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All Journal Dinamik Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA JURIKOM (Jurnal Riset Komputer) JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Sistem Informasi dan Informatika (SIMIKA) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jutsi: Jurnal Teknologi dan Sistem Informasi Journal of Social Responsibility Projects by Higher Education Forum KLIK: Kajian Ilmiah Informatika dan Komputer J-Com (Journal of Computer) Brilliance: Research of Artificial Intelligence Jurnal Ipteks Terapan : research of applied science and education International Journal of Management Science and Information Technology (IJMSIT) Jurnal Algoritma Digital Transformation Technology (Digitech) Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Journal of Applied Business and Technology Journal Of Indonesian Social Society Management of Information System Journal ITEJ (Information Technology Engineering Journals) Journal Computer Science and Applied Technology
William Ramdhan
Universitas Royal
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Analisis Metode Eoq untuk Mengoptimalkan Persediaan pada Sistem Rantai Pasok (Studi Kasus: Kaulamuda Coffee Space) Selly Tri Amanda; William Ramdhan; Chitra Latiffani
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10536

Abstract

Kaulamuda Coffee Space merupakan usaha kuliner yang menghadapi tantangan dalam pengelolaan persediaan bahan baku, di mana sering terjadi ketidakstabilan stok berupa kekurangan bahan (stockout) yang menghambat penjualan maupun penumpukan bahan (overstock) yang berisiko rusak. Penelitian ini bertujuan untuk mengatasi permasalahan tersebut dengan merancang sistem informasi Supply Chain Management (SCM) yang menerapkan metode Economic Order Quantity (EOQ). Metode EOQ digunakan untuk menganalisis dan menentukan jumlah pemesanan bahan baku yang paling ekonomis, titik pemesanan kembali (Reorder Point), dan persediaan pengaman (Safety Stock). Sistem ini dikembangkan berbasis web menggunakan bahasa pemrograman PHP dan database MySQL. Hasil dari penelitian ini adalah sebuah aplikasi manajemen persediaan yang mampu memberikan rekomendasi pengadaan bahan baku secara tepat jumlah dan tepat waktu. Penerapan sistem ini diharapkan dapat meminimalkan total biaya persediaan, meningkatkan efisiensi operasional, serta menjamin ketersediaan stok demi kelancaran proses produksi dan kepuasan pelanggan di Kaulamuda Coffee Space
Transfer Learning Model Evaluation on CNN Algorithm: Indonesian Sign Language System (SIBI) Deny Jollyta; Prihandoko Prihandoko; Johan Johan; William Ramdhan; Erick Santoso
Journal of Applied Business and Technology Vol. 6 No. 2 (2025): Journal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/jabt.v6i2.213

Abstract

In Indonesia as much as elsewhere, the deaf can communicate using sign language. The Indonesian Sign Language System (SIBI) is one of the sign language systems used in Indonesia. A model produced by the Convolutional Neural Network (CNN) method can be used in computer science for the recognition of sign language. By using the Transfer Learning paradigm, CNN's performance may be enhanced. However, not many researches have been conducted to assess the effectiveness of transfer learning on sign language models, particularly those that use the TensorFlow library. In fact, the evaluation results can influence the selection of the transfer learning model together with CNN. This study aims to evaluate the efficacy of using the CNN model for SIBI sign language through Transfer Learning. The data used are images of 24 SIBI alphabets and are processed through the TensorFlow library. The images will be recognized through the transfer learning performance of 6 models, namely VGG16, VGG19, Resnet50, Desenet121, Inception-V3 and MobileNet-V2. The results of the study found that through the TensorFlow library, Mobilenetv2 had the highest accuracy of 78% after 20 epochs.
Analisis Komparatif Algoritma K-Means dan K-Medoids dalam Klasterisasi Minat Belajar Siswa MDTA Qur'an Kisaran William Ramdhan
Management of Information System Journal Vol 4 No 3: Juli 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/mis.v4i3.3116

