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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer dan Agri-Informatika Scan : Jurnal Teknologi Informasi dan Komunikasi Indonesian Journal of Business and Entrepreneurship (IJBE) Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Ilmiah KOMPUTASI JOURNAL OF APPLIED INFORMATICS AND COMPUTING J I M P - Jurnal Informatika Merdeka Pasuruan Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Antivirus : Jurnal Ilmiah Teknik Informatika ILKOMNIKA: Journal of Computer Science and Applied Informatics Just TI (Jurnal Sains Terapan Teknologi Informasi) TEPIAN Teknomatika (Jurnal Teknologi dan Informatika) Buletin Poltanesa JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Jurnal Lentera Pengabdian Journal of Geomatics Engineering, Technology, and Science ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat
Karim, Syafei
Politeknik Pertanian Negeri Samarinda
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering 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 Languange, Linguistic, Communication & Media Social Sciences Other

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Pelatihan Penerapan Artificial Intelligence (AI) untuk Menunjang Aktifitas Pembelajaran Pada Sekolah Dasar Daarul Hijrah Al-Amin Samarinda Franz, Annafi; Maria, Eny; Suswanto, Suswanto; Yulianto, Yulianto; Rachmadani, Budi; Junirianto, Eko; Nurhuda, Asep; Khamidah, Ida Maratul; Ramadhani, Suci; Muslimin, Muslimin; Beze, Husmul; Andrea, Reza; Karim, Syafei; Putra, Emil Riza; Ramadhani, Fajar; Satria, Bagus; Imron, Imron
Lentera Pengabdian Vol. 1 No. 04 (2023): Oktober 2023
Publisher : Lentera Ilmu Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59422/lp.v1i04.139

Abstract

Dalam era perkembangan teknologi yang cepat dan globalisasi yang semakin luas, pendidikan di tingkat Sekolah Dasar (SD) menghadapi tantangan untuk terus meningkatkan kualitas pembelajaran. Kecerdasan Buatan (Artificial Intelligence atau AI) telah muncul sebagai sebuah alat potensial yang dapat merevolusi metode pembelajaran dan meningkatkan keterlibatan siswa. Namun, untuk berhasil menerapkan AI dalam kurikulum SD, para pendidik memerlukan pemahaman dan pelatihan yang memadai. Pengabdian ini bertujuan untuk memberikan latar belakang dan implementasi pelatihan penerapan AI dalam konteks pembelajaran di Sekolah Dasar Daarul Hijrah Al-Amin, Samarinda. Melibatkan para guru sebagai peserta utama, pelatihan ini berfokus pada memperkenalkan konsep dasar AI dan memberikan panduan praktis tentang cara mengintegrasikan teknologi ini ke dalam metode pembelajaran yang sudah ada. Harapannya, pelatihan ini akan membantu para pendidik dalam menciptakan lingkungan pembelajaran yang adaptif, interaktif, dan sesuai dengan kebutuhan individu siswa, dengan demikian, mendorong perkembangan keterampilan dan pemahaman yang lebih mendalam. Hasil dari pengabdian ini diharapkan dapat berkontribusi signifikan dalam pembaruan pendekatan pembelajaran di tingkat SD dan menciptakan dasar yang kokoh untuk peningkatan kualitas pendidikan dalam menghadapi tuntutan zaman modern yang terus berkembang.
Prostate Cancer Detection Using Gradient Boosting Machines Effectively MusliminB, Muslimin; Karim, Syafei; Nurhuda, Asep
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 3 (2025): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.107742

Abstract

Prostate cancer remains a leading cause of cancer-related deaths among men globally, emphasizing the critical need for accurate diagnostic tools. This study investigates the application of Gradient Boosting Machines (GBMs) for prostate cancer detection using a dataset with key tumor characteristics such as radius, texture, area, and symmetry. Data preprocessing included normalization, missing value handling, and the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance. The GBM model demonstrated an accuracy of 75%, with high precision (82%) and recall (88%) for malignant cases, underscoring its potential as a reliable diagnostic tool. However, the model's performance for benign cases was limited by severe class imbalance, reflected in a precision of 33% and recall of 25%. Interpretability was enhanced using SHAP values, identifying key predictors like tumor perimeter and compactness. While GBMs show promise in prostate cancer diagnostics, future research should incorporate multimodal data, advanced balancing techniques, and rigorous validation frameworks to enhance generalizability and fairness. This study highlights the value of machine learning in healthcare, contributing to improved diagnostic accuracy and patient outcomes.
Predicting USD to IDR Exchange Rates with Decision Trees B, Muslimin; Karim, Syafei; Nurhuda, Asep
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 6 No 3 (2024): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.235

