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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL REKAYASA TEKNOLOGI INFORMASI Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Informasi dan Teknologi Journal of Robotics and Control (JRC) Community Development Journal: Jurnal Pengabdian Masyarakat JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) International Journal of Robotics and Control Systems KLIK: Kajian Ilmiah Informatika dan Komputer DiJITAC : Digital Journal of Information Technology and Communication Ilmu Komputer untuk Masyarakat Sanskara Akuntansi dan Keuangan West Science Social and Humanities Studies Jurnal Pengabdian Masyarakat dan Riset Pendidikan Journal of Computer Science Advancements Techno Agriculturae Studium of Research Journal of Multidisciplinary Sustainability Asean Jurnal Pengabdian Masyarakat Nusantara OBOR: Oikonomia Borneo Journal of Social Science Utilizing Technology
Aldi Bastiatul Fawait Fawait
Universitas Widya Gama Mahakam Samarinda
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Training on Portfolio Creation and Learning Media Using Google Sites for Teachers and Students at SMK Muhamadiyah Banjar Sunardi Sunarni; Muhammad Kunta Biddinika; Furizal Furizal; Aldi Bastiatul Fawait; Yana Mulyana
ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2022): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Muhammadiyah Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (663.209 KB) | DOI: 10.35568/abdimas.v5i2.2732

Abstract

Website is a need to be very important to create an online presence for individuals, businesses, companies, and education. By using website, everyone can be better to known and widely known on the internet. However, some users still think that having a website should prepare many things, ranging from cost to good coding skills. The presence of the Google company in the world of technology provides convenience through its products. Google Sites is one of the platforms that provides services to make it easier to create the websites that are used as objects of training activities with workshop activity partners by Master Program of Informatics Universitas Ahmad Dahlan and SMK Muhammadiyah Banjar. The purpose of this community service activity is to carry out training on the use of Google Sites in creating portfolios and learning media. The audience of service is teachers and students with a total of 27 participants from SMK Muhammadiyah Banjar West Java Province. The activity was carried out on August 24, 2022. The stages of the activity were preparation, implementation, and evaluation. Preparation is carried out by conducting a pre-test survey of trainees. The implementation is carried out with training and hands on implementation of website creation for each participant. Evaluation of activities is carried out for each stage by collecting post-test from each trainee. The result of the activity is to increase the knowledge of training participants, both students and teaching staff in overcoming problems in the world of technology so as to make it easier to adapt to the industrial world. The training carried out received a very good response with the score of 79.13% stating that they strongly agreed with the advantages of this training.concept of healthy elderly people related to the pandemic.
Integration of AHP and TOPSIS Methods for Small and Medium Industries Development Decision Making Anton Yudhana; Rusdi Umar; Aldi Bastiatul Fawait Fawait
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 5 (2022): Oktober 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (898.876 KB) | DOI: 10.29207/resti.v6i5.4223

Abstract

Financial problems are one of the reasons why small and medium-sized industries (SMIs) in West Kutai have not developed optimally. Government assistance programs are one of the solutions. This program must be appropriate, so a decision-making tool is needed to help choose the right SMIs to be assisted later. The weight of the criteria was determined using the Analytical Hierarchy Process (AHP) technique, and the priority of the SMIs as the preferred proposal for the recipients of development assistance was determined using the Technique for Other Reference by Similarly to Ideal Solution (TOPSIS) approach. Labor, investment, production capacity, production value, and raw materials were used to determine the priorities of SMIs beneficiaries. Furthermore, TOPSIS prioritizes the development of alternative small and medium-sized industries with types of handicraft commodities. Integration of AHP and TOPSIS methods has been successfully used in the IKM Development Priority Determination Application, with 83.3% precision and 96.4% accuracy achieved by using a confusion matrix so that the IKM ranking can be known. The results of the study found that integration of the two methods was successfully used for Small and Medium Industries Development Decision Making.
IMPLEMENTASI DATA MINING DENGAN ALGORITMA REGRESI LINEAR SEDERHANA UNTUK MEMPREDIKSI NILAI EKSPOR DI KALIMANTAN TIMUR DENGAN APLIKASI RAPIDMINER Rahmah, Sitti Rahmah; Fawait, Aldi Bastiatul
DiJITAC : Digital Journal of Information Technology and Communication DiJITAC, Vol 4 No.2, April 2024
Publisher : Universitas Islam Negeri Sultan Aji Muhammad Idris Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21093/dijitac.v4i2.8963

