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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Informatics and Communication Technology (IJ-ICT) International Journal of Advances in Applied Sciences Jurnal Transformatika Al-Ihkam: Jurnal Hukum dan Pranata Sosial TRANSISTOR Elektro dan Informatika E-Dimas: Jurnal Pengabdian kepada Masyarakat Sistemasi: Jurnal Sistem Informasi Indonesian Journal of Community Services Abdimas Universal JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Nusantara of Engineering (NOE) Prosiding Seminar Riset Mahasiswa Jurnal Ilmiah Sultan Agung Journal of Data Insights Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Rekayasa Sistem Informasi dan Teknologi Journal of Computer Science and Information Technology
Riansyah, Andi
Universitas Islam Sultan Agung
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Other

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Implementasi Sistem Informasi Surat Online Realtime Pada Organisasi Badan Wakaf Ghufron; Badieah, Badieah; Riansyah, Andi
Nusantara of Engineering (NOE) Vol 6 No 1 (2023): Volume 6 No 1 Tahun 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/noe.v6i1.19911

Abstract

Sistem Informasi Surat Online Realtime pada Organisasi Badan Wakaf solusi teknologi informasi untuk mempercepat proses pengelolaan surat dan tugas secara efektif dan efisien. Sistem memungkinkan pengguna untuk menerima surat dari setiap unit secara real-time. Sistem dirancang untuk memudahkan proses pengelolaan tugas dari setiap unit, untuk dapat meminimalkan kesalahan, meningkatkan produktivitas dan mengurangi biaya operasional pengiriman surat fisik. Notifikasi otomatis, arsip digital, dan sebagai tugas pada bagian atau unit merupakan fitur sistem ini. pengguna dapat memantau dan melacak status surat secara real-time, proses tindak lanjut surat. Implementasi sistem pada badan wakaf melibatkan beberapa tahap, analisis kebutuhan, perancangan sistem, pengembangan sistem, uji coba dan peluncuran sistem. Tahap analisis kebutuhan mencakup identifikasi masalah dan kebutuhan pengguna, sedangkan tahap perancangan sistem melibatkan desain dan pemodelan sistem. Tahap pengembangan sistem melibatkan pengkodean dan pengujian sistem, sedangkan tahap uji coba dilakukan untuk memastikan sistem berjalan dengan baik sebelum peluncuran. Diperlukan pelatihan untuk pengguna agar dapat menggunakan sistem dengan benar dan efektif. Dalam implementasi sistem informasi perlu memperhatikan faktor-faktor yang mempengaruhi penerimaan dan penggunaan sistem oleh pengguna. Faktor-faktor ini termasuk keamanan dan privasi, kemudahan penggunaan, dan dukungan dari manajemen. Harapannya untuk efisiensi pekerjaan dan memberikan manfaat yang signifikan proses permintaan dari unit di bawah yayasan badan wakaf.
Implementation of An Indonesian Vehicle License Plate Recognition System In Real-Time Using EasyOCR and Regex Pattern Validation Moch Taufik; Asep Hernandi; Muhammad Wahyu Syaiful Anaam; Andi Riansyah
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.473

Abstract

This study presents the design and implementation of a real-time Automatic License Plate Recognition (ALPR) system specifically tailored for Indonesian vehicle plates, integrating EasyOCR, computer vision-based image preprocessing, and Regular Expression (regex) validation. The system captures images or video streams and applies a multi-level preprocessing pipeline, including grayscale conversion, Gaussian noise reduction, edge detection, and contour-based plate localization, before performing optical character recognition based on deep learning using a convolutional recurrent neural network with an attention mechanism. Post-recognition processing with regex filtering ensures strict compliance with the official Indonesian license plate format, thereby minimizing false positives and improving recognition accuracy. Experimental evaluation using real-world surveillance data achieved 75% accuracy, 100% precision, 75% recall, and an F1-score of 86%, indicating an optimal balance between detection precision and sensitivity. The system’s advantages include real-time performance, ease of deployment with open-source software, and adaptability to various lighting and environmental conditions. However, the system still shows limitations under extreme conditions such as nighttime, heavy rain, and dense traffic, where recognition accuracy tends to decrease. Therefore, future research will focus on algorithm optimization for low-light, adverse weather, and motion-blur scenarios, large-scale deployment in urban areas, and integration with AI-based vehicle tracking, positioning this system as a key enabling technology in the development of smart city infrastructure.
Implementation of XGBoost for diabetes mellitus risk prediction based on health history Riansyah, Andi; Ghufron, Ghufron; Fitriyah, Lailatul; Suyanto, Suyanto
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1028-1039