Abstract

Learning interest is one of the important factors that influence student success in following the learning process. However, identification of students' learning interest levels is often done subjectively so that it is less able to describe the student's condition as a whole. This study aims to compare the performance of the K-Means and K-Medoids algorithms in grouping the learning interests of MDTA Qur'an Kisaran students based on academic and non-academic data. The dataset used consists of 119 students with six variables, namely academic grades, attendance percentage, memorization assessment, Qur'an reading ability, moral assessment, and student participation. The clustering process was carried out with three clusters representing the categories of high, medium, and low learning interest. Cluster quality evaluation was carried out using the Davies-Bouldin Index (DBI) and Silhouette Coefficient. The results showed that the K-Means algorithm produced a DBI value of 1.5839 and a Silhouette of 0.2186, while the K-Medoids algorithm produced a DBI value of 1.5950 and a Silhouette of 0.2046. Based on the evaluation results, the K-Means algorithm performed better than K-Medoids in clustering student learning interests. The clustering results can be used to support decision-making in student development, developing learning strategies, and selecting participants for the Inter-Islamic Sports and Arts Week (PORSADIN) in a more objective and data-driven manner.
Comparison Of Machine Learning Algorithms For Rice Production Prediction Abdul Karim; Yuwaldi Away; Syahrial; Roslidar; Jeperson Hutahaean; William Ramdhan; Yessica Siagian
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 2 (2026): April 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i2.7453

Abstract

Rice production forecasting plays an important role in supporting future agricultural planning, food supply management, and food security. Accurate yield prediction allows governments and farmers to estimate production outcomes and develop appropriate strategies to maintain stable food availability.This study addresses this gap by comparing four regression-based machine learning models: Random Forest, XGBoost, Support Vector Regression (SVR), and Artificial Neural Network (ANN). All models were trained and tested using the same dataset to ensure a fair evaluation. Model performance was measured using the coefficient of determination (R²). The results show that Random Forest achieved the best performance (R² = 0.963), followed by XGBoost (R² = 0.959). In contrast, SVR (R² = -0.064) and ANN (R² = -2.417) performed poorly, indicating limited predictive capability. Overall, these findings suggest that ensemble-based methods, particularly Random Forest and XGBoost, are more reliable and effective for rice production forecasting compared to SVR and ANN.
Machine Learning Decision Support System for Heart Disease Prediction with Optuna and Threshold Optimization Ramdhan, William; Hutahaean, Jeperson; Jollyta, Deny; Karim, Abdul
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5684

Abstract

Cardiovascular disease remains a major global health challenge, necessitating accurate and reliable decision support systems for early detection. This study proposes a machine learning–based decision support system that integrates ensemble learning, automated hyperparameter optimization using Optuna, and decision threshold tuning. The system was evaluated using several baseline machine learning models, including Logistic Regression, SVM, KNN, Decision Tree, and Random Forest, with the Random Forest model selected for optimization. Hyperparameter tuning with Optuna and decision threshold optimization led to a significant improvement in accuracy (95.0%) and ROC–AUC (0.977), with the optimized model outperforming all baseline models. This approach demonstrates improved sensitivity, reduced false negatives, and enhanced predictive performance, offering a clinically reliable tool for early heart disease detection. The results emphasize the importance of model optimization and decision threshold calibration in clinical decision support systems.
Data Mining Dengan Pendekatan Multiple Linear Regression Untuk Prediksi Hasil Panen Padi Alwi Syahbirin; William Ramdhan; Wan Mariatul Kifti
JURIKOM (Jurnal Riset Komputer) Vol. 13 No. 2 (2026): April 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i2.9652

