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All Journal Prosiding SNATIF JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Informatika Universitas Pamulang GUYUB: Journal of Community Engagement RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Jurnal Informasi Pengabdian Masyarakat Nusantara Journal of Computers and its Applications Jurnal Riset Sistem dan Teknologi Informasi Aspirasi : Publikasi Hasil Pengabdian dan Kegiatan Masyarakat Abhakte
sudriyanto sudriyanto
Universitas Nurul Jadid
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Other

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Pelatihan Pemanfaatan Aplikasi Google Drive dan Google Form Sebagai Instrumen Evaluasi Hasil Belajar Siswa bagi Guru Madrasah Ibtidaiyah Raudlatul Mutaallimin Sudriyanto Sudriyanto; Novi Fitriani; Dinda Lailatul Qomariyah; Wiwik Widianti
ASPIRASI : Publikasi Hasil Pengabdian dan Kegiatan Masyarakat Vol. 1 No. 6 (2023): November : ASPIRASI : Publikasi Hasil Pengabdian dan Kegiatan Masyarakat
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/aspirasi.v1i6.89

Abstract

Education is a key element in the development of society and the nation. Madrasah Ibtidaiyah Raudlatul Mutaallimin Pandean Paiton Probolinggo faces challenges in evaluating student learning outcomes during distance learning. Technological limitations have prompted the search for innovative solutions. The goal of this service effort is to improve the quality of student learning outcome evaluations by utilizing Google Drive and Google Form applications in distance learning. Teachers are empowered through intensive training, workshops, and mentoring, including the use of Google Drive and Google Form in teaching and evaluation question development techniques. Active interaction and knowledge sharing occur during training, which has successfully enhanced teachers' knowledge and skills in creating evaluation instruments with Google Form. The final survey results show a significant improvement, with 87% of respondents experiencing improvement. They are now able to design evaluation instruments more effectively during distance learning. The use of Google Drive and Google Form as evaluation tools opens up opportunities for improving the quality of education. Recommendations for the future include continuing to support teachers, deepening the integration of technology in the learning process, and expanding training to enhance the effectiveness of learning at Madrasah Ibtidaiyah Raudlatul Mutaallimin Pandean Paiton Probolinggo..
Clustering Loyalitas Pelanggan Menggunakan Algoritma K-Means Berbasis Web Shafarina Aprilia, Diva; Sudriyanto; Moh Jasri
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 6 (2024): RESOLUSI July 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i6.2039

Abstract

Active customer engagement in transactions with the company significantly impacts profitability. Categorizing customer data into loyal and non-loyal segments is a common method to identify loyalty patterns. The results of this segmentation can guide companies in designing follow-up strategies, including tailored incentives based on customer loyalty levels. Implementing a web-based K-Means Clustering algorithm allows PT Bhara Utama's management to easily access customer segmentation results, speeding up data analysis and enhancing decision-making efficiency. The use of web technology also facilitates integration with existing information systems and provides more flexible access. An experiment conducted on 660 customer data resulted in three groups: 8 very loyal customers, 461 moderately loyal customers, and 191 non-loyal customers. Accuracy evaluation using the Davies-Bouldin Index (DBI) showed a value of 0.19, indicating high-quality clusters.
Pelatihan Penggunaan Microsoft Office Bagi Siswa MA Nurul Jadid Paiton Probolinggo Sudriyanto Sudriyanto; Mochammad Faid; Moh Sukron; Ahmad Supriadi
Jurnal Informasi Pengabdian Masyarakat Vol. 1 No. 2 (2023): Mei: Jurnal Informasi Pengabdian Masyarakat
Publisher : Institut Nalanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47861/jipm-nalanda.v1i2.396