Abstract

Diabetes mellitus (DM) is a chronic disease with a growing global burden and specific challenges for early management, particularly in regions with limited access to healthcare. This study develops a web-based system to classify diabetes risk from medical history using extreme gradient boosting (XGBoost), an ensemble model of decision trees. The dataset comprised 520 respondents (320 DM, 200 non-DM) and underwent labeling, standardization, and an 80:20 train–test split, followed by hyperparameter selection via grid search and 5-fold cross-validation (CV). On the test set, the model achieved an accuracy of 0.9888, precision of 1.0000, recall of 0.9718, and an F1-score of 0.9857; discriminative performance was also strong with an area under the receiver operating characteristic curve (AUC ROC) of 0.839. These findings confirm that XGBoost effectively handles complex or imbalanced medical data while providing probabilistic outputs that are clinically meaningful. Deployed as a web application, the system can support early screening, triage, and clinical decision-making, thereby expediting referrals and personalizing interventions in primary care and hospital settings, especially in resource-constrained environments. This work lays the groundwork for further development, including the integration of explainable artificial intelligence (XAI) techniques to enhance clinical transparency.
MSME Digital Transformation Readiness Prediction for Data-Driven Decision Support: Prediksi Kesiapan Transformasi Digital UMKM untuk Dukungan Pengambilan Keputusan Berbasis Data Andi Riansyah; Maya Indriastuti; Maulana Ahmad Widiarta
Journal of Data Insights Vol 4 No 1 (2026): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v4i1.1193

Abstract

Digital transformation readiness among micro, small, and medium enterprises (MSMEs) varies across business sectors and organizational capabilities. This study develops a supervised classification model to predict MSME digital transformation readiness for data-driven decision support. Target labels were constructed from previous fuzzy clustering results and organized into three readiness levels: low, moderate, and high. The predictive model was built using Random Forest with business type, workforce transformation, dynamic capability, and SME performance as key predictors. Data preprocessing included categorical encoding, train-test separation, and class imbalance handling applied only to the training data to avoid data leakage. Model evaluation on the hold-out set produced 91.40% accuracy, 91.36% macro precision, 92.16% macro recall, and 91.72% macro F1-score. The confusion matrix showed that 85 of 93 test observations were correctly classified, with most errors occurring between adjacent readiness levels. Feature importance analysis indicated that dynamic capability was the most influential predictor, followed by workforce transformation and SME performance. The findings demonstrate that Random Forest can transform clustering-based insights into a practical predictive model for prioritizing MSME assistance, training, and digital development programs.
Sosialisasi Pengelolaan Sampah melalui Aplikasi Bank Sampah di Desa Manggihan Kecamatan Getasan Kabupaten Semarang Andi Riansyah; Bagus Satrio Waluyo Poetro; Iven Aurananta Damaivila
Indonesian Journal of Community Services Vol 8, No 1 (2026): May 2026
Publisher : LPPM Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/ijocs.8.1.74-82