Abstract

The rice agricultural sector plays an essential role in Asahan Regency, but current harvest predictions are still carried out conventionally and subjectively. This causes data inaccuracies that impact uncertainty in logistics planning and production policies by the local government. Therefore, this study aims to build a more accurate rice harvest prediction model to assist the Department of Agriculture of Asahan Regency in making strategic decisions. The research methodology used is data mining techniques by implementing the multiple linear regression method, utilizing historical data on land area and rainfall to predict harvest yields. The main results of this study indicate that the web-based prediction model designed is capable of performing valid calculations, producing a harvest projection for 2025 of 54,308.79 tons that aligns with mathematical model calculations. The implication of this research is that the relevant agencies have a reliable decision support tool for planning food security, irrigation systems, and fertilizer provision more efficiently, thereby minimizing errors caused by manual calculations
DETERMINATION OF PRIORITIES OF ELEMENTARY SCHOOL REHABILITATION AT ASAHAN USING SIMPLE ADDICTIVE WEIGHT Dian Aprillia; William Ramdhan; Wan Mariatul Kifti
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (775.325 KB) | DOI: 10.34288/jri.v4i4.193

Abstract

In the budgeting process for school building rehabilitation activities in Asahan Regency, there are still inaccuracies in selecting prioritized primary schools for rehabilitation. This study aimed to apply the Simple Additive Weighting (SAW) method to determine five primary schools that were prioritized for repair. This research method uses quantitative methods. The data source comes from the East Kisaran and West Kisaran Elementary Schools. The data were analyzed using the SAW method based on the criteria weight depending on the matrix value and normalization. The results showed the 5 largest criteria weights, namely UPTD SDN 010097 Selawan (0.940), UPTD SDN 014689 Lestari (0.884), UPTD SDN 010039 Sentang (0.880), SD Taman Kasih Karunia (0.847), and UPTD SDN 018453 Siumbut-Umbut (0.820). ). This study concluded that the double exponential smoothing method could make it easier to determine which primary school decisions are prioritized for rehabilitation.
Workshop Pemanfaatan Tools Artificial Intelligence Dalam Pembelajaran Sebagai Upaya Peningkatan Kompetensi Guru SMK Di Era Digital William Ramdhan; Nurwati; Andrew Ramadhani
Journal Of Indonesian Social Society (JISS) Vol. 4 No. 1 (2026): JISS - Februari
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jiss.v4i1.633

Abstract

Perkembangan teknologi digital, khususnya Artificial Intelligence (AI), menuntut guru untuk mampu mengintegrasikan teknologi secara efektif dalam proses pembelajaran. Namun, hasil identifikasi awal di SMK Al-Ma’asum Kisaran menunjukkan bahwa sebagian guru masih memiliki keterbatasan pemahaman dan keterampilan dalam memanfaatkan tools AI untuk mendukung pembelajaran mendalam. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi guru dalam memanfaatkan tools AI sebagai pendukung perancangan pembelajaran, pengembangan media, dan asesmen adaptif. Solusi yang ditawarkan berupa kegiatan workshop berbasis praktik langsung yang dilaksanakan secara tatap muka pada Jumat, 21 November 2025, dengan melibatkan 28 guru SMK Al-Ma’asum Kisaran. Workshop memfokuskan pada pemanfaatan ChatGPT untuk penyusunan skenario pembelajaran berbasis Problem Based Learning (PBL) dan soal Higher Order Thinking Skills (HOTS), Canva untuk perancangan media visual, Quizizz dan Kahoot untuk asesmen adaptif, serta PhET Interactive Simulations untuk visualisasi pembelajaran. Hasil evaluasi menunjukkan peningkatan pemahaman pembelajaran mendalam dari 56% menjadi 82%, pemanfaatan AI dari 61% menjadi 87%, serta kemampuan menyusun modul ajar dari 58% menjadi 81%. Tingkat kepuasan peserta mencapai 94%, menunjukkan bahwa workshop efektif dalam meningkatkan kompetensi guru dan mendukung inovasi pembelajaran berbasis AI.
E - CRM E-CRM DALAM MENDUKUNG PROSES BISNIS PENJUALAN BUSANA DI DITA FASHION BATU BARA Mahyumita Sari; William Ramdhan; Elly Rahayu
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8369

