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All Journal JURNAL PENELITIAN ILMU PENDIDIKAN QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama Pendas : Jurnah Ilmiah Pendidikan Dasar Islamika : Jurnal Ilmu-Ilmu Keislaman Aplikasia: Jurnal Aplikasi Ilmu-Ilmu Agama JOURNAL OF SCIENCE AND SOCIAL RESEARCH YUME : Journal of Management EDUKATIF : JURNAL ILMU PENDIDIKAN VISIO DEI: JURNAL TEOLOGI KRISTEN Jurnal Ilmiah Profesi Pendidikan Manna Rafflesia Journal of Civil Engineering and Planning (JCEP) Indonesian Journal of Primary Science Education (IJPSE) Jurnal Development Jurnal Prajaiswara CENDEKIA: Jurnal Ilmiah Pendidikan SWARNA Polinomial : Jurnal Pendidikan Matematika Jurnal Pendidikan Dasar Dharmawangsa: International Journal of the Social Sciences, Education and Humanitis Analisis Gender dan Agama Indonesian Journal of Advanced Research (IJAR) Journal of Computer Science and Research Jurnal Portal Sipil International Asia Of Law and Money Laundering (IAML) International Journal of Islamic Studies Higher Education Jurnal Al Kahfi : Jurnal Pendidikan Agama Islam Jurnal Kala Nea KAFFAH: Jurnal Pendidikan dan Sosio Keagamaan GEMBIRA (Pengabdian Kepada Masyarakat) Nomico Journal of Technology and Computer (JOTECHCOM) Jurnal Abdimas UM Jambi IPSSJ
Adi Putra
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Transportation Other

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Education Philosophical Dimensions of Artificial Intelligence in Islamic Religious and Legal Education Putra, Adi; Efendi, Roni; Putra, Pristian Hadi; Ramadani, Laili
Islamika : Jurnal Ilmu-Ilmu Keislaman Vol. 25 No. 2 (2025): Islamika: Jurnal Ilmu-Ilmu Keislaman
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat, Institut Agama Islam Negeri (IAIN) Kerinci, Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32939/islamika.v25i2.6110

Abstract

Kecerdasan Buatan (Artificial Intelligence/AI) kini menjadi elemen penting dalam pendidikan modern, termasuk dalam studi Islam dan pendidikan hukum. Meskipun AI menawarkan efisiensi dan akses informasi yang luas, penggunaannya yang cepat memerlukan refleksi filosofis agar tidak menggeser nilai dasar pendidikan. Penelitian ini menggunakan metode studi kepustakaan atau yuridis normatif yang dipadukan dengan pendekatan komparatif dan analisis kualitatif untuk menelaah perubahan yang ditimbulkan AI terhadap proses pembelajaran. Secara ontologis, ketergantungan pada AI mengubah pola interaksi belajar dari hubungan langsung antarpendidik dan peserta didik menjadi proses yang lebih dimediasi teknologi. Dari sisi epistemologis, tantangan utama ialah menjaga keaslian produksi dan penyampaian pengetahuan ketika alat AI dapat memengaruhi cara berpikir yang sebelumnya dibangun melalui upaya manusia. Secara aksiologis, pemanfaatan AI harus berada dalam batas etika, moral, dan integritas akademik agar tidak mengurangi nilai-nilai dasar pembelajaran. Penelitian ini menekankan pentingnya kebijakan pendidikan Agma Islam yang seimbang antara penggunaan AI dan penguatan kompetensi manusia. Rekomendasi utama mencakup penyusunan pedoman literasi AI yang sesuai dengan kebutuhan pendidikan Agama Islam dan hukum, serta pengembangan sistem evaluasi yang menekankan orisinalitas dan proses. Dengan demikian, AI dapat berfungsi sebagai alat pendukung tanpa menghilangkan nilai kemanusiaan dalam pendidikan.
Comparative Study of Machine Learning Approaches Based on Artificial Neural Network, Regression, and Clustering for Diabetes Prediction Nauval Alfarizi; Adi Putra; Prima Lydia Yosophin Batubara; Satria Sinurat
Journal of Computer Science and Research (JoCoSiR) Vol. 3 No. 3 (2025): July: Health Science Informatic
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

