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All Journal JITEK (Jurnal Ilmiah Teknosains) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal SOLMA Jusikom : Jurnal Sistem Komputer Musirawas JUTIM (Jurnal Teknik Informatika Musirawas) J-Dinamika: Jurnal Pengabdian Kepada Masyarakat JUSIM (Jurnal Sistem Informasi Musirawas) Jurnal Tekno Kompak Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Nasional Ilmu Komputer Jurnal Pengembangan Sistem Informasi dan Informatika Journal of Soft Computing Exploration LOSARI: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat (ABDIRA) Jurnal Abdi Masyarakat Indonesia Ngabdimas : Pengabdian Pada Masyarakat Society: Jurnal Pengabdian Masyarakat Informatics and Enginering Dedication Knowbase : International Journal of Knowledge in Database Ngabdimas Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Syahri, Riduan
Institut Teknologi Pagar Alam
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Nursing Public Health Social Sciences Transportation Veterinary Other

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PELATIHAN PEMASARAN DIGITAL BERBASIS MEDIA SOSIAL UNTUK PENGUATAN KAPASITAS KELOMPOK TANI SEHASE I Puspita, Desi; Syahri, Riduan; Putrawansyah, Ferry
FORDICATE Vol 4 No 2 (2025): April 2025
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v4i2.11478

Abstract

This community service activity aims to increase the capacity of the Sehase 1 Farmer Group in terms of marketing agricultural products through the use of social media. In today's digital era, social media is an effective and efficient means to promote products widely without geographical limitations. The methods used in this activity include training, mentoring, and evaluation of the use of social media platforms such as Instagram, Facebook, and Tiktok. The indicator of the success of the assistance activity for processing chilies into chili powder is by measuring before (pre-test) and after (post-test) the extension with the level of knowledge and skills of participants in terms of making and benefits of chili powder and the quality of chilies in the long term. The results obtained were a high increase in farmer knowledge and skills with a percentage level of 98.83% in the high category. The results of the activity showed an increase in the knowledge and skills of farmer group members in creating digital content and managing social media accounts professionally
Classification Of Outstanding Students Using Support Vector Machine (SVM) Based on Data Mining Riduan Syahri; Desi Puspita
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.13191

Abstract

This research aims to classify outstanding students at the Pagar Alam Institute of Technology using the Support Vector Machine (SVM) algorithm based on data mining. Early identification of outstanding students is crucial for supporting potential development and institutional decision-making. Historical data from 245 students from the 2016 to 2018 cohorts were utilized, encompassing course grades and Cumulative Grade Point Average (CGPA). The research process included data preprocessing such as normalization and splitting the data into 80% training data and 20% testing data. The SVM model was implemented with a Radial Basis Function (RBF) kernel and parameters C=1.0 and gamma=0.1. Evaluation results show that the model achieved an overall accuracy of 89.80% on the testing data. The model's performance was further validated through a confusion matrix (9 True Positives, 1 False Negative) and a classification report indicating good precision and recall for both classes. Furthermore, an Area Under the Curve (AUC) value of 0.93 signifies the model's excellent discriminative ability. This study contributes by providing an effective classification tool for identifying outstanding students, which can serve as a basis for the institution to design more targeted development and recognition programs.
SISTEM PAKAR DIAGNOSA STUNTING BALITA MENGGUNAKAN NAIVE BAYES Andayani, Mastra; Putrawansyah, Ferry; Syahri, Riduan
Jusikom : Jurnal Sistem Komputer Musirawas Vol 10 No 1 (2025): Jusikom : Jurnal Sistem Komputer Musirawas JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusikom.v10i1.2649

Abstract

This study aims to develop an expert system to diagnose stunting in toddlers using the naive bayes method. Stunting is a serious health problem that is often ignored due to lack of public awareness and limited access to health services. This expert system is designed to diagnose stunting based on symptoms inputted by the user without having to consult directly with medical personnel. The naive bayes method is used to handle uncertainty in the data and provide a level of certainty in the diagnosis. Research data were obtained through observation, interviews with medical personnel at the Health Office, and literature studies. This system was developed using the PHP programming language and MySQL database, and tested using the blackbox testing technique. This system is expected to increase awareness and early detection of stunting, while supporting the Health Office in its efforts to reduce the prevalence of stunting.
Penerapan Algoritma C4.5 Untuk Prediksi Anak Stunting Di Kota Pagar Alam Hakim, Revaldo Xsanal; Putrawansyah, Ferry; Syahri, Riduan
Jurnal Tekno Kompak Vol 18, No 2 (2024): AGUSTUS
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtk.v18i2.4078