Abstract

Abstrak Perkembangan teknologi internet yang semakin pesat, didukung oleh kemudahan akses melalui berbagai perangkat komunikasi, telah mengubah pola dan perilaku konsumen dalam berbelanja menjadi lebih efektif dan efisien. Selain itu, melalui pokok pembahasan yang dilakukan pada penelitian kali ini bertujuan dapat meningkatkan efektivitas aktivitas pemasaran yang sebelumnya hanya mengandalkan media sosial, diperlukan penerapan sistem yang lebih terintegrasi agar seluruh proses pemasaran dapat berjalan secara lebih optimal dan terarah. Dan selain itu juga untuk bagian Metode Penelitian yang digunakan dalam penelitian kali ini adalah metode kualitatif, karena penelitian ini ditujuhkan untuk dapat memperoleh pemahaman yang mendalam mengenai fenomena yang terjadi melalui pengumpulan dan analisis data. Berdasarkan keseluruhan penjabaran dalam penelitian ini maka penulis dapat menyimpulkan bahwa penerapan Electronic Customer Relationship Management (E-CRM) pada Dita Fashion terbukti mampu meningkatkan efektivitas proses bisnis, terutama dalam pemasaran, pelayanan dan pengelolaan hubungan dengan pelanggan. Sistem ini mengintegrasikan aktivitas promosi serta komunikasi pelanggan ke dalam satu platform sehingga lebih terstruktur, cepat dan mudah dikendalikan. Selain meningkatkan kualitas pelayanan melalui respons yang lebih efisien, E-CRM juga memusatkan data pelanggan, termasuk riwayat transaksi pelanggan. Ketersediaan informasi yang terorganisasi tersebut membantu Dita Fashion memahami kebutuhan pelanggan dengan lebih baik serta mendukung penyusunan strategi bisnis yang lebih tepat, efektif dan berorientasi pada kepuasan pelanggan. Abstract The rapid development of internet technology, supported by easy access via various communication devices, has transformed consumer shopping patterns and behaviors, making them more effective and efficient. Furthermore, the focus of this study aims to enhance the effectiveness of marketing activities—which previously relied solely on social media by implementing a more integrated system so that the entire marketing process can run more optimally and in a targeted manner. Furthermore, the research method employed in this study is a qualitative approach, as this research is intended to gain a deep understanding of the phenomena observed through data collection and analysis. Based on the overall findings of this study, the author concludes that the implementation of Electronic Customer Relationship Management (E-CRM) at Dita Fashion has proven effective in enhancing business process efficiency, particularly in marketing, customer service, and customer relationship management. This system integrates promotional activities and customer communications into a single platform, making them more structured, faster, and easier to manage. In addition to improving service quality through more efficient responses, E-CRM also centralizes customer data, including customer transaction histories. The availability of this organized information helps Dita Fashion better understand customer needs and supports the development of business strategies that are more precise, effective, and focused on customer satisfaction.
Pemanfaatan Media Sosial dan E-Commerce Sebagai Peluang Usaha Mandiri Bagi Kader Desa Kelurahan Dadimulyo Masitah Handayani; William Ramdhan; Dewi Maharani
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 1 No. 1 (2021): April 2021
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v1i1.607

