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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL REKAYASA TEKNOLOGI INFORMASI Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat METIK JURNAL 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 Engineering, Science and Information Technology 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 Scientific Journal of Engineering Research Journal of Computer Science Advancements Techno Agriculturae Studium of Research Research of Scientia Naturalis Journal of Multidisciplinary Sustainability Asean Jurnal Pengabdian Masyarakat Nusantara OBOR: Oikonomia Borneo Journal of Social Science Utilizing Technology Journal of Multidisciplinary Informatics, Artificial Intelligence, and Business Innovation
Aldi Bastiatul Fawait Fawait
Universitas Widya Gama Mahakam Samarinda
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Efektivitas dan Hambatan Pengelolaan Zakat Produktif di Samarinda (Studi Kasus pada LAZ DPU KALTIM Sugiarto; Abiyajid Bustami; Aldi Bastiatul Fawait
OBOR: Oikonomia Borneo Vol. 8 No. 1 (2026): April
Publisher : University of Widya Gama Mahakam Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/obor.v8i1.3987

Abstract

Zakat produktif semakin diposisikan sebagai instrumen strategis dalam keuangan sosial Islam karena tidak hanya ditujukan untuk memenuhi kebutuhan konsumsi jangka pendek, tetapi juga diarahkan pada penguatan kapasitas ekonomi dan kemandirian mustahik. Namun demikian, implementasi program zakat produktif pada tingkat lokal masih menghadapi berbagai tantangan manajerial dan kelembagaan yang memengaruhi keberlanjutan program. Penelitian ini bertujuan menganalisis efektivitas dan hambatan pengelolaan zakat produktif pada LAZ DPU Kaltim di Kota Samarinda. Penelitian menggunakan pendekatan kualitatif deskriptif dengan desain studi kasus. Pengumpulan data dilakukan pada Januari– Maret 2026 melalui wawancara mendalam, observasi lapangan, studi dokumentasi, dan telaah formulir penilaian kelayakan mustahik. Informan penelitian terdiri atas dua amil dan empat mustahik. Hasil penelitian menunjukkan bahwa pengelolaan zakat produktif telah menggunakan mekanisme asesmen multidimensi dan penjaringan berbasis komunitas. Namun demikian, masih ditemukan kendala berupa ketidaksesuaian administrasi domisili, keterbatasan kompetensi kewirausahaan penerima, durasi monitoring yang singkat, proses penilaian manual, serta lemahnya orientasi keberlanjutan usaha. Penelitian ini menawarkan perspektif efektivitas zakat produktif berbasis proses kelembagaan yang menekankan kesiapan penerima, pendampingan ahli, digitalisasi asesmen, dan monitoring jangka menengah sebagai faktor penentu keberlanjutan pemberdayaan.
Analysis of Student Acceptance of SPADA E-Learning Using UTAUT Method Syekh Budi Syam; Muh. Jamil; Aldi Bastiatul Fawait
Jurnal Informasi dan Teknologi 2024, Vol. 6, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v6i3.590

Abstract

SPADA UWGM is an e-learning platform used by Widyagama Mahakam University Samarinda (UWGM). This platform has been used since 2020 for the teaching and learning process, both to provide materials, assignments, and quizzes and to take attendance. The use of e-learning is certainly a technological innovation in the field of education. This progress is something that cannot be avoided because it is also strongly supported by the advancement of science, so there needs to be a measurement of the extent to which this e-learning can be accepted from the perception of its users. This study uses the UTAUT method with six variables, namely performance expectancy, effort expectancy, social influence, facilitating condition, use behavior, and Behavioral Intention to measure the level of student acceptance of SPADA UWGM. The questionnaire used was a questionnaire with answer choices in the form of a Likert scale and was processed using the smart PLS application to see the reliability and validity of the questionnaire items and prove the hypothesis between variables with an error tolerance limit of 10%. The results of this study indicate that performance expectancy does not affect behavior intention. While effort expectancy and social influence influence behavior intention. Other things such as facilitation conditions and behavioral intentions influence use behavior. So based on the research conducted, it can be concluded that the performance of the SPADA UWGM e-learning system does not influence students' interest in using and utilizing the existing e-learning system. Meanwhile, social influence and a sense of trust that the existing system is easy to use have a significant influence on students' efforts and intentions in using the SPADA UWGM e-learning system. Other things such as the condition of campus facilities in supporting the use of the system have an influence on students' seriousness in using the e-learning system, which means that the better the facilities, the more students' motivation will increase in utilizing SPADA UWGM sustainably.
Ensemble Learning untuk Model Prediksi Risiko Preeklamsia dan Explainable AI Berbasis SHAP Yudhi Fajar Saputra; Milkhatun; Mahmoud Ahmad Al-Khasawneh; Yazeed Al Moaiad; Aldi Bastiatul Fawait; Sitti Rahmah; Zakaria Ahmad Dahlan
METIK Jurnal Vol. 10 No. 1 (2026): METIK Jurnal Issue Published
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/kp377403

