasar dalam upaya peningkatan kualitas layanan. Penelitian ini bertujuan untuk mengevaluasi dan membandingkan kinerja beberapa algoritma machine learning dalam mengklasifikasikan sentimen dari ulasan pengguna Maxim. Data dikumpulkan menggunakan metode web scraping dan dikelompokkan berdasarkan rating bintang. Tahapan pra-pemrosesan mencakup pembersihan teks, tokenisasi, stemming, dan pembobotan menggunakan metode TF-IDF. Algoritma yang digunakan meliputi Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Decision Tree, K-Nearest Neighbors (KNN), dan Random Forest (RF). Evaluasi dilakukan menggunakan metrik akurasi, presisi, recall, dan F1-score. Berdasarkan hasil analisis, algoritma Random Forest menunjukkan kinerja terbaik dengan akurasi mencapai 95%. Secara umum, hasil penelitian ini menegaskan bahwa Random Forest unggul dibandingkan algoritma lain dalam menganalisis sentimen ulasan pengguna aplikasi Maxim
A Hybrid Approach of Pearson Correlation and PCA in Feature Selection for Opinion Mining Tri Romadloni, Nova; Kurniawan, Wakhid; Ariyadi, Muhammad Yusuf; Efendi, Burhan
IJID (International Journal on Informatics for Development) 2025
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

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

Abstract

This study proposes a hybrid feature selection approach that combines Pearson Correlation and Principal Component Analysis (PCA) to improve classification performance in opinion mining tasks. The rapid growth of e-commerce on social media platforms, such as TikTok, has generated a significant volume of user-generated reviews, which are valuable sources of consumer sentiment. However, the high dimensionality of textual data poses challenges in achieving accurate sentiment classification. To address this issue, the proposed method first applies Pearson Correlation to remove irrelevant features with weak correlation to sentiment labels, followed by PCA to reduce dimensionality. The dataset consists of user reviews from the TikTok Seller platform. Experiments using SVM, Naive Bayes, and Random Forest show that the hybrid approach achieves the highest accuracy of 86.2% (SVM and RF), improving over PCA-only by +0.9% and recovering 13.8% accuracy loss for Naive Bayes (from 72.0% to 83.1%). The results demonstrate that integrating correlation- and projection-based methods yields a more compact and effective feature set. This approach is especially suited for opinion mining in noisy, high-dimensional e-commerce data.
Sosialisasi Bijak Menggunakan Gadget untuk Edukasi Orang Tua dalam Mendampingi Anak Belajar Nova Tri Romadloni; Hasna Karima, Fatimah; Mariyanto, Mariyanto
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 4 No. 4 (2025): November 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v4i4.6520

Abstract

The use of gadgets has become an essential part of daily life, including in supporting children’s learning processes. Gadgets provide wide access to information, interactive educational applications, and opportunities to develop digital skills. However, excessive use without proper guidance can lead to negative impacts such as physical health problems, digital addiction, decreased concentration, and reduced social interaction. These challenges highlight the crucial role of parents as guides, supervisors, and role models in ensuring wise gadget use. This community service program aimed to educate parents, particularly PKK mothers in Dawung Village, on practical strategies for accompanying children in their use of gadgets. The activities were carried out through socialization sessions, interactive discussions, and quizzes. The discussion revealed major issues faced by parents, such as difficulty in limiting screen time, children’s preference for gaming over learning, and limited knowledge of educational applications. Meanwhile, the quiz results indicated that most participants achieved “good” (45%) and “very good” (37.5%) categories, with an average score of 72, showing improved understanding after the program. This program concludes that family digital literacy can be strengthened through interactive socialization that actively involves participants. With consistent parental guidance, gadgets can be directed to become a healthy, productive, and safe learning tool for children’s development.
Co-Authors Adi Jufriansah Akib, Irwan Avianti, Risqi Nur Azmi Khusnani Budilaksono, Sularso Cucut Hariz Pratomo Cucut Hariz Pratomo Edwin Ariesto Umbu Malahina Efendi, Burhan Erwinda Sam Anafih Fanani, Galih Pramuja Inngam Hana Mulia, Pamela Handoko, Frendy Prasetyo Hani Setiani Hasna Karima, Fatimah Hendri Setiawan Hilman F Pardede IMAM SANTOSO Kurniaji, Ganno Tri Buana Kurniawan, Wakhid Lenny Puspita Dewi Mariyanto Mariyanto Mariyanto Maure, Osniman Paulina 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 Nurul Iksani, Salma Pratomo, Cucut Hariz Primananda, Masdicka Maulana Rahmawati, Aderima Rauhulloh Ayatulloh Khomeini Noor Bintang Resi Intan Penatari Rianti , Ria Rika Putri Utami Saefudin Samsi Samsi Sari, Desi Lajar Setyawati, Yayuk Sholefah, Wahyu Putri Sya’bani, Nur Hayati Tanti Diyah Rahmawati, Tanti Diyah Tristanti, Novi Wakhid Kurniawan Wakhid Kurniawan Wiwit Supriyanti YAN ADITYA PRADANA Yayu Sri Rahayu Yitno Puguh Martomo