Abstract

Permasalahan pengelolaan sampah di pedesaan masih menjadi isu penting, khususnya di Desa Manggihan, Kecamatan Getasan, Kabupaten Semarang. Sampah rumah tangga yang tidak terkelola dengan baik menimbulkan pencemaran lingkungan dan menurunkan kualitas kesehatan masyarakat. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk memperkenalkan dan mengimplementasikan aplikasi Bank Sampah sebagai inovasi manajemen pengelolaan sampah berbasis digital. Aplikasi ini dirancang untuk membantu masyarakat dalam memilah, mencatat, dan mengelola sampah rumah tangga secara lebih terstruktur dan transparan. Metode pelaksanaan meliputi observasi lapangan, diskusi kelompok terarah, sosialisasi, pelatihan penggunaan aplikasi, serta monitoring keterlibatan masyarakat. Hasil kegiatan menunjukkan adanya peningkatan kesadaran warga dalam memilah sampah, ditandai dengan keterlibatan rumah tangga yang mulai aktif berpartisipasi dalam pencatatan setoran melalui aplikasi untuk mendukung pengelolaan sampah. Kehadiran karang taruna sebagai fasilitator lokal turut mendukung keberhasilan implementasi dengan membantu warga beradaptasi terhadap teknologi. Implikasi dari kegiatan ini adalah terciptanya sistem pencatatan yang lebih akuntabel, peningkatan partisipasi masyarakat, serta terbentuknya model pengelolaan sampah berbasis komunitas yang dapat direplikasi di desa lain.Waste management in rural areas remains a significant issue, particularly in Manggihan Village, Getasan District, Semarang Regency. Improperly managed household waste contributes to environmental pollution and decreases public health quality. This Community Service Program (PkM) aimed to introduce and implement a Waste Bank mobile application as a digital innovation for household waste management. The application was designed to assist the community in sorting, recording, and managing waste in a more structured and transparent manner. The implementation methods included field observation, focus group discussions, socialization, training on application use, and monitoring of community participation. The results showed an increase in community awareness of waste sorting, indicated by households that began to actively participate in recording their deposits through the application to support waste management activities. The involvement of local youth organizations (karang taruna) also contributed to the success of the program by assisting residents in adapting to the technology. The implications of this program include the establishment of a more accountable recording system, increased community participation, and the development of a community-based waste management model that can be replicated in other villages.
Implementasi Teknologi Tepat Guna dan Strategi Digital Marketing untuk Peningkatan Kapasitas Produksi dan Omset UMKM Kopi Boyo Jepara Akhmad Syakhroni; Muhammad Sagaf; Andi Riansyah
Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Vol. 7 No. 1 (2026): Juli 2026
Publisher : Fakultas Teknik Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/94mt9z65

Abstract

This Community Service Program aims to empower the coffee MSME "VINZOEI" located in Sumanding Village, Kembang Sub-district, Jepara Regency, which has significant potential in the coffee plantation sector. The main problems faced by the partner include dependence on third-party services for coffee roasting, limited use of digital marketing, and unattractive product packaging. This program offers solutions through the application of coffee roasting machine technology to improve production efficiency and quality, internet marketing training to expand market reach, and the development of new, more appealing packaging designs to enhance product value. The program activities include socialization, training, technology implementation, mentoring, and periodic evaluations. This initiative aligns with the goals of the SDGs and ASTA CITA, and supports the achievement of key university performance indicators (IKU). It is expected that this program will help the partner increase production capacity, expand marketing coverage, and sustainably improve business assets and revenue.
Deep neural network classification in chatbot system family health counseling services Andi Riansyah; Sam Farisa Chaerul Haviana; Ratna Supradewi; Muhammad Ainul Wahib
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i2.pp1211-1218

