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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Informatika Jurnal Teknologi Teknosains: Media Informasi Sains dan Teknologi Scientific Journal of Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Komtika (Komputasi dan Informatika) Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Telematika CCIT (Creative Communication and Innovative Technology) Journal Technologia: Jurnal Ilmiah Abdimasku : Jurnal Pengabdian Masyarakat Infotech: Journal of Technology Information Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Dan Tekonologi Komputer (JITEK) Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Jurnal Teknologi Buffer Informatika Jurnal Komtika (Komputasi dan Informatika) Jurnal Informatika Dan Tekonologi Komputer Jurnal Teknik Informatika dan Teknologi Informasi
Rahmat Sulaiman
ISB Atma Luhur
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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Physics Social Sciences Other

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MENINGKATKAN PROMOSI DAN PENGUATAN SDM MELALUI PEMBUATAN MEDIA PROMOSI BAGI PARA UMKM Sugihartono, Tri; Sulaiman, Rahmat; Alkayess, Ahmad Faqih; Indallah, Royhan; Yanuarti, Elly
Jurnal Pengabdian Masyarakat Berbasis Teknologi Vol 4 No 1 (2023): Volume 4, Nomor 1, Mei 2023
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/abdimastek.v4i1.1672

Abstract

Pada era Revolusi Industri 4.0 penggunaan teknologi, komunikasi, dan informasi semakin maju dan terus berkembang. Proses ini terus mengalami kemajuan yang terbilang cukup pesat. Dengan kemajuan yang pesat ini digitalisasi sangat membantu masyarakat dengan memberikan kemudahan juga menciptakan banyak perubahan. Begitupun para UMKM harus bisa membuat berbagai macam inovasi yang berlandaskan teknologi yang bisa digunakan untuk kegiatan sehari-hari. Tujuan dari adanya digitalisasi adalah untuk membantu pelanggan dalam memudahkan segala aktivitas dan pekerjaan mereka sehari-hari. Dengan adanya latar belakang diatas maka tantangan kita sebagai masyarakat saat ini adalah sadar digitalisasi, salah satunya di bidang desain grafis, Proses Digitalisasi di bidang UMKM dapat berupa pembuatan desain digital, dan penggunaan media sosial,. 2 unsur tersebut yang dapat saling keterkaitan dan mempunyai dampak yang cukup besar. Sehingga pelaku UMKM dapat memberikan informasi kepada masyarakat tentang produk yang dijual secara luas. diharapkan dengan adanya pembinaan UMKM di keluarahan ampui dapat memberikan kontribusi nyata dalam pelaksanaan dan pembinaan terhadap UMKM di kelurahan ampui.
WORKSHOP DIGITAL MARKETING SEBAGAI UPAYA PENGUATAN KUALITAS PEMBELAJARAN DAN PENGUASAAN TEKNOLOGI Yanuarti, Elly; Sarwindah, Sarwindah; Sugihartono, Tri; Sulaiman, Rahmat
Jurnal Pengabdian Masyarakat Berbasis Teknologi Vol 4 No 2 (2023): Volume 4, Nomor 2, Oktober 2023
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/abdimastek.v4i2.2010

Abstract

Dunia pemasaran digital saat ini sudah berkembang dan terus berubah seiring penggunaan internet yang semakin tinggi dan adanya teknologi dan tren baru yang muncul. Digital marketing yang merupakan pemasaran interaktif dan terpadu memudahkan interaksi antara produsen, perantara pasar dan konsumen. Tujuan dari pengabdian kepada masyarakat ini adalah untuk meningkatkan kompetensi pendidik dalam memanfaatkan teknologi digital untuk meningkatkan promosi sekolah dan memasarkan produk kreatif yang dihasilkan oleh peserta didik di setiap jurusan. Workshop digital marketing ini menjadi wadah agar tercapainya tujuan untuk peningkatan kualitas pembelajaran dan penguasaan teknologi 4.0 dari kurikulum merdeka. Workshop ini akan membantu para pendidik lebih memahami cara mengintegrasikan teknologi dalam pembelajaran sehingga peserta didik memiliki bekal dan siap dalam menghadapi tantangan dunia digital.
IMPLEMENTASI METODE ACCESS CONTROL LIST PADA MIKROTIK DALAM MENGAMANKAN JARINGAN INTERNET DI KANTOR LURAH AIR SELEMBA Rahmat Sulaiman; Rab Sahf Al Fathul; Agustina Mardeka Raya
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 4 No. 1 (2024): April: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v4i1.2880