Abstract

This research aims to assess the effectiveness of Microsoft Office training for students of Madrasah Aliyah (MA) Nurul Jadid in Paiton, Probolinggo. The training was chosen due to the importance of enhancing digital literacy and computer skills for students in an era heavily reliant on technology. The community engagement methods employed include lectures, demonstrations, and hands-on exercises conducted by the participants. The research results indicate a positive impact on improving the knowledge and skills of participants in the good category, increasing by 64.42%. However, challenges were observed among participants in the fair and poor categories, experiencing respective declines of 5.45% and 58.96%. These reductions highlight the need to reinforce the program with more varied methods and a personalized approach. Additionally, leveraging technology to facilitate interactive learning is essential to ensure that the benefits of the training can be equally felt by all participants. For further development, program enhancements are necessary to utilize more diverse methods and adopt a personal approach. The integration of technology can be harnessed to create a more interactive learning environment, fostering motivation and ensuring that the training's benefits are equally distributed among all participants. Thus, this research provides valuable insights for future training implementations, enabling a more effective approach to enhancing digital literacy and computer skills for students of Madrasah Aliyah Nurul Jadid in this rapidly advancing technological era.
Empowering Gen-Z: Pelatihan Digital Marketing Berbasis AI untuk Siswa SMK Nurul Jadid Paiton Probolinggo Sudriyanto Sudriyanto; Kamil Malik; Jamal Jamal
Abhakte Jurnal Pengabdian Kepada Masyarakat Vol 3 No 1 (2025): ABHAKTE
Publisher : Fakultas Sosial dan Ilmu Politik Universitas Wiraraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24929/abhakte.v3i2.4140

Abstract

The rapid development of digital technology requires the younger generation, especially vocational high school students, to have skills in digital-based marketing. However, many students still do not understand and master effective digital marketing strategies, especially those that utilize artificial intelligence (AI). Therefore, this community service activity aims to improve the understanding and skills of SMK Nurul Jadid Paiton Probolinggo students in AI-based digital marketing. The training was carried out through lecture methods, interactive discussions, and direct practice using various AI tools for digital marketing. Evaluation was carried out through pre-tests and post-tests to measure the effectiveness of the training. The results of the implementation showed a significant increase in student understanding and skills. The average pre-test score of 62.3 increased to 85.7 in the post-test, indicating the effectiveness of the practice-based learning approach. In addition, students were able to implement digital marketing strategies independently in business simulation projects. This activity not only provides short-term benefits but also contributes to students' readiness to face competition in the digital industry. As a follow-up, further mentoring and integration of materials into the school curriculum are recommended to ensure the sustainability of the benefits of this program.
PKM Pelatihan Digital Marketing untuk Peningkatan Kompetensi Gen Z di Era Ekonomi Digital Sudriyanto Sudriyanto; Achmad Andri Yudiono; Andi Wahyudi; Sutrisno Sutrisno
Abhakte Jurnal Pengabdian Kepada Masyarakat Vol 3 No 2 (2025): ABHAKTE
Publisher : Fakultas Sosial dan Ilmu Politik Universitas Wiraraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24929/abhakte.v3i2.4714

Abstract

Perkembangan ekonomi digital menuntut generasi muda, khususnya Generasi Z, untuk memiliki kompetensi dalam mengoptimalkan teknologi digital secara produktif. Namun, kondisi nyata menunjukkan masih rendahnya literasi digital serta keterampilan teknis Generasi Z dalam memanfaatkan media sosial untuk tujuan pemasaran dan personal branding. Menjawab permasalahan tersebut, kegiatan pengabdian kepada masyarakat ini dilaksanakan bersama mitra PT. Poter Teknik Nusantara melalui program pelatihan digital marketing yang dirancang secara sistematis dan aplikatif. Tujuan kegiatan ini adalah meningkatkan pemahaman Generasi Z terhadap konsep dasar pemasaran digital, membekali mereka dengan keterampilan teknis dalam pembuatan konten kreatif, serta menumbuhkan kesadaran akan pentingnya pemanfaatan media sosial untuk pengembangan potensi diri dan usaha mandiri. Metode pelaksanaan meliputi penyusunan modul pelatihan, sosialisasi dan pre-test, pelaksanaan pelatihan dengan pendekatan hands-on learning, praktik mandiri peserta berupa proyek kampanye digital, serta evaluasi melalui perbandingan hasil pre-test dan post-test. Hasil kegiatan menunjukkan peningkatan yang signifikan pada pemahaman peserta dengan rata-rata peningkatan lebih dari 70% serta lahirnya karya kreatif digital yang dipublikasikan di media sosial. Manfaat kegiatan ini tidak hanya meningkatkan literasi digital individu, tetapi juga membuka peluang terbentuknya generasi muda yang adaptif, kompetitif, dan berkontribusi dalam mendukung ekosistem ekonomi digital di tingkat lokal maupun nasional.
Bapak Analisis dan Prediksi Diabetes Menggunakan Artificial Neural Network dengan Dataset CDC Diabetes Health Indicators : Analisis dan Prediksi Diabetes Menggunakan Artificial Neural Network dengan Dataset CDC Diabetes Health Indicators Dodi Dwi Riskianto Dwi; Muhammad Afandi; M. Raihan Ramadhan; Sudriyanto Sudriyanto
Jurnal Riset Sistem dan Teknologi Informasi Vol. 4 No. 1 (2026): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v4i1.2096