Abstract

Mental health problems affect many aspects of life, including physical well being, work productivity, social functioning, and suicide risk. In Indonesia, access to professional mental health services remains very limited: only a small proportion of people with depression receive treatment and the number of mental health professionals per population is far below international recommendations, creating an urgent service gap. This study proposes an artificial intelligence–based chatbot to support family mental health counseling services in Indonesia. The chatbot uses a deep neural network (DNN) to classify user questions into counseling intent categories and to provide appropriate responses. Psychologists compiled and verified a dataset of Indonesian counseling questions and responses, which was then pre processed using standard text processing techniques and encoded with a bag of words (BoW) representation. A fully connected DNN with one input layer, two hidden layers of eight neurons each, and a SoftMax output layer was trained using the Adam optimizer (learning rate 0.01) on 80% of the data and evaluated on the remaining 20%. The best configuration achieved a training accuracy of 96%, with test results of 93% accuracy, 92% precision, 93% recall, and 92% F1-score. These findings indicate that proposed DNN based chatbot can accurately classify counseling intents and generate contextually appropriate responses, suggesting its potential as complementary tool to support initial family mental health counseling in Indonesia.
TRANSFORMASI PERTANIAN BERKELANJUTAN MELALUI SMART HYDROPONIC FARMING DAN GREEN ENERGY DI DESA KEDUNGCINO KABUPATEN JEPARA Rieska Ernawati; Jenny Putri Hapsari Hapsari; Safrizal Safrizal; M Sagaf; Muhammad Irfan; Candra Setiawan; Andi Riansyah
BHAKTI NAGORI (Jurnal Pengabdian kepada Masyarakat) Vol. 5 No. 2 (2025): BHAKTI NAGORI (Jurnal Pengabdian kepada Masyarakat) Desember 2025
Publisher : LPPM UNIKS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/bhakti_nagori.v5i2.5099

Abstract

Smart farming merupakan pendekatan pertanian modern yang mengintegrasikan teknologi digital, Internet of Things (IoT), otomatisasi, serta energi terbarukan untuk meningkatkan produktivitas dan efisiensi pengelolaan lahan. Transformasi ini menjadi sangat penting mengingat tantangan sektor pertanian saat ini, seperti perubahan iklim, keterbatasan lahan, fluktuasi harga energi, serta meningkatnya kebutuhan pangan akibat pertumbuhan penduduk. Oemahku hydrofarm menghadapi masalah kesulitan monitoring suhu, kelembaban dan nutrisi serta minimnya pasokan listrik saat memproduksi selada hidroponik. Kegiatan ini bertujuan mengembangkan model implementasi smart farming terpadu yang mampu menjawab permasalahan tersebut melalui pengembangan sistem monitoring lingkungan, manajemen nutrisi otomatis, dan penggunaan energi surya sebagai sumber daya utama. Metode pengabdian dilakukan melalui perancangan IoT, pemilihan sensor lingkungan (pH, TDS, suhu, kelembaban), integrasi perangkat kontrol berbasis mikrokontroler, serta penyusunan dashboard pemantauan berbasis aplikasi Android. Selain itu, dilakukan evaluasi performa sistem terhadap konsumsi energi, pertumbuhan tanaman, stabilitas nutrisi, serta produktivitas hasil panen selama satu siklus budidaya. Hasil pengabdian menunjukkan bahwa penerapan smart farming mampu menurunkan penggunaan air hingga 38% melalui sistem irigasi presisi, meningkatkan pertumbuhan tanaman sebesar 22% akibat kestabilan nutrisi serta menurunkan ketergantungan terhadap listrik PLN sebesar 65% berkat integrasi photovoltaic. Selain itu, pemantauan real-time melalui IoT terbukti meningkatkan akurasi pengambilan keputusan petani, mengurangi kesalahan manual, dan meningkatkan kontinuitas produksi. Dengan demikian, model smart farming yang dikembangkan dalam pengabdian ini terbukti efektif, efisien, dan relevan untuk diterapkan pada sistem pertanian modern, khususnya bagi pelaku UMKM pertanian yang membutuhkan solusi adaptif dan berkelanjutan.
Pemberdayaan Tentor Lembaga Bimbingan Belajar Tanjungharjo Grobogan melalui Pengembangan Learning Object Material Berbasis Artifial Intelligence Mochamad Abdul Basir; Jupriyanto Jupriyanto; Andi Riansyah; Mohamad Aminudin
KOMUNITA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 5 No 1 (2026): Februari
Publisher : PELITA NUSA TENGGARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60004/komunita.v5i1.417