Abstract

This research aims to determine the development of export value in East Kalimantan. This research data utilizes secondary data obtained directly from the Central Statistics Agency of East Kalimantan Province. The analysis method applied is a simple linear regression algorithm data mining. Research findings reveal that the export value in East Kalimantan in January 2022 - April 2024 up to the predicted export value in May 2024 - December 2024 experienced a decline in the export value in East Kalimantan. With an accuracy in predicting the RMSE value of 3.182%, this means that the predicted percentage of East Kalimantan's export value is classified as very accurate. The hope of this research is that this research will become a reference for decision making for related parties, so that they can find the best strategy to increase export value in East Kalimantan. In order to realize economic improvement in East Kalimantan in the future.
Long Short-Term Memory vs Gated Recurrent Unit: A Literature Review on the Performance of Deep Learning Methods in Temperature Time Series Forecasting Furizal, Furizal; Fawait, Aldi Bastiatul; Maghfiroh, Hari; Ma’arif, Alfian; Firdaus, Asno Azzawagama; Suwarno, Iswanto
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1546

Abstract

Temperature forecasting is a crucial aspect of meteorology and climate change studies, but challenges arise due to the complexity of time series data involving seasonal patterns and long-term trends. Traditional methods often fall short in handling this variability, necessitating more advanced solutions to enhance prediction accuracy. LSTM and GRU models have emerged as promising alternatives for modeling temperature data. This study is a literature review comparing the effectiveness of LSTM and GRU based on previous research in temperature forecasting. The goal of this review is to evaluate the performance of both models using various evaluation metrics such as MSE, RMSE, and MAE to identify gaps in previous research and suggest improvements for future studies. The method involves a comprehensive analysis of previous studies using LSTM and GRU for temperature forecasting. Assessment is based on RMSE values and other metrics to compare the accuracy and consistency of both models across different conditions and temperature datasets. The analysis results show that LSTM has an RMSE range of 0.37 to 2.28. While LSTM demonstrates good performance in handling long-term dependencies, GRU provides more stable and accurate performance with an RMSE range of 0.03 to 2.00. This review underscores the importance of selecting the appropriate model based on data characteristics to improve the reliability of temperature forecasting.
Evolution of the Use of Artificial Intelligence in Mobile Applications to Improve the Efficiency of Public Service Loso Judijanto; Arief Yanto Rukmana; Aldi Bastiatul Fawait; Sitti Rahmah; Sugiarto Sugiarto
West Science Social and Humanities Studies Vol. 2 No. 11 (2024): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v2i11.1457

Abstract

The integration of artificial intelligence (AI) into mobile applications has transformed public service delivery by enhancing efficiency, accessibility, and responsiveness. This study employs a bibliometric approach to analyze the evolution of AI applications in public service, focusing on research trends, key contributors, and thematic developments from 2000 to 2024. The findings reveal a rapid increase in research output since 2018, driven by advancements in enabling technologies such as IoT, 5G, and machine learning, as well as global challenges like the COVID-19 pandemic. Key application areas identified include healthcare, smart cities, and governance, with AI-powered mobile apps demonstrating significant potential in addressing societal needs. However, challenges related to data privacy, algorithmic bias, and technical infrastructure persist. This study underscores the importance of ethical frameworks, interdisciplinary collaboration, and localized solutions to maximize the impact of AI in public service delivery. The findings offer valuable insights for researchers, practitioners, and policymakers seeking to leverage AI for smarter and more equitable public services.
Concerns of Ethical and Privacy in the Rapid Advancement of Artificial Intelligence: Directions, Challenges, and Solutions Furizal, Furizal; Ramelan, Agus; Adriyanto, Feri; Maghfiroh, Hari; Ma'arif, Alfian; Kariyamin, Kariyamin; Masitha, Alya; Fawait, Aldi Bastiatul
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.24090

Abstract

AI is a transformative technology that emulates human cognitive abilities and processes large volumes of data to offer efficient solutions across various sectors of life. Although AI significantly enhances efficiency in many areas, it also presents substantial challenges, particularly regarding ethics and user privacy. These challenges are exacerbated by the inadequacy of global regulations, which may lead to potential abuse and privacy violations. This study provides an in-depth review of current AI applications, identifies future needs, and addresses emerging ethical and privacy issues. The research explores the important roles of AI technologies, including multimodal AI, natural language processing, generative AI, and deepfakes. While these technologies have the potential to revolutionize industries such as content creation and digital interactions, they also face significant privacy and ethical challenges, including the risks of deepfake abuse and the need for improved data protection through platforms like PrivAI. The study emphasizes the necessity for stricter regulations and global efforts to ensure ethical AI use and effective privacy protection. By conducting a comprehensive literature review, this research aims to provide a clear perspective on the future direction of AI and propose strategies to overcome barriers in ethical and privacy practices.
Penerapan Artificial Intelligence untuk Analisis Risiko Proyek Green bonds di Indonesia Judijanto, Loso; Fawait, Aldi Bastiatul
Sanskara Akuntansi dan Keuangan Vol. 3 No. 02 (2025): Sanskara Akuntansi dan Keuangan (SAK)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/sak.v3i02.521