Abstract

Predicting currency exchange rates is a complex challenge due to the numerous factors influencing market fluctuations. This study explores the application of decision trees to predict the USD to IDR exchange rate, leveraging historical data and key economic indicators. Decision trees, known for their ability to model non-linear relationships, offer an interpretable approach to understanding the factors driving exchange rate movements. The study demonstrates that decision trees can successfully capture the patterns in the data, providing a foundation for accurate predictions. However, the volatility and unpredictability of exchange rates, driven by geopolitical events, market sentiment, and macroeconomic shifts, highlight the limitations of the model. While decision trees provide a valuable starting point, the research suggests that combining them with advanced methods, such as ensemble techniques (random forests or gradient boosting) or time-series models (ARIMA or LSTM), could improve forecasting accuracy. Incorporating a wider range of features, including macroeconomic indicators and market sentiment analysis, further enhances the model's robustness. The findings underscore the need for hybrid approaches that combine the strengths of multiple models to better capture the dynamic and complex nature of financial markets. This research contributes to the broader understanding of exchange rate prediction and offers practical insights for businesses and financial institutions seeking to make informed decisions.
Video branding untuk promosi usaha mikro kecil menengah (UMKM) Eka Sari, Wahyuni; Yulianto, Yulianto; Junirianto, Eko; Franz, Annafi; Karim, Syafei; Khamidah, Ida Maratul
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 4 No 1 (2021)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v4i1.7174

Abstract

Nowadays, Branding or marketing share has evolved from creating images to video. The appropriate videos promotions can increase consumer interest in buying products. The suitable video can provide an positive image to consumers of a product or service. However, there are many obstacles in making interesting branding with video, such as the technique of taking pictures and creating an interesting storyline, the ability to package interesting videos such as editing sound and images, dubbing and then adding text. Solution for the problem, a community service program was carried out by the Politeknik Pertanian Negeri Samarinda to owners of micro, small and medium businesses (UMKM) in Samarinda. Implementation of this activity is carried out for a one-day workshop and then online mentoring for one week. The method of implementation is with lectures, practices, discussions and then questions and answers. This activity was attended by 30 participants. From 30 participants there were 28 participants who succeeded in making a video branding with a duration of 1 to 2 minutes.
Consumers' Perception of Omah Maha Hampers of College Students' Entrepreneurship Amalia, Puji Astuti; Syam, Herdi; Maulita; Yahya, Shanty; Karim, Syafei
Indonesian Journal of Business and Entrepreneurship Vol. 9 No. 2 (2023): IJBE, Vol. 9 No. 2, May 2023
Publisher : School of Business, IPB University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/ijbe.9.2.266

Abstract

This research is a qualitative study with a case study approach. This research was conducted in one Micro, Small and Medium Enterprise, Omah Maha. Omah Maha is a Micro, Small and Medium Enterprise organized by a group of students supported by Politeknik Negeri Samarinda. This research aimed to know consumers' perceptions of the hamper Omah Maha produced. The hamper created by Omah Maha is unique since it is a new business supported by Politeknik Negeri Samarinda, yet it is well known. Moreover, it has produced more than 50 packages in the first month. The research was conducted from September to November 2022. The data were collected through questionnaires, interviews and documentation. The subjects of the study were the consumers who met the criteria of this study. The data were analyzed and described qualitatively. The study found that the consumers had some perceptions of the hamper produced by Omah Maha, such as the price being affordable since the consumers could decide the price range. Furthermore, the strategy of promotion was interesting. Omah Maha used some digital platforms to advertise their product and offer special prices in the advertisement. The consumers also thought that the hamper had cultural value. Moreover, social factors, location and excellent service are also some factors that were considered. Keywords: consumers' perceptions, hamper, cultural value, Omah Maha, case study
Application of Marker-Based Tracking Augmented Reality of Human Digestive System for Elementary School Lestari, Ayu; Andrea, Reza; Karim, Syafei
TEPIAN Vol. 4 No. 3 (2023): September 2023
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v4i3.793