Abstract

Modern technology has created significant opportunities for enhancing personalization in learning, particularly through the utilization of data analytics and artificial intelligence, which enable the customization of learning products based on students’ needs, levels of understanding, and learning styles. This condition requires educators and tutoring instructors to possess adequate digital skills in order to produce instructional materials that are relevant, adaptive, and easily accessible. Responding to this need, this community service program was designed to provide training and assistance in developing digital-based learning products for tutors at the AURORA Tutoring Institute in Grobogan Regency, Central Java. The program was implemented through four stages: socialization, training, mentoring, and monitoring and evaluation. The training consisted of two main sessions: (1) multimedia production through the development of PowerPoint materials assisted by artificial intelligence and the recording of instructional content, and (2) training in managing a Learning Management System using Google Classroom. A total of 10 tutors participated in the entire series of activities. The evaluation results indicate an improvement in participants’ digital competencies, evidenced by all tutors (100%) being able to produce learning multimedia that is more engaging, interactive, flexible, and ready for use in tutoring sessions. This program demonstrates that structured training interventions can effectively enhance the quality of learning digitalization within tutoring institutions.
Applying fuzzy Tsukamoto method to improve production efficiency in manufacturing industry Moch Taufik; Andi Riansyah; Muhammad Qomaruddin; Muhammad Sholahuddin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i1.pp356-364

Abstract

Manufacturing can increase competitiveness and reduce costs by improving production efficiency. The study’s goal is to develop a production prediction system using the fuzzy Tsukamoto technique. This method is used to model the uncertainty that occurs during the production process. Thus, production planning based on demand and inventory availability can be more accurate. After being tested on production data from a manufacturing company, the fuzzy Tsukamoto method showed the ability to make more efficient decisions than conventional methods. This system not only significantly reduces production costs but also improves overall operational efficiency, including resource management, waste reduction, and cycle time optimization. The adoption of this method provides added value to companies in facing increasing market competition while keeping production costs low without compromising quality.
Co-Authors Ahmad Mujib Ahmad Syarif Hidayatullah Ahmad Tri Yulianto Akhmad Syakhroni Alamsyah Alamsyah Almahdi, Bardad Andhika Bayu Pratama Asep Hernandi Badieah Assegaf Basir, Mochamad Abdul Candra Setiawan Damaivila, Iven Aurananta Dedy Kurniadi Dewi Ayu Fatmawati Eka Nuryanto Budi Susila Fajarini, Intan Putri Nur Febrian Rio Hartono Ghufron ghufron, ghufron Hermawan, Hildan Mulyo Hidayat, Ilham Ida Widihastuti Imam Much Ibnu Subroto Iven Aurananta Damaivila Jenny Putri Hapsari Hapsari Jupriyanto . Lailatul Fitriyah Lilis Nuryawai M Sagaf M. Roichani M. Sagaf Maulana Ahmad Widiarta Maulida, Aina Nurul Maya Indriastuti Maya Indriastuti Moch Taufik Moch Taufik Mohamad Aminudin Muhammad Ainul Wahib Muhammad Irfan Muhammad Khosyi in Muhammad Ni’am Muhammad Qomaruddin Muhammad Rahman Hakim Muhammad Sagaf Muhammad Sholahuddin Muhammad Wahyu Syaiful Anaam Muna Madrah Muna Yastuti Madrah Munaf Ismail Munir, Abdulloh Mutamimah Mutamimah Mutamimah Mutamimah Nur Muhammad Syaifuddin Nur'aini, Intan Poetro, Bagus Satrio Waluyo Pratama, Nirmala Putri Randy Ilhamzah Ratna Supradewi Ratna Supradewi Rieska Ernawati Saadah, Farikhatus Safrizal Safrizal Sam Farisa Chaerul Haviana Sapto Utomo Sri Mulyono Sri Mulyono Suyanto Suyanto Syakhroni, Akhmad Vergiawan Alfiansyah Wirastama, Dimas Surya Yusuf Arief Wicaksono