Abstract

Di Pagar Alam, Prediksi dan pengukuran tingkat Stunting masih mengandalkan analisis sekunder. Kader Posyandu melibatkan diri dalam mengukur kondisi balita, dan hasilnya diserahkan kepada ahli untuk menilai apakah balita tersebut mengalami Stunting atau tidak. Tujuan dari penelitian ini adalah mengaplikasikan Algoritma C4.5 untuk melakukan Prediksi terkait kasus Stunting pada anak. Dari permasalahan yang ada diatas, maka metode yang dapat menyelesaikan permasalahan ini yaitu Algoritma C4.5 yang termasuk dalam Pohon Keputusan pada Data Mining. Proses Data Mining peneliti menggunakan salah satu metode CRIPSP-DM dan pengujian Data Mining menggunakan Confusion Matrix serta pengujian Sistem menggunakan Black Box Testing. Hasil dalam penelitian ini berupa sebuah Sistem yang menerapkan aturan dari Pohon keputusan. Sistem Prediksi status gizi Anak yang dirancang penulis layak karena dapat mengkategorikan status gizi balita. balita secara otomatis berdasarkan Zscore yang ditetapkan dan hanya terdapat selisih 11,8% dari pengujian Prediksi dataset yang sama menggunakan Rapid Miner. Sistem yang penulis rancang dapat lebih cepat dan efektif dalam memPrediksi status gizi Anak. Berdasarkan Berdasarkan data hasil uji, dapat disimpulkan bahwa akurasi Algoritma C.4.5 untuk memPrediksi anak Stunting yaitu 88,20% tergolong baik. Sedangkan pengujian Sistem menggunakan Black Box Testing memperoleh total 4.35 masuk ke kategori sangat layak. Tujuan Sistem ini adalah membantu tenaga kesehatan dalam membuat keputusan terkait Prediksi status gizi balita. Sistem Prediksi ini bermanfaat untuk mengidentifikasi balita berisiko gizi buruk sehingga tindakan pencegahan dapat dilakukan dengan lebih efektif.
Optimalisasi Kader Posyandu Kelurahan Bangun Rejo Pembuatan Produk Makanan Tambahan Seblak (Sehat, Bergizi, Lahap, Enak) Putrawansyah, Ferry; Syahri, Riduan; Padya, Inka Rizki
Jurnal Pengabdian Masyarakat (ABDIRA) Vol 5, No 4 (2025): Abdira, Oktober
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdira.v5i4.1147

Abstract

The provision of supplementary feeding at community health posts aims to support adequate nutrition for toddlers. However, limited government funding poses challenges for posyandu cadres. To overcome this, cadres conduct self-funding initiatives, even though most of them are housewives. This community service activity aims to assist cadres in developing a provision of supplementary feeding production enterprise through education, capital support, and business mentoring. The stages include preparing health media, conducting health education, forming a management team, producing provision of supplementary feeding, and evaluating business progress. The activity involved 12 cadres from Bangun Rejo Village. The results showed increased knowledge among cadres in producing nutritious, locally sourced provision of supplementary feeding, along with improvements in toddlers’ nutritional status: severe malnutrition decreased from 25% to 10%, moderate malnutrition from 75% to 50%, and good nutrition increased from 0% to 40%. This demonstrates that PMT effectively improves toddlers’ nutrition.
SISTEM PENDUKUNG KEPUTUSAN REKOMENDASI HOMESTAY DI KOTA PAGAR ALAM DENGAN METODE TOPSIS Masdalipa, Risnaini; Setiadi, Dedi; Syahri, Riduan
(JITEK)Jurnal Ilmiah Teknosains Vol 9, No 2/Nov (2023): JiTek
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jitek.v9i2/Nov.17247

Abstract

Technological developments can be used appropriately and properly will provide benefits and facilitate human work. The decision support system is an information system that can be used to assist in decision making, in this case, namely providing homestay recommendations to tourists who will visit the city of Pagar Alam which is a tourist destination in South Sumatra. Tourists who will stay at homestays must come directly to several homestays to ask about the rental price and facilities provided by the homestay manager. Sometimes people who are looking for a homestay don't immediately match the homestay they are visiting, so they have to find another homestay that is suitable and in accordance with the available budget so that this situation is not optimal, because the process for people to find a suitable homestay can take a long time. The method used is Technique for Order of Preference by Similiarty to Ideal Solution, which is a method for solving Multi Attribute Decision Making problems. The system development uses the Rapid Application Development (RAD) method, which is a process model used in incremental software development, especially for short processing times, which consists of three stages, namely requirements planning, design workshop, implementation. From the calculation results of the TOPSIS method with four criteria determined for several alternatives, according to the selection of criteria by the user, as well as the results of ranking alternatives with the highest preference value, namely 0.5962, and kia homestay as a recommendation according to what is expected by the user.
KLASIFIKASI PENGUNJUNG WISATA DI KOTA PAGAR ALAM DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR (K-NN) Syahri, Riduan; Puspita, Desi
(JITEK)Jurnal Ilmiah Teknosains Vol 9, No 2/Nov (2023): JiTek
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jitek.v9i2/Nov.17329