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Abstract

This study presents a comparative analysis of three machine learning model and algorithms Artificial Neural Network (ANN), Logistic Regression, and K-Means Clustering using the Pima Indians Diabetes dataset. The main objective is to evaluate the performance of supervised and unsupervised methods in predicting diabetes based on physiological and clinical features. he ANN model was developed using a feedforward and backpropagation approach, Logistic Regression applied the fundamental logit equation, and K-Means Clustering was employed as an unsupervised reference. Model performance was assessed using Accuracy, Precision, Recall, and F1-score for supervised models, and Adjusted Rand Index (ARI) for clustering. Experimental results indicate that Logistic Regression achieved the best accuracy of 0.7573, followed by ANN with 0.7078, while K-Means obtained an ARI of 0.1614. The heatmap comparison shows that supervised models outperform unsupervised approaches, with Logistic Regression offering better interpretability and stability, and ANN demonstrating the ability to model nonlinear relationships. K-Means, though less accurate, provided valuable insight into data structure and natural grouping. Overall, the findings confirm that supervised learning models, particularly Logistic Regression and ANN, are more effective for medical prediction tasks. Future research may explore hybrid or ensemble models that combine the interpretability of Logistic Regression, the adaptability of ANN, and the exploratory capability of clustering to enhance medical diagnostic performance.
ANALISIS PENANGANAN DATA TIDAK SEIMBANG TERHADAP KINERJA KLASIFIKASI SENTIMEN MULTIKELAS PADA ULASAN MARKETPLACE TOKOPEDIA Alfarizi, Nauval; Sinurat, Satria; Putra, Adi; Amin, Muhammad; Lydia, Prima
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5804

Abstract

Abstract: The development of digital marketplaces has led to an increasing number of user reviews, which can be used to understand consumer perceptions of products and services. However, sentiment analysis in marketplace reviews faces a major challenge: class imbalance, where positive sentiment often dominates to an extreme. This study aims to analyze the effects of various imbalanced data-handling techniques on the performance of machine-learning-based multiclass sentiment classification in Tokopedia marketplace reviews. The dataset used consists of 56,981 reviews with three sentiment classes, with more than 97% of them being positive. Feature extraction was performed using the TF-IDF method, resulting in 17,765 features. The handling of data imbalance was tested through four scenarios: class weighting, Random Oversampling, SMOTE, and ADASYN, with the Naive Bayes, Logistic Regression, and Random Forest algorithms. The experimental results show that Random Forest with SMOTE achieves the highest accuracy of 0.9749 but has limitations in recognizing minority classes, with a recall of 0.3786. In contrast, Logistic Regression with Random Oversampling provides the most balanced performance with the highest F1-score (macro) value of 0.4992 and recall of 0.5866. Keywords: Analysis, Sentiment, Imbalanced Data, Multi-Class Classification F1-Score Abstrak: Perkembangan marketplace digital menyebabkan meningkatnya jumlah ulasan pengguna yang dapat dimanfaatkan untuk memahami persepsi konsumen terhadap produk dan layanan. Namun, analisis sentimen pada ulasan marketplace menghadapi tantangan utama berupa ketidakseimbangan distribusi kelas, di mana sentimen positif sering kali mendominasi secara ekstrem. Penelitian ini bertujuan untuk menganalisis pengaruh berbagai teknik penanganan data tidak seimbang terhadap kinerja klasifikasi sentimen multikelas pada ulasan marketplace Tokopedia berbasis machine learning. Dataset yang digunakan terdiri dari 56.981 ulasan dengan tiga kelas sentiment, di mana proporsi sentimen positif mencapai lebih dari 97%. Ekstraksi fitur dilakukan menggunakan metode TF-IDF yang menghasilkan 17.765 fitur. Penanganan ketidakseimbangan data diuji melalui empat skenario, yaitu class weighting, Random Oversampling, SMOTE, dan ADASYN, dengan algoritma Naive Bayes, Logistic Regression, dan Random Forest. Hasil eksperimen menunjukkan bahwa Random Forest dengan SMOTE menghasilkan akurasi tertinggi sebesar 0,9749, namun memiliki keterbatasan dalam mengenali kelas minoritas dengan nilai recall 0,3786. Sebaliknya, Logistic Regression dengan Random Oversampling memberikan performa paling seimbang dengan nilai F1-score (macro) tertinggi sebesar 0,4992 dan recall 0,5866. Kata kunci: Analisis, Sentimen, Data Tidak Seimbang, Klasifikasi Multi Kelas F1-Score
Constitutional Responsibility of the State for the Protection of the Right to Health in the Implementation of the Free Nutritious Meal Program Putra, Adi
International Asia Of Law and Money Laundering (IAML) Vol. 4 No. 4 (2025): International Asia Of Law and Money Laundering (IAML)
Publisher : International Asia Of Law and Money Laundering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59712/iaml.v4i4.150