Abstract

Preeclampsia is a pregnancy complication that poses significant risks to both mother and fetus. Early prediction of preeclampsia risk is crucial to improve maternal healthcare outcomes. This study aims to develop a predictive model for preeclampsia risk using ensemble learning approaches and to enhance model interpretability through Explainable Artificial Intelligence (XAI). The dataset consists of 332 pregnant women who received antenatal care, with 330 complete clinical records after data cleaning. Two ensemble learning algorithms, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), were implemented and evaluated using Receiver Operating Characteristic (ROC) curves, Area Under the Curve (AUC), and additional classification metrics. The best-performing model was further analyzed using SHapley Additive exPlanations (SHAP) to assess feature contributions at both global and individual levels. The results indicate that XGBoost outperformed Random Forest with an AUC of 0.81 compared to 0.72 after applying class weighting and 5-fold cross-validation. XGBoost also demonstrated more balanced performance with an accuracy of 0.83, recall of 0.85, and specificity of 0.60. In contrast, Random Forest achieved an accuracy of 0.91 and specificity of 0.98 but failed to detect positive cases, with a recall of 0.00, indicating bias toward the majority class. SHAP analysis reveals that height, weight, age at menarche, and the number of antenatal care (ANC) visits significantly influence prediction, while hypertension consistently contributes to increased risk. This study demonstrates that integrating ensemble learning with XAI improves both predictive performance and model transparency for preeclampsia risk assessment.
IMPLEMENTASI DATA MINING DENGAN ALGORITMA REGRESI LINEAR SEDERHANA UNTUK MEMPREDIKSI NILAI EKSPOR DI KALIMANTAN TIMUR DENGAN APLIKASI RAPIDMINER Sitti Rahmah Rahmah; Aldi Bastiatul Fawait
DiJITAC : Digital Journal of Information Technology and Communication DiJITAC, Vol 5 No.1, Oktober 2024
Publisher : Universitas Islam Negeri Sultan Aji Muhammad Idris Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21093/dijitac.v5i1.8952

Abstract

Penelitian ini bertujuan untuk mengetahui perkembangan nilai ekspor di Kalimantan Timur. Data penelitian ini memanfaatkan data sekunder yang didapatkan langsung dari Badan Pusat Statistik Provinsi Kalimantan Timur. Metode analisis yang diterapkan adalah data mining algoritma regresi linear sederhana. Temuan penelitian mengungkapkan bahwa nilai ekspor di Kalimantan Timur pada bulan Januari 2022 - April 2024 hingga prediksi nilai ekspor bulan Mei 2024 – Desember 2024 mengalami penurunan nilai ekspor di Kalimantan Timur. Dengan akurasi prediksi nilai RMSE sebesar 3,182% artinya persentase prediksi nilai ekspor Kalimantan Timur tergolong dalam kategori sangat akurat. Harapan dari penelitian ini adalah penelitian ini menjadi acuan pengambilan Keputusan pihak-pihak terkait, agar dapat mencari strategi terbaik untuk meningkatkan nilai ekspor di Kalimantan Timur. Agar terwujudnya peningkatan perekonomian di Kalimantan Timur pada waktu mendatang.
Peningkatan Wawasan Statistika pada Siswa SMK Muhammadiyah Loa Janan Sitti Rahmah; Muh. Jamil; Aldi Bastiatul Fawait; Yudhi Fajar Saputra; Yulindawati
JURPIKAT Vol 7 No 2 (2026)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v7i2.3097