Abstract

Diabetes mellitus is a chronic disease with increasing prevalence and requires effective early detection efforts. This study aims to develop a diabetes risk prediction model using an Artificial Neural Network (ANN) based on non-laboratory health indicators. The dataset used is the CDC Diabetes Health Indicators with a large amount of data and characteristics of classes that are not fully balanced. The research stages include data preprocessing that includes handling missing values, encoding categorical data using one-hot encoding, normalization of numerical features, and analysis of the target class distribution. The ANN model was trained using a Multilayer Perceptron architecture with dropout regularization and L2 penalty and AdamW optimization. The evaluation results show that the model achieved an accuracy of 86.45%, a precision of 85.2%, a recall of 82.7%, and an AUC-ROC value of 0.89. Although the accuracy is in the medium range for a large dataset, the high AUC value indicates excellent model discrimination ability. This performance is affected by the limited number of non-laboratory features used and the imbalanced class distribution. The findings of this study indicate that ANN based on simple health indicators has the potential to be used as a diabetes risk screening tool in primary healthcare. Further research is recommended to apply class balancing techniques, model interpretability analysis, and external validation in the Indonesian population.
Bapak Prediksi Depresi Mahasiswa Menggunakan Algoritma Random Forest Berbasis Data Psikososial Depression Prediction Among University Students Using a Random Forest Algorithm Based on Psychosocial Data : Prediksi Depresi Mahasiswa: Pendekatan Berbasis Data Psikososial Menggunakan Algoritma Random Forest Abiyya Alfahrizi Putra Arifiansyah Abiyya; Muhammad Afandi; Dodi Dwi Riskianto; Sudriyanto Sudriyanto
Jurnal Riset Sistem dan Teknologi Informasi Vol. 4 No. 1 (2026): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA)
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v4i1.2100

Abstract

College students' mental health is a critical issue that is gaining increasing attention, particularly regarding depression, which significantly impacts quality of life and academic achievement. This study aims to develop a predictive model for depression in college students based on psychosocial data using the Random Forest algorithm. The data used is a public secondary dataset from Kaggle with 1,000 samples, covering demographic variables, lifestyle, and psychological indicators. The analysis process included data preprocessing, class balancing, model training, and evaluation using accuracy, precision, recall, F1-score, and confusion matrix metrics. Test results showed that the Random Forest model was able to predict depression with 87.0% accuracy, 86.1% precision, 87.4% recall, and 86.7% F1-score, demonstrating good and stable performance. Word cloud visualization identified academic pressure, stress, and anxiety as dominant factors. Compared to previous research using the SVM algorithm, Random Forest demonstrated improved performance, particularly in handling complex and imbalanced data. This study confirms the effectiveness of the Random Forest-based machine learning approach in supporting the early detection of college students' depression and provides a foundation for the development of mental health monitoring systems in higher education settings.
Co-Authors Abiyya Alfahrizi Putra Arifiansyah Abiyya Achmad Andri Yudiono Ahmad Khairi ahmad supriadi Andi Wahyudi Atoillah Shohibul Hikam Dinda Lailatul Qomariyah Dodi Dwi Riskianto Dodi Dwi Riskianto Dwi Isti Ghulam Hidayatullah Jamal Jamal Kamil Malik M. Ainun Rofiq Hariri M. Alman David M. Fajar Santoso M. Lukman Hakim M. Raihan Ramadhan Maulidiansyah Maulidiansyah mochammad faid Moh Ahsan Al Maliki Moh Furqan Moh Jasri Moh Novi Hermawan Moh Sukron Muhammad Afandi Muhammad Riyan Ulil Albab Novi Fitriani Putri Tsamrotul Fu’adiyah Rudi Rizaldi Shafarina Aprilia, Diva Siti Aisyah Sukma Agung Adi Luwih Sutrisno Sutrisno Syamsul Arifin Wahab Sya’roni Wahyu Pratama Mukti Wakiludinil Hasan Wiwik Widianti Yaqin, Moh. Ainol