Abstract

Abstract: Nowadays, the use of social media and e-commerce has a significant influence on people's lives and is supported by the rapid development of information technology. The existence of social media and e-commerce provides benefits to society, one example is in the field of independent business. This service activity is carried out in the form of socialization or delivering short material followed by a discussion where this activity aims to provide insight into the proper use of social media and e-commerce so that it can provide benefits to its users. Participants in this activity were village cadres in Dadimulyo Village. The result of this service activity is in the form of understanding material for activity participants who can later implement social media and e-commerce in creating independent business opportunities. Keywords: Social Media; E-Commerce; Cadre Abstrak: Pada zaman sekarang, pemanfaatan media sosial dan e-commerce memiliki pengaruh yang signifikan dalam kehidupan masyarakat dan didukung dengan perkembangan teknologi informasi yang pesat. Adanya media sosial dan e-commerce memberi manfaat bagi masyarakat salah satu contohnya adalah dalam bidang usaha mandiri. Adapun kegiatan pengabdian ini dilaksanakan dalam bentuk sosialisasi atau menyampaian materi singkat yang dilanjutkan dengan diskusi dimana kegiatan ini bertujuan untuk memberikan wawasan mengenai pemanfaatan media sosial dan e-commerce dengan tepat sehingga mampu memberikan manfaat bagi para penggunanya. Peserta pada kegiatan ini adalah para kader desa yang ada di Kelurahan Dadimulyo. Hasil dari kegiatan pengabdian ini adalah berupa pemahaman materi bagi para peserta kegiatan yang nantinya dapat mengimplementasikan media sosial dan e-commerce dalam menciptakan peluang usaha mandiri. Kata Kunci: Media Sosial; E-Commerce; Kader 
Co-Authors . Roslidar Abdul Karim Abdul Karim Abdul Karim Syahputra Abdul Karim Syaputra Ade Amanda Yunita Ade Chairani Ade Nurainun Afriany, Joli Agi Septi Pitaya Aidil Adi Suhendra Akmal Akmal Alwi Syahbirin Andrew Ramadhani Anggi Melisa Nasution Anjani Annisa Azzahra Arridha Zikra Syah Ayu Riski Azura Rahmadani Hasibuan Cecep Maulana Chitra Latiffani Chitra Latiffani Chitra, Latiffani Dahriansah - Dahriansyah Dahriansyah Dalimunthe, Ruri Ashari Darmiyanti Marpaung Deny Jollyta Deny Jollyta Dewi Maharani Dian Aprillia Dian Aprillia Dinda Novri Farenza Dwi Putri eka eka Elly Rahayu Era Fazira Erick Santoso Frans Andrean Hasibuan Gina Safira Havid Syafwan Indri Arfanda Jeperson Hutahaean Jeperson Hutahaean Jeperson Hutahaean Jihan Raihan Zein Johan Johan Junaidi Sholat Kifti, Wan Mariatul Leli Dayani M. Zulfakhri Jain Mahyumita Sari Masitah Handayani Mesran, Mesran Mhd Ishan Muhammad Novri Rachmawan Nadya Viranika Nency Widya Monalisa Nofriadi Nofriadi Nurmawati Nursucika Hasanah Nurwati Nurwati Nurwati Nurwati Nurwati Oktaviani Dwi Rahayu Parini Prihandoko Prihandoko Pritty Noviana Sari Putri Rahma Dhini Rahayu, Elly Rahmayanti Raja Fazlun Dinara Ricki Ananda Riki Andri Yusda Rizwan Sai Rohminatin Rohminatin Rolly Yesputra Roni Dalimunthe Roslidar Ruri Ashari Dalimunthe sahren, sahren Santoso Santoso Santoso Santoso Santoso Santoso Sartini Sartini Sela Gustin Selly Tri Amanda Siti Nur Sakinah Siti Nurhanis Sitta Ayu Anggraini Sri Helena Utami Saragih Sudarmin Sudarmin Suginam SUMANTRI . Sumatri Sumatri Sumatri Sumatri Surya Darma Nasution Syafwan, Mahdhivan Syahrial Syahrial, Syahrial Teguh Gilang Maulana Marpaung Teti Purwanti Umi Indah Hazrina USWATUN HASANAH Vira Fahrani Waji Datur Rahmi Sipahutar Wan Mariatul Kifti Wan Mariatul Kifti Wan Mhd Iqbal Muttaqin Widya Amanda Susilo Yessica Siagian Yessica Siagian Yunika Afrianti Yurizka Sri Nanda Yuwaldi Away Zulkarnain Sirait