Abstract

Rendahnya literasi statistika siswa di SMK Muhammadiyah Loa Janan menjadi dasar pelaksanaan program Pengabdian kepada Masyarakat (PKM). Permasalahan ini penting karena penguasaan statistika merupakan bagian dari kompetensi numerasi yang diperlukan oleh lulusan SMK dalam menghadapi dunia kerja serta pengambilan keputusan berbasis data. Berdasarkan hasil observasi dan wawancara dengan guru, sebagian besar siswa masih mengalami kesulitan dalam memahami konsep dasar statistika, seperti pengumpulan, penyajian, dan interpretasi data. Kondisi tersebut dipengaruhi oleh rendahnya kemampuan dasar matematika yang berdampak pada menurunnya motivasi serta kepercayaan diri siswa dalam pembelajaran. Program ini bertujuan untuk meningkatkan literasi statistika siswa melalui pembelajaran interaktif berbasis modul kontekstual serta menilai efektivitasnya. Kegiatan melibatkan 40 siswa kelas XII, satu guru pendamping, empat dosen, dan dua mahasiswa. Tahapan kegiatan meliputi sosialisasi, pelatihan interaktif melalui diskusi, simulasi, latihan soal, serta evaluasi menggunakan post-test. Analisis data menggunakan uji chi-square (goodness of fit). Hasil menunjukkan adanya perbedaan distribusi nilai yang signifikan (χ² hitung = 26,02 > χ² tabel = 11,07; α = 0,05) dengan dominasi kategori rendah dan sedang.
Peningkatan Pemahaman Siswa Sekolah Menengah Kejuruan terhadap Pengolahan Citra Digital dan Computer Vision melalui Kegiatan Edukasi dan Praktik Sederhana Muh Jamil; Sitti Rahmah; Aldi Bastiatul Fawait; Yudhi Fajar Saputra
JURPIKAT Vol 7 No 2 (2026)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v7i2.3140

Abstract

Pesatnya perkembangan teknologi berbasis Computer Vision membuat berbagai aplikasi pengolahan citra menjadi semakin mudah untuk digunakan oleh siswa. Namun, kemudahan tersebut tidak selalu diikuti dengan pemahaman mengenai bagaimana teknologi tersebut bekerja. Kegiatan pengabdian ini bertujuan untuk memberikan pemahaman dasar mengenai pengolahan citra digital dan Computer Vision kepada siswa sekolah menengah kejuruan. Kegiatan ini dilaksanakan melalui penyampaian materi dan praktik sederhana menggunakan Google Teachable Machine, kemudian dievaluasi melalui pretest dan posttest. Hasil analisis menunjukkan bahwa sebagian besar indikator mengalami peningkatan yang signifikan (p < 0,05). Di sisi lain, siswa juga menunjukkan respon yang sangat positif dengan tingkat minat dan persepsi yang berada pada kategori tinggi hingga sangat tinggi. Meskipun demikian, beberapa konsep dasar seperti pixel dan resolusi masih perlu diperdalam. Namun secara keseluruhan, kegiatan ini mampu meningkatkan pemahaman sekaligus menumbuhkan ketertarikan siswa terhadap teknologi Computer Vision.
Applications of Artificial Intelligence in Weather Prediction and Agricultural Risk Management in India Aldi Bastiatul Fawait; Puteri Aprilani; Sugiarto Sugiarto; Vann Sok
Techno Agriculturae Studium of Research Vol. 1 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/agriculturae.v1i3.1591