Abstract

The growing need for sustainable financing has positioned Green bonds as an important instrument to fund environmentally friendly projects. However, these projects face various risks, including financial, environmental, and regulatory challenges, especially in emerging markets such as Indonesia. This study explores the application of Artificial Intelligence (AI) in mitigating these risks through qualitative research involving five interviewees from the fields of finance, environment, and technology. Using NVIVO for thematic analysis, the findings highlight the potential of AI in predictive analysis, environmental monitoring, and risk scenario simulation, while overcoming challenges such as data quality, cost, and regulatory inconsistency. This study underscores the transformative role of AI in improving transparency, efficiency, and scalability in green bond risk management, and provides recommendations to stakeholders to foster sustainable finance practices in Indonesia.
Pengambilan Keputusan Rekomendasi Prioritas Bantuan IKM di Kota Samarinda dengan metode AHP dan TOPSIS Rahmah, Sitti; Fawait, Aldi Bastiatul; Jamil, Muh; Arifin, Merlina Lidiana; Saputri, Nadia Keril
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 9, No 1 (2025): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v9i1.19824

Abstract

Industri usaha kecil menengah (IKM) di Kota Samarinda terbilang belum mengalami perkembangan yang maksimal, dengan salah satu hambatannya ialah faktor finansial. Pemerintah mengusulkan program bantuan yang harus tepat sasaran, memerlukan keputusan yang tepat untuk menyeleksi IKM penerima bantuan. Metode yang digunakan adalah Analytical Hierarchy Process (AHP) untuk menentukan bobot kriteria dan Technique for Other Reference by Similarity to Ideal Solution (TOPSIS) untuk menentukan prioritas bantuan sebagai rekomendasi penerima bantuan. Kriteria penentuan penerima bantuan adalah tenaga kerja, investasi, kapasitas produksi, nilai produksi, dan bahan baku. Penelitian ini dilakukan melalui tahap Input, Proses, dan Output. Hasil penelitian membuktikan rasio konsistensi yang dihasilkan sebesar 0,0961 atau <0,1, yang sesuai dengan teori perhitung CR dalam metode AHP. Ranking hasil menggunakan metode TOPSIS menunjukkan bahwa IKM Agus Salim Variasi menempati urutan pertama, UD. Hamas di urutan kedua, dan Bengkel Langgeng Teknik di urutan ketiga, sehingga direkomendasikan sebagai prioritas bantuan. Penelitian ini menemukan bahwa integrasi metode AHP dan TOPSIS efektif untuk pengambilan keputusan rekomendasi prioritas bantuan IKM di Kota Samarinda.
PEMANFAATAN KECERDASAN BUATAN DALAM MENINGKATKAN EFISIENSI BISNIS DAN KEPUTUSAN MANAJERIAL Kohar , Abdul; Fawait, Aldi Bastiatul; Hendratri, Bhaswarendra Guntur; Huda, Syafa'at Ariful; Darmun, Darmun; Wartono, Tono
Jurnal Review Pendidikan dan Pengajaran Vol. 8 No. 2 (2025): Volume 8 No. 2 Tahun 2025
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jrpp.v8i2.45729

Abstract

Penelitian ini bertujuan untuk menganalisis pemanfaatan teknologi kecerdasan buatan (Artificial Intelligence/AI) dalam pengambilan keputusan bisnis pada era digital. Dalam dunia bisnis modern, kecepatan dan akurasi dalam pengambilan keputusan menjadi faktor penentu keberhasilan, sehingga adopsi teknologi mutakhir seperti AI menjadi sangat relevan. Penelitian ini menggunakan metode studi literatur dengan menganalisis berbagai jurnal ilmiah nasional yang relevan dan terbit pada tahun 2024. Hasil studi menunjukkan bahwa AI memiliki peran strategis dalam meningkatkan efisiensi operasional, menganalisis data besar secara real time, serta memberikan rekomendasi keputusan yang berbasis algoritma dan pembelajaran mesin. AI tidak hanya membantu perusahaan besar dalam merumuskan strategi, tetapi juga mendukung pengembangan UMKM dalam menghadapi tantangan pasar yang kompleks. Pemanfaatan AI dalam sistem informasi manajemen, proses otomasi bisnis, dan transformasi intelijen bisnis terbukti mampu meningkatkan daya saing organisasi. Meskipun demikian, penelitian juga menemukan tantangan dalam bentuk kesiapan infrastruktur teknologi, literasi digital sumber daya manusia, serta aspek etika dan keamanan data. Oleh karena itu, integrasi AI dalam proses pengambilan keputusan bisnis perlu diiringi dengan kebijakan yang adaptif dan edukasi berkelanjutan. Penelitian ini memberikan kontribusi teoretis dan praktis bagi pengembangan strategi bisnis berbasis teknologi di era digital.
Edukasi Dasar Kecerdasan Buatan Untuk Siswa di SMA Negeri 12 Samarinda: Pengabdian Aldi Bastiatul Fawait; Sitti Rahmah; Yudhi Fajar Saputra; Sugiarto; La Jupriadi Fakhri; Merlina Lidiana Arifin; Edwin Pramudya; Nelson Sompa Arifin
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 1 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 1 (Juli 2025 -
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i1.2488

