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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmiah KOMPUTASI Information Management For Educators And Professionals (IMBI) Jurnal Ilmiah Matrik JURNAL REKAYASA TEKNOLOGI INFORMASI Sebatik TEPIAN Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Informatika Wicida Jurnal Nasional Teknik Elektro dan Teknologi Informasi Abadi: Jurnal Ahmad Dahlan Mengabdi Jurnal Lentera Pengabdian ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat Diteksi : Jurnal Pengabdian Kepada Masyarakat JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Nurhuda, Asep
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Religion Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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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.
Pelatihan AI Untuk Meningkatkan Kreativitas Berkarya Di SMK TI Pratama PGRI Samarinda Franz, Annafi; Maria, Eny; Suswanto; Junirianto, Eko; Yulianto; Nurhuda, Asep; Khamidah, Ida Maratul; Ramadhani, Suci; Andrea, Reza; Beze, Husmul
Ahmad Dahlan Mengabdi Vol 3 No 2 (2024): ABADI : Jurnal Ahmad Dahlan Mengabdi Edisi September 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Institut Teknologi dan Bisnis Ahmad Dahlan Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58906/abadi.v3i2.150

Abstract

Workshop penggunaan media sosial bagi siswa SMPN 1 Siman bertujuan meningkatkan minat dan keterampilan kewirausahaan e-commerce. Diikuti 150 siswa kelas 8 dan 9, kegiatan ini mencakup pelatihan pembuatan akun bisnis di Instagram dan TikTok serta pembuatan konten promosi menggunakan Canva. Evaluasi pre-test dan post-test menunjukkan peningkatan pemahaman dan keterampilan hingga 32%. Sebanyak 90% siswa berhasil mempublikasikan konten yang menarik audiens. Perubahan penggunaan media sosial dari hiburan menjadi sarana produktif menandai dampak positif kegiatan ini. Program ini efektif menumbuhkan jiwa kewirausahaan digital dan direkomendasikan untuk dilanjutkan dengan pendampingan serta pelatihan lanjutan.
The Development of a Geographic Information System for Mapping Creative Economy Actors in Balikpapan Using the Prototype Method Rawanggalih, Raihan Maheswara; Nurhuda, Asep; Satria, Bagus
TEPIAN Vol. 5 No. 3 (2024): September 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i3.3104

Abstract

Geographic Information Systems (GIS) play a crucial role in collecting, managing, analyzing, and presenting geographically referenced data. This research focuses on the development of a GIS-based application designed to map and analyze the distribution of creative economy participants in Balikpapan. Using the System Development Life Cycle (SDLC) Prototype method, the study integrates spatial data with geographic analysis, utilizing technologies such as Node.js, Leaflet, Laravel, and QGIS in the development process. Data related to creative economy actors is gathered locally, while spatial data is sourced from the Ina Geoportal website. This web-based application provides comprehensive mapping capabilities, enabling users to identify strategic business locations, optimize business potential, and improve service accessibility. Additionally, the tool aims to offer insights for local government policymaking, contributing to regional economic growth and enhancing community welfare. The integration of GIS into the application also supports the preservation and promotion of regional cultural identity, offering valuable information for sustainable development. Ultimately, this research highlights the significant role of GIS in improving economic planning, fostering informed decision-making, and driving sustainable development in Balikpapan.
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 AA Sudharmawan, AA Ahmad Fahrijal Pukeng Alam, Muhammad Wahyu Syafiul Andi Yusika Annafi Franz annafi franz, annafi Bagus Perwira Utama Yoga Suwatno Dewi Rosita Eko Junirianto Emil Riza Putra Fajar Ramadhani Harpad, Bartolomius Husmul Beze, Husmul Ida Maratul Khamidah Imron Imron Imron, Imron Ita Arfyanti Junirianto, Eko Karim, Syafei Maria, Eny Muhamad Almazazi Metekohy Muhamad Risky Ramadhani Muhammad Sirajul Amin Mubarak Muslimin B, Muslimin Muslimin Muslimin Nurhasanah , Nurhasanah Nursobah, Nursobah Ping , Maria Floriana Pitrasacha Adytia Putra Hadi Wijaya Rachmad Fauzi Rachmadani, Budi Rahim, ilma Rahmat Hidayat Ramadhani, Budi Rawanggalih, Raihan Maheswara Reza Andrea Rini, Eka Mistiko Salmon Salmon Satria , Bagus Sefty Wijayanti Suci Ramadhani, Suci Sunarto Suswanto Suswanto Suswanto Suswanto Suswanto, Suswanto Tandi, Yospin Tommy Bustomi Wijayanti, Sefty Yulianto Yulianto Yulianto Yunita Yunita