Abstract

The digestive system in humans is one of the materials taught in biology subjects. Submission of material about the digestive system in humans is still through conventional media such as blackboards and pictures contained in biology books. While this material about the digestive system is difficult to see directly because most of it occurs in the body. Augmented Reality is a technique that combines two-dimensional and three-dimensional virtual differences into a real sphere. Augmented Reality can be one of the effective teaching materials in elementary schools because of the rapidly advancing technology.
A Virtual Museums and 3D Artefacts to Improve Cultural Heritage Education Satria, Bagus; Ramadhani, Fajar; Karim, Syafei; Aini, Nur
TEPIAN Vol. 4 No. 4 (2023): December 2023
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v4i4.2967

Abstract

In the current era of globalization and modernization, the imperative to safeguard and convey cultural heritage and history to society becomes increasingly significant. Web-based virtual museums have emerged as a pivotal solution, facilitating the preservation and promotion of cultural heritage on a global scale. These virtual platforms offer visitors unprecedented access to artifact collections, transcending the limitations of physical museum visits. The immersive features, such as the ability to view objects from diverse angles and zoom in on intricate details, present a profound and engaging experience. This research is to contribute insights into the development of effective web-based virtual museums featuring 3D artifact representations, thereby making a meaningful contribution to the broader field of cultural heritage preservation. The primary objective of this study is to enrich the exploration and learning experiences of visitors in the realm of cultural heritage through digital platforms. The research employs a structured software development methodology encompassing vital stages like needs analysis, system design, implementation, testing, and maintenance. By focusing on the technological aspects, the study seeks to address challenges related to quality and reliability faced by web-based virtual museums. Furthermore, the findings aim to enhance the overall effectiveness of these museums in offering a comprehensive and captivating journey through cultural artifacts. This research is poised to not only advance the field of virtual museum development but also foster a deeper appreciation and understanding of our rich cultural heritage.
Cloud Storage for Object Detection using ESP32-CAM Imron, Imron; Satria, Bagus; Karim, Syafei; Ramadhani, Fajar
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.2994

Abstract

Cloud storage services can create an object storage bucket to store our pictures, among them the Cloud Storage FUSE, Scaleway, S3 bucket, Firebase,  etc. intelligent IoT systems generate vast amounts of multi-source industrial data, which necessitate a large amount of storage and processing power to enable real-time data processing and analysis. Cloud computing can be intricately linked into intelligent IIoT systems due to its strong computational and storage capabilities. Cloud Storage for Object Detection using ESP32-CAM. Create a workable solution that supports distributed storage bucket and implement it in a real-world setting. Implement the entire system as an addition to the well-known IoT cloud storage and run multiple experiments to evaluate its functionality in scenarios with varying setups and system. The target objects that are used as data sets are the ESP8266, Wemos D1, and Arduino Uno. Figuring out the ideal parameters for training the FOMO (First Object, More Object) model and then putting it into practice. It was necessary to find a balance between learning rate and accuracy, on the other hand, to maintain the highest possible accuracy in the identification of the microcontroller object to minimise the number of false positive reports. Find the value learning rate effective to this object is 0.01 with F1 score 98.7% and accuracy score 89.58%.
Random Forest Methodology for Analyzing Diabetes Risk Factors B, Muslimin; Karim, Syafei; Nurhuda, Asep
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 5 No 4 (2023): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.248