Abstract

Agriculture in India is particularly vulnerable to climate change and extreme weather conditions, which can negatively impact productivity and food security. This research was conducted against the background of the importance of developing technology to help farmers in dealing with weather uncertainty and managing agricultural risks. The purpose of this study is to explore the application of artificial intelligence (AI) in accurately predicting weather as well as managing the risks associated with extreme weather in India's agricultural sector. This study uses a descriptive method with a quantitative and qualitative approach, where data is collected through interviews with agricultural experts, analysis of historical weather data, and AI modeling. The results show that the AI application is able to predict weather patterns with an accuracy rate of up to 90%, which helps farmers make more informed decisions regarding planting timing, irrigation, and pesticide use. In addition, AI-based risk management systems allow for early detection of extreme weather, thereby reducing crop losses. The conclusion of the study is that artificial intelligence applications have great potential to improve food security and agricultural productivity in India by helping farmers anticipate weather changes and manage risks more efficiently. However, the adoption of this technology requires adequate training and infrastructure to ensure its optimal use in the field.
Impact of Using Big Data Analisys in Increasing Personalization of Learning Rahmawati Rahmawati; Nursalim Nursalim; Agry Alfiah; Andi Hasyim; Aldi Bastiatul Fawait
Journal of Computer Science Advancements Vol. 2 No. 2 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i2.906

Abstract

In today’s digital era, big data analytics has become a very relevant topic to improve learning personalisation as it can collect and analyse very large and complex data. Big data analytics can lead to a more efficient learning system by collecting and analysing huge and complex data. In education, big data analytics can be used to understand students’ learning behaviour, their needs and preferences, so that learning and learning outcomes can be improved. This research is conducted with the aim of using big data analytics to improve learning personalisation. It also aims to find out the challenges of using big data analytics to improve learning personalisation. The method used in this research is quantitative method. This method is a way of collecting numerical data that can be tested. Data is collected through the distribution of questionnaires addressed to students. Furthermore, the data that has been collected from the distribution of the questionnaire, will be accessible in Excel format which can then be processed with SPSS. From the research results, it can be seen that the big data analysis has shown that the use of more detailed and accurate data can help teachers find students’ special needs and improve learning effectiveness. As a result, teachers can create learning strategies that are better suited to students’ needs and improve their learning outcomes. From this study, we can conclude that the use of big data analytics in improving personalisation allows teachers to understand better the individual needs and preferences of students, so that more suitable learning plans can be developed and student engagement can be improved.
The Impact of Using Collaborative Learning Platforms on Increasing Student Creativity Rizky Wardhani; Dedi Zulkarnain Pulungan; Dodi Irawan; Thitus Gilaa; Aldi Bastiatul Fawait
Journal of Computer Science Advancements Vol. 2 No. 2 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i2.1082

Abstract

One of the student-centred learning (SCL) methods is collaborative learning. In collaborative learning, students are required to actively participate in learning together or in groups. And collaborative learning is also based on the needs of students to improve the quality of learning. This research is conducted to find out how the use of collaborative learning platforms can help students become more creative in collaborative activities. By understanding the different types of collaborative learning platforms, teachers and parents are able to incorporate the role of technology in students' learning process. In conducting this research, researchers used quantitative methods in the implementation of the research. The data obtained by researchers was obtained through distributing questionnaires presented by researchers through a goggle from application. The distribution of this questionnaire was carried out by researchers online, which then the results of the acquisition of the distribution of this questionnaire will be processed using an SPSS application.  From this research, the researcher can conclude that the impact of using a collaborative learning platform on increasing student creativity shows positive results. With the use of collaborative learning platform, it can visualise abstract and complex concepts, opening opportunities for students to develop their imagination and creativity through rich visual exposure. Based on the results of this study, it shows that collaborative learning platform can enhance students' creativity as it allows students to interact more actively and interactively during the learning process. In addition, rich visual exposure enables better understanding and enhances students' creativity and imagination.
The Impact of Adaptive Learning Technology on Improving Students’ Concept Understanding Farida Arinie Soelistianto; Dony Andrasmoro; Yusriati Yusriati; Mardiati Mardiati; Aldi Bastiatul Fawait
Journal of Computer Science Advancements Vol. 2 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i3.1176