Abstract

This study focuses on the constitutional responsibility of the state for the protection of the right to health in the implementation of the free nutritious food (MBG) Program, by placing mass poisoning events as problematic indicators of the fulfillment of state obligations on children's health rights. The research uses normative juridical methods with constitutional and conceptual approaches, analyzing the obligations of the state based on the 1945 Indonesian constitution, international legal instruments, and legislation related to health and food. The findings show that there is a normative gap between the constitutional guarantee of the right to health and the weak mechanism for implementing social programs in the aspects of supervision, accountability, and legal protection. The state has not fully fulfilled the three dimensions of the constitutional obligation (obligation to respect, protect, and fulfill) in ensuring the food security of the MBG program. The weakness of technical regulations, the fragmentation of supervisory institutions, and the absence of clear accountability mechanisms reflect a disregard for the principles of the welfare state as mandated by the Constitution. This article recommends the reconstruction of a legal framework that integrates the constitutional dimension of the right to health with the operational design of the program, the institutional strengthening of integrated supervision, as well as the affirmation of state accountability mechanisms through administrative, civil and criminal channels. The fulfillment of the constitutional rights of citizens cannot be left solely to market mechanisms or returned to the logic of administrative efficiency, but must be guaranteed through a solid legal infrastructure and an effective accountability system.
Implementation of tahfidz learning using the Tahsin and Tasmi' Methods Yudi Darmawan; Adi Putra; Noprijon
Al-Kahfi: Jurnal Pendidikan Agama Islam Vol. 11 No. 1 (2025): January
Publisher : STAI YAPTIP Simpang Empat Pasaman Barat Indonesia in collaboration with International Islamic Studies Development and Research Center (IISDRC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70820/al-kahfi.v11i1.466

Abstract

Maintaining the memorization of the Qur'an is very important and difficult, therefore it is highly recommended in memorizing the Qur'an for the memorizers to use the tahfidz, tahsin and tasmi' methods continuously. In order to make it easier for them to add memorization and maintain memorization. This study aims to analyze and describe the Implementation of tahfidz tahsin and tasmi' learning in improving the quality of students' memorization of the Qur'an at Mts Darul Yamani, Kejorongan Pisang Hutan, Sasak Ranah Pasisie District, West Pasaman Regency. This study uses a field research method, the type of approach is qualitative, The source of this research data is Primary data obtained through interviews with informants, namely the Principal of MTS Darul Yamani, teachers and students of SMK Darul Yamani regarding the Implementation of tahfidz learning using the tahsin and tasmi' methods at MTS Darul Yamani. Tahfidz learning using the tahsin and tasmi' method at MTS Darul Yamani is implemented once a week so that students understand and memorize the Qur'an more quickly. The form of the method used before teaching must use a learning plan. The implementation process that the tahsin and tasmi' method in tahfidz learning is one of the lessons to support the Qur'an tahfidz program. As well as evaluation of the implementation of tahfidz learning using the tahsin and tasmi' method is that at the end of each semester, MTS Darul Yamani holds an Al-Qur'an memorization test to evaluate student achievement. Students must meet the memorization targets that have been set according to their class level and supporting factors in the implementation of tahfidz learning using the Tahsin and tasmi' method are that the tahfidz program gets full support from the school, parental encouragement and student interest in participating in tahfidz learning. The inhibiting factors are due to sin and immorality, intentions that are not sincere because of Allah SWT and being full. The implications of this research can be used as initial data for subsequent researchers in studying this problem in different contexts and issues.
Comparative Machine Learning Analysis for Sentiment Classification of Sumatra Disaster 2025 Alfarizi, Nauval; Lydia, Prima; Novelan, Muhammad Syahputra; Putra, Adi; Sinurat, Satria
Journal of Technology and Computer Vol. 3 No. 1 (2026): February 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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