Abstract

To meet the minnimum requirements of people who want to get information quickly and easily, the need for internet access is very high. Thus, we must continue to look for and strive for quality. There is a delay in communication and there is no filtering for devices connected to Office of Salemba’s internet. This is because there is no way to regulate the access rights for each device on the network, therefore it is necessary to implement the Access Control List (ACL) method on computer networks with the aim of making staff or employees more stable when working. In getting internet access, the development used is NDLC consisting of Analysis, Design, Prototyping Simulation, Implementation, Monitoring and Management. Data collection methods are literature study, observation and interviews. The routerboard that has been used is RB941-2nd. The results obtained from this research are that this method is very helpful in limiting the number of clients who get the internet and filtering unauthorized packets.
Carprice Intelligence: Prediction Price of Second Car using Machine Learning Rahmat Sulaiman; Burham Isnanto
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 18, No 1 (2026): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v18i1.37602

Abstract

Determining a fair market price for a used vehicle is a significant challenge for both sellers and buyers due to a lack of data transparency and the variety of influencing factors such as brand, production year, and mileage. This research aims to address this issue by developing a market data-based used vehicle price prediction system using a machine learning approach. The methodology adapts the CRISP-DM framework. Data is collected through web scraping from leading online marketplaces and processed through cleaning, normalization, and encoding before being used for modeling. Various regression algorithms were implemented, and the Linear Regression model was chosen for its optimal performance. The model was evaluated using the R Squared metric, yielding a score of 74% on the training data and 76% on the test data, demonstrating good accuracy and adaptability to new data. The best model was then implemented into a simple user interface based on Streamlit, allowing users to get a more objective recommendation for buying and selling prices. Overall, this system has great potential to facilitate more efficient and transparent transactions in the used automotive market, helping users make smarter and more profitable decisions.
Optimalisasi Pembangunan Desa: Prediksi Kebutuhan Intervensi Ekonomi di Jawa Barat Menggunakan Algoritma Machine Learning Burham Isnanto; Rahmat Sulaiman
Buffer Informatika Vol. 12 No. 1 (2026): Buffer Informatika
Publisher : Department of Informatics Engineering, Faculty of Computer Science, University of Kuningan, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/buffer.v12i1.519

Abstract

Rural development plays a crucial role in reducing economic disparities, particularly in West Java, which comprises 5,311 villages with substantial variation in the Village Development Index (Indeks Desa Membangun/IDM). This study develops a machine-learning-based predictive model to classify villages’ economic intervention needs by utilizing multidimensional data—economic, social, and infrastructure indicators—sourced from BPS and the Ministry of Villages. Three machine learning algorithms—Random Forest, Gradient Boosting, and XGBoost—were evaluated using the 2023 West Java IDM dataset, which includes several relevant variables.The preprocessing stage involved handling missing values, data normalization, and data transformation, while hyperparameter optimization using GridSearchCV significantly improved model accuracy. The results indicate that XGBoost outperformed the other algorithms, achieving an accuracy of 88% and an F1-score of 0.93, particularly excelling in identifying autonomous villages (Class A) and high-intervention villages (Class D). Key contributing variables included the availability of financial services and the number of micro-industries.The model was integrated into an interactive dashboard built with Dash to support policymakers in conducting multi-level analyses (village/subdistrict/regency) and formulating evidence-based recommendations. The findings of this study have important implications for enhancing the efficiency of resource allocation and improving policy transparency, aligning with Bappenas' initiative to implement the Village Index starting in 2025. Overall, this research reinforces the importance of data-driven approaches for targeted and sustainable rural development
KLASIFIKASI MORTALITAS PENYAKIT JANTUNG ATEROSKLEROSIS MENGGUNAKAN ALGORITMA NAIVE BAYES, ADABOOST, DAN XGBOOST Burham Isnanto; Rahmat Sulaiman
Technologia : Jurnal Ilmiah Vol 17 No 3 (2026): Technologia (Juli)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jit.v17i3.24059