Abstract

Adaptive learning technology is an educational method that uses artificial intelligence and computer algorithms. This learning system can manage students’ interaction pattern during learning activities. The use of adaptive learning technology is able to change students from just receiving information to an active and collaborative part in the learning process. This research was conducted with the aim of improving the quality of education in Indonesia by encouraging teachers to use this technology. This research also aims to provide a better understanding of the potential and weaknesses of adaptive learning technology in improving students’ concept understanding as well as providing stronger guidance for curriculum development and better educational practices.  The method used in this research is quantitative method. This method is a way of collecting numerical data that can be tested. Data is collected through the distribution of questionnaires addressed to students. Furthermore, the data that has been collected from the distribution of the questionnaire, will be accessible in Excel format which can then be processed with SPSS. From the results of the study, it can be seen that the impact of using adaptive learning technology shows that adaptive learning technology can improve the quality of education. Research shows that with the use of adaptive learning technology, it can change teaching methods, learning materials, and can find out the level of learning difficulties faced by these students. From this study, researchers can conclude that the impact of using adaptive learning technology, can improve student understanding and achievement and has the potential to improve the quality of education. with the existence of adaptive learning technology, it is able to increase student involvement and motivation in learning, so that student understanding in learning can be achieved well.
Co-Authors Abiyajid Bustami Agry Alfiah Ahmad Fadilla Aisyah Nursyam Alfian Ma’arif ALYA MASITHA Andi Hasyim Andrian Anye Anton Yudhana Apolonia Diana Sherly da Costa Arief Yanto Rukmana Arifin, Merlina Lidiana Asno Azzawagama Firdaus Asno Azzawagama Firdaus Aulita Az'Zahra Dhena Aldy Bayu Pamungkas Bernardo Damian De Ornay Cecillia Listia Anggraini Dadang Muhammad Hasyim Darmun, Darmun Dedi Zulkarnain Pulungan Dodi Irawan Dony Andrasmoro Edwin Pramudya Eko Prasetio Widhi Elsya Fauziah Fahmi, Miftahuddin Farida Arinie Soelistianto Ferdinandus Heru Moreno Christian Paran Feri Adriyanto Furizal Furizal Furizal, Furizal Gede Enos Karli Gregorivo Hizkia Brighita Totopandey Haviluddin Haviluddin Hendratri, Bhaswarendra Guntur Hendrikus Hang Himang Hersiyati Palayukan Hidayatus Sibyan Huda, Syafa'at Ariful Jamil, Muh Jamil, Muh Jamil Judijanto, Loso Kariyamin, Kariyamin Klara Bare Nuhan Kohar , Abdul La Jupriadi Fakhri La Jupriadi Fakhri Leo nakanisi aran Lisnawati Loso Judijanto M. Fajar Rizky Maghfiroh, Hari Mahmoud Ahmad Al-Khasawneh Marcello Fellix Febrian Mardiati Mardiati Maria Kristiana Damayanti Teting Maslim Tammaling Merlina Lidiana Arifin Merlina Lidiana Arifin Milkhatun Milkhatun, Milkhatun Muh. Jamil Muhamad Fuat Asnawi Muhammad Kunta Biddinika Nadia Keril Saputri Nazaruddin Insyroh Nelson Sompa Arifin Nelson Sompa Arifin Norsianalara Nursalim Nursyam, Aisyah Otniel Christovel Ganda Puteri Aprilani Rahmah, Sitti Rahmah Rahmawati Ramelan, Agus Rayner Alfred Reviandari Widyatiningtyas, Reviandari Reyza Febrianto Ridho Aulia Tabliq Sidiq Rizky Wardhani Ronald Alexandre Rosmasari Rosmasari, Rosmasari Rusdi Umar Rywalman Rante Pasang Saputra, Yudhi Fajar Saputri, Nadia Keril Sara Hussain Sherly Virgoila Pidang Sitti Rahmah Sitti Rahmah Sitti Rahmah Sitti Rahmah Sitti Rahmah Sitti Rahmah Sitti Rahmah Rahmah Sopia daud Sri Nur Hidayati Sugiarto Sugiarto Sugiarto S Sulung Alfianto Akbar Sunardi, Sunardi Suwarno, Iswanto Syaifullah, Ahmad Syekh Budi Syam Thitus Gilaa Vann Sok Vinsensia Florince Seke Virasanty Muslimah Wartono, Tono wati, asiah Yana Mulyana Yazeed Al Moaiad Yazeed Al Moaiad Yohanes Andriano Teras Yovi Aldiyanto Yudhi Fajar Saputra Yudhi Fajar Saputra Yudhi Fajar Saputra Yudhi Saputra Yulindawati Yulindawati, Yulindawati Yusriati, Yusriati Zakaria Ahmad Dahlan Zhang Li