Abstract

Indonesia is highly vulnerable to natural disasters due to its geological position, resulting in extensive disaster-related news coverage that shapes public sentiment. This study presents a comparative machine learning analysis for sentiment classification of online news related to natural disasters in Sumatra during December 2025. The dataset was collected through web scraping from two major Indonesian news portals, like CNN Indonesia and Detik, and categorized into three sentiment classes: negative, neutral, and positive. Sentiment classification was conducted using Naive Bayes, Support Vector Machine (SVM), and k-Nearest Neighbors (KNN) algorithms. The results demonstrate that Naive Bayes achieved accuracy values of 0.57 on the CNN Indonesia dataset and 0.61 on the Detik dataset. However, its performance was highly biased toward the dominant negative class, as indicated by low macro-average F1-scores of (0.24) and (0.39). In contrast, SVM showed the most balanced performance by reducing class bias, achieving accuracies of (0.68) and (0.67) with macro-average F1-scores of (0.51) and (0.59), respectively. KNN demonstrated moderate performance, with accuracy values of 0.60 and 0.59, but remained less effective than SVM in handling minority sentiment classes.
ANALISIS PERAN GURU DALAM MENINGKATKAN MINAT BELAJAR BAHASA INGGRIS DI SEKOLAH DASAR Arya Bintang Prasetyo; Dudung Amir Sholeh; Adi Putra
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 4 (2025): Volume 10. No4, Desember 2025.
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i4.14755

Abstract

The purpose of this study is to determine the roles of teachers in increasing interest in learning English in elementary schools. The research method used is the literature study method by analyzing various previous studies related to this topic. The results of the literature study show that teachers have a very important role in increasing interest in learning English in students at the elementary school level. Because of its very important role, teachers must have broad competence and insight. There are many ways that teachers can use to increase interest in learning English in students at the elementary school level, among which are choosing the method, learning style and learning media that will be used during learning.
PERAN MODEL TGT DALAM MENINGKATKAN CAPAIAN BELAJAR IPA DI TINGKAT SATUAN PENDIDIKAN DASAR: STUDI LITERATUR Damayanti Firdaus, Efrida; Mira Amelia Amri; Adi Putra
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 01 (2026): Volume 11 No. 01 Maret 2026 Public
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i01.42896

Abstract

Science education, known as IPA in elementary schools, plays a crucial role in honing critical thinking skills along with various other transformative competencies needed in the demanding world of the 21st century. However, there are various obstacles faced in science learning, so that students' achievement in science learning in the learning components that include thinking (cognitive), emotional response (affective), and practical skills (psychomotor) are also affected. The Team Games Tournament (TGT) model has become an alternative to encourage improvement in elementary school students' science learning outcomes. Through a descriptive qualitative approach based on a literature study, this article examines ten recent studies that examine the role of TGT in the cognitive, affective, and psychomotor domains of elementary school science learning. The results of the analysis show that the consistent application of TGT improves students' understanding of science concepts (cognitive), motivation (affective), and cooperation (psychomotor) among students. Thus, the TGT model is recommended as the main model in designing science learning at the elementary level, as well as a foundation for further research and development of innovative models.
PEMANFAATAN MEDIA PEMBELAJARAN INTERAKTIF (VIDEO ANIMASI DAN POWERPOINT VISUAL) UNTUK MENINGKATKAN MINAT BELAJAR DAN PEMAHAMAN KONSEP IMAN DALAM PENDIDIKAN AGAMA KRISTEN DI SEKOLAH DASAR Adi Putra