Abstract

The city of Pagar Alam has many beautiful tourist options, fresh and cold air, and unique culture and culinary delights. So that it becomes an area that is visited by many local and foreign tourists. Of the many visitors who come, not a few of them leave impressions in the form of reviews of the places they have visited. The purpose of this study is to determine the classification and to determine the accuracy produced by the K-Nearest Neighbor (K-NN) method. The K-Nearest Neighbor (K-NN) method is used to classify visitor data on Pagar Alam tours. Tests carried out to get good accuracy results and evaluate using a confusion matrix. This research produces a classification system that can identify and classify Pagar Alam tourism visitors using the K-Nearest Neighbor (K-NN) algorithm with the results obtained the greatest accuracy with a value of k = 3 with 99% accuracy, K0 gets 98% precision, recall 100 and a fi-score of 99%, for k1 precision 100%, the recal is 89% and the fi-score is 92%, while for K2 the precision is 100%, the recal is 100%, the f1-score is 100%.
Integration of Machine Learning and Web-Based Expert Systems for Diabetes Risk Analysis in Pagar Alam Syahri, Riduan; Puspita, Desi; Masdalipa, Risnaini
Knowbase : International Journal of Knowledge in Database Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v5i2.10268

Abstract

This study aims to develop an integrated system combining Machine Learning (ML) and a Web-Based Expert System for genomic and clinical data analysis to mitigate the rising diabetes cases in Pagar Alam City. The research adopts the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology, encompassing business understanding, data understanding, data preparation, modeling, evaluation, and deployment phases. Unlike previous studies relying on standard public datasets, this research integrates genomic profiles (TCF7L2 and KCNQ1 SNPs) alongside local clinical parameters from five sub-districts in Pagar Alam. Quantitative data from 640 samples were analyzed using the Support Vector Machine (SVM) algorithm. Evaluation results during the modeling phase show that the SVM model achieved a superior accuracy of 99.07%, demonstrating that integrating genomic data significantly enhances predictive precision. The web-based expert system implemented in the deployment phase provides personalized prevention recommendations based on individual risk profiles. This application is expected to serve as a strategic tool for the Pagar Alam government to enhance the effectiveness of prevention programs through localized and genetic-based interventions.
Pelatihan dan Implementasi Smart Sewing Machine (SSM) Guna Peningkatan Efisiensi Produksi dan Pengurangan Waste Kain pada Komunitas Penjahit Kriya Wanita Syahri, Riduan; Edowinsyah; Alfis Arif
LOSARI: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2025): Desember 2025
Publisher : LOSARI DIGITAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53860/losari.v7i2.536

Abstract

Textile waste is one of the largest contributors to solid waste, requiring innovative handling. Community partners, especially tailors and recycling activists, often face challenges in production efficiency, waste management, and digital market access. This community service aims to address these challenges through comprehensive training and technology utilization. The method employed involves training, mentoring, and hands-on practice focusing on three main aspects: 1) Textile Waste Utilization using creative upcycling techniques, 2) Simple Business Management to enhance business sustainability, and 3) Digital Marketing for recycled products. The main innovation in this activity is the introduction and practice of using SSM (Smart Sewing Machine), which can significantly increase the speed and precision of recycled product production. The results show a significant improvement in partners' technical skills in processing textile waste into economically valuable products, increased understanding of financial and inventory management, and expanded market access through digital platforms. This training successfully transformed the perception of textile waste into a sustainable business opportunity. It is hoped that this activity can serve as a model for both waste reduction and sustainable income generation for the community
Co-Authors Abdi NAsrullah Alfis Arif Andayani, Mastra Arie Yandi Saputra Buhori Muslim Debi Guzmaliza Dedi Setiadi Dedi Setiadi Desi Puspita Desi Puspita Edowinsyah Efan Ferry Putrawansyah Ferry Putrawansyah, Ferry Gusmaliza, Debi Hakim, Revaldo Xsanal Ichsan, Onne Akbar Nur Masdalipa, Risnaini Padya, Inka Rizki Puspita, Desi Rahmayati, Desy Sari, Pita Tri Cahaya, Della Tri Susanti Xsanal Hakim, Revaldo Zulkipli Zulkipli