Abstract

Kegiatan pengabdian kepada masyarakat berupa edukasi dasar kecerdasan buatan (Artificial Intelligence/AI) telah dilaksanakan di SMA Negeri 12 Samarinda dengan tujuan untuk meningkatkan literasi teknologi di kalangan pelajar. Kegiatan ini berlangsung selama satu hari dan diikuti oleh 47 siswa, didampingi oleh dua orang dosen serta dibantu oleh mahasiswa Program Studi Ilmu Komputer Universitas Widya Gama Samarinda. Materi yang disampaikan berfokus pada pengenalan AI sebagai teknologi yang mampu menangani tugas-tugas kognitif seperti pembelajaran, pemecahan masalah, dan pengenalan pola. Berdasarkan hasil evaluasi dari 10 pertanyaan angket, pelatihan ini menunjukkan hasil yang positif, di mana sebagian besar peserta berada pada kategori “Cukup Mengerti” (69,84%) dan “Sangat Mengerti” (18,99%), sementara hanya sebagian kecil yang “Kurang Mengerti” (13,12%) dan tidak ada peserta yang “Tidak Mengerti” (0%). Hasil tersebut mengindikasikan bahwa pelatihan ini berhasil memberikan pemahaman dasar yang baik mengenai AI kepada siswa. Kegiatan ini juga menunjukkan potensi besar dalam mengembangkan Sumber Daya Manusia (SDM) lokal yang adaptif terhadap kemajuan teknologi, serta layak untuk dilanjutkan dalam skala yang lebih luas sebagai bagian dari upaya meningkatkan kesiapan generasi muda dalam menghadapi tantangan era digital.
Co-Authors Abiyajid Bustami Adriyanto, Feri Agry Alfiah Aisyah Nursyam Alfian Ma’arif ALYA MASITHA Andi Hasyim Anton Yudhana Arief Yanto Rukmana Arifin, Merlina Lidiana Asno Azzawagama Firdaus Bayu Pamungkas Darmun, Darmun Dedi Zulkarnain Pulungan Dodi Irawan Dony Andrasmoro Edwin Pramudya Eko Prasetio Widhi Fahmi, Miftahuddin Farida Arinie Soelistianto Furizal Furizal Furizal, Furizal Hendratri, Bhaswarendra Guntur Hersiyati Palayukan Hidayatus Sibyan Huda, Syafa'at Ariful Jamil, Muh Jamil, Muh Jamil Judijanto, Loso Kariyamin, Kariyamin Kohar , Abdul La Jupriadi Fakhri La Jupriadi Fakhri Loso Judijanto M. Fajar Rizky Maghfiroh, Hari Mardiati Mardiati Merlina Lidiana Arifin Merlina Lidiana Arifin Milkhatun, Milkhatun Muh. Jamil Muhamad Fuat Asnawi Muhammad Kunta Biddinika Nadia Keril Saputri Nelson Sompa Arifin Nursalim Nursyam, Aisyah Puteri Aprilani Rahmah, Sitti Rahmah Rahmawati Rahmawati Ramelan, Agus Reviandari Widyatiningtyas, Reviandari Rizky Wardhani Rosmasari Rosmasari, Rosmasari Rusdi Umar Saputra, Yudhi Fajar Saputri, Nadia Keril Sara Hussain Sitti Rahmah Sitti Rahmah Sitti Rahmah Sitti Rahmah Rahmah Sri Nur Hidayati Sugiarto Sugiarto Sugiarto S Sulung Alfianto Akbar Sunardi, Sunardi Suwarno, Iswanto Syaifullah, Ahmad Syekh Budi Syam Thitus Gilaa Vann Sok Virasanty Muslimah Wartono, Tono wati, asiah Yana Mulyana Yudhi Fajar Saputra Yudhi Fajar Saputra Yulindawati Yulindawati, Yulindawati Yusriati, Yusriati Zhang Li