Abstract

Diabetes is a chronic disease posing significant health challenges globally, with rising prevalence due to genetic, lifestyle, and environmental factors. This research employs the Random Forest methodology to analyze diabetes risk factors and predict outcomes using a dataset of 768 patient records. Key attributes such as glucose levels, BMI, blood pressure, and age were evaluated to uncover their contribution to diabetes risk. The study achieved an overall accuracy of 72%, with glucose emerging as the most influential predictor, followed by BMI and age. While the model showed strong performance in identifying non-diabetic cases, moderate precision and recall for diabetic cases highlighted the impact of class imbalance. Feature importance analysis provided actionable insights, emphasizing glucose and BMI monitoring in diabetes management. Despite its strengths, challenges such as class imbalance and feature redundancy were noted, suggesting the need for oversampling techniques, additional variables, and advanced feature engineering. These findings demonstrate the utility of Random Forest in healthcare analytics, supporting predictive and preventive care strategies. Future research should focus on integrating lifestyle factors, expanding datasets, and exploring advanced machine learning models to enhance predictive accuracy and real-world applicability.
Pelatihan Internet of Things (IoT) untuk Peningkatan Kompetensi Praktik Siswa SMK Bhakti Loa Janan Kutai Kartanegara Imron, Imron; Maria, Eny; Satria, Bagus; Nurhuda, Asep; Junirianto, Eko; Ramadhani, Suci; Khamidah, Ida Maratul; Franz, Annafi; Yulianto, Yulianto; Beze, Husmul; Suswanto, Suswanto; Ramadhani, Budi; Andrea, Reza; Karim, Syafei
ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2025): ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat
Publisher : UPT Publikasi dan Penerbitan Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/abdiunisap.v3i2.472

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi siswa SMK Bhakti Loa Janan dalam memahami dan menerapkan teknologi Internet of Things (IoT) sebagai kesiapan menghadapi era industri digital. Kegiatan diikuti oleh 30 siswa dengan tahapan meliputi koordinasi awal, persiapan perangkat dan modul pelatihan, penyampaian teori, praktik langsung (hands-on training), evaluasi, dan pendampingan. Materi mencakup pengenalan konsep dasar IoT, pemrograman mikrokontroler Arduino dan ESP32, serta penerapan sensor DHT11 untuk sistem pemantauan suhu dan kelembaban berbasis platform ThingSpeak. Hasil evaluasi menunjukkan peningkatan signifikan pada pemahaman dan keterampilan siswa dalam merancang serta mengoperasikan sistem IoT secara mandiri. Peserta mampu mengintegrasikan perangkat keras dan perangkat lunak, serta memahami alur komunikasi data dengan baik. Selain itu, guru pendamping memperoleh wawasan baru untuk mengembangkan materi pembelajaran berbasis IoT di sekolah. Secara keseluruhan, kegiatan ini berdampak positif terhadap peningkatan literasi teknologi siswa serta memperkuat kolaborasi antara perguruan tinggi dan sekolah kejuruan dalam membangun ekosistem pendidikan vokasi yang adaptif terhadap perkembangan teknologi digital.
Co-Authors Alam, Muhammad Wahyu Syafiul annafi franz, annafi Annafi’ Franz AYU LESTARI Dawamul Arifin Dian Pratiwi Nurdin Egi Noviandra, Muhammad Eka Sari, Wahyuni Eko Junirianto Eko Junirianto Emil Riza Putra Erna Mulyati F. V. Astrolabe Sian Prasetya Fajar Ramadhani Fajar Ramadhani Herdi Syam Husmul Beze, Husmul Ida Maratul Khamidah Imam Kuswardayan Imron Imron Imron, Imron Junirianto, Eko Kardika, Adelia Juli Kevin Rivaldi Sosang Linda Linda Linda Linda M. Zaenal Abidin Maria, Eny Maulita Milatus Sholihah Mukarromah Muhammad Ari Pratama Murti, Darlis Heru Muslimin B, Muslimin Muslimin Muslimin Nia Kurniadin Nur Aini Nurhuda, Asep Pratiwi Wijayanti Puji Astuti Amalia Rachmadani, Budi Ramadhani, Budi Reza Andrea Riko Raynol Hasan Ronaldo Pascalis Naro Rudito Rudito Salsabila, Unik Hanifah Sry Wahyuni Suci Ramadhani Suci Ramadhani, Suci Sundarti, Anisa Suswanto Suswanto Suswanto, Suswanto Tarsius Aloysius Pedor Wahyuni Eka Sari Winda Surmanti Yahya, Shanty Yulianto Yulianto Yulianto Yulianto Yulianto