Abstract

Penyakit kardiovaskular, khususnya aterosklerosis, merupakan penyebab utama kematian global dengan menyumbang sekitar 32% dari seluruh kematian di dunia. Penelitian ini mengimplementasikan tiga algoritma machine learning—Naive Bayes Gaussian, AdaBoost, dan XGBoost—untuk memprediksi mortalitas pasien penyakit jantung aterosklerosis (ICD I25.1) menggunakan data rekam medis elektronik dari Pusat Jantung Nasional Harapan Kita periode 2016–2021 yang terdiri dari 4.691 rekaman pasien. Proses pengolahan data mengikuti kerangka Knowledge Discovery in Databases (KDD) yang meliputi seleksi, preprocessing, transformasi, dan klasifikasi data. Dataset memiliki ketidakseimbangan kelas yang signifikan dengan 4.478 data mortalitas rendah dan 213 data mortalitas tinggi, sehingga ROC AUC dipilih sebagai metrik evaluasi utama. Hasil penelitian menunjukkan XGBoost memiliki nilai ROC AUC tertinggi sebesar 0,74, diikuti AdaBoost sebesar 0,68, dan Naive Bayes sebesar 0,64. Analisis SHAP mengungkap bahwa konsentrasi hemoglobin (khermchc), hemoglobin rata-rata per sel (hermch), trombosit, dan leukosit adalah fitur yang paling berpengaruh terhadap prediksi mortalitas. Model terbaik diimplementasikan dalam aplikasi berbasis web menggunakan Flask dan Python, memungkinkan masyarakat melakukan deteksi dini risiko mortalitas penyakit jantung aterosklerosis secara mandiri.
Fish Disease Classification Using MobileNetV3Large Transfer Learning and Fine-Tuning Dela Fifi Lusiana; Ellya Helmud; Rahmat Sulaiman
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 3 (2026): Article Research July 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i3.16246

Abstract

Fish diseases represent a major challenge in the aquaculture industry as this phenomenon frequently leads to significant economic losses. Manual disease identification requires specialized expertise and is time-consuming in the field. Therefore, this study aims to implement the MobileNetV3Large Deep Learning architecture to automatically identify eight types of fish conditions. This research dataset utilizes 2,400 digital images distributed evenly across eight fish condition categories. Each class consists of 300 image samples, including Bacterial Red disease, Aeromoniasis, Bacterial gill disease, EUS Disease, Fungal diseases Saprolegniasis, Parasitic diseases, White tail disease, and a Healthy Fish group. The dataset was sourced from https://www.kaggle.com/datasets/irfanulhuda/fish-disease-detection-dataset. These conditions include bacterial, fungal, viral, and parasitic infections, as well as healthy fish conditions. The research methodology applies Transfer Learning techniques combined with Fine-Tuning optimization on the last 70 layers. The methodology applies a transfer learning strategy with a data split of 80% for training, 10% for validation, and 10% for testing. This step was taken to adapt the model's weights to the visual characteristics of the fish disease images. The process was evaluated using the Adam optimization function and the Categorical Cross-Entropy loss function. Experimental results demonstrate highly superior model performance on the test data. The MobileNetV3Large model successfully achieved a test accuracy of 92.92% with a loss value of 0.2099. Furthermore, evaluation through the Confusion Matrix and ROC curves yielded an average AUC value of 1.00 across the majority of classes. This figure indicates that the model possesses exceptionally high discrimination capacity and sensitivity. In conclusion, the computational efficiency of the MobileNetV3Large architecture makes this system a highly potential solution. Researchers can implement this model on mobile devices to assist fish farmers in diagnosing diseases quickly and accurately directly at the aquaculture sites
Peranan Strategis Teknologi dalam Memperkuat Wawasan Kebangsaan dan Karakter Generasi Muda untuk Bela Negara di Era Digital Tri Sugihartono; Syafrul Irawadi; Rahmat Sulaiman; Elly Yanuarti; Agustina Mardeka Raya; Goenawan Brotosaputro
Jurnal Pengabdian Masyarakat Berbasis Teknologi Vol 7 No 01 (2026): Volume 7, Nomor 1, Mei 2026
Publisher : ISB Atma Luhur

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

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk menguatkan peranan strategis teknologi dalam membentuk wawasan kebangsaan, karakter, dan kesadaran bela negara generasi muda di era digital. Dilatarbelakangi oleh perubahan global, bonus demografi menuju Indonesia Emas 2045, serta ancaman digital seperti hoaks, judi online, radikalisme, dan disinformasi, kegiatan ini dilaksanakan di Kampus ISB Atmaluhur Belinyu. Metode yang digunakan adalah ceramah interaktif, diskusi kasus, dan tanya jawab. Peserta berjumlah 36 orang yang terdiri dari pelajar SMA/SMK dan mahasiswa. Hasil kegiatan menunjukkan peningkatan signifikan dalam pemahaman peserta tentang literasi digital berbasis Pancasila, pentingnya wawasan kebangsaan, serta bentuk-bentuk bela negara non-militer. Kegiatan ini direkomendasikan untuk menjadi program berkelanjutan dalam membangun generasi unggul yang berkarakter dan berdaya saing global.
IMPLEMENTATION OF C4.5 ALGORITHM FOR ASSESMENT OF COMMUNITY SATISFACTION Rahmat Sulaiman; Agustina Mardeka Raya; Laurentinus; Aria Setiawan
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 3 No. 2 (2023): Juli : Jurnal Informatika dan Teknologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v3i2.1826

Abstract

This Research applies the C4.5 Algorithm in deciding community satisfaction of sommunity services. Algorithm C4.5 is a classification algorithm with a decision tree technique that is well known and preferred because it has many advantages. These advantages, for example, can process numeric and discrete data, can handle missing attribute values, produce rules that are easy to interpret and the fastest. This research is a classification with the concept of data mining involving 20 community questionnaire data which are categorized as: cheap, expensive, appropriate, inappropriate, fast, long, comfortable, uncomfortable. There are four attributes that affect community satisfaction including: handling costs, service procedures, handling time and convenience. From the results of this research that has been conducted by researchers, it can be concluded. The customer satisfaction of the community services can be predicted and evaluated by utilizing data mining techniques using the C4.5 Algorithm to predict community satisfaction. This research also provided that C4.5 Algorihtm can be used to get high result of accuracy
Co-Authors Agustina Mardeka Raya Ahmad Faqih Alkayess Al Fathul, Rab Sahf Alkayess, Ahmad Faqih Aria Setiawan Cahya Saputra, Kornelius Eko Chrisna Putra, Rendy Rian Dela Fifi Lusiana Dwi Yuny Sylfania Elly Yanuarti Ellya Hellmud Ellya Helmud Fransiskus Panca Juniawan Goenawan Brotosaputro Harrizki Arie Pradana Harry Sudjikianto Hellmud, Ellya Indallah, Royhan Isnanto, Burham Juniawan, Fransiskus Panca Juwita, Ayu Ratna Kirana, Chandra Laurentinus Laurentinus, Laurentinus Marina Vebu Marini . Marini Marini Padli Padli Pradana, Harrizki Arie R Burham Isnanto Rab Sahf Al Fathul Romadiana, Parlia Royhan Indallah Sarwindah Sarwindah Sarwindah, Sarwindah Sudjikianto, Harry Sugihartono, Tri Syafrul Irawadi Tri Sugihartono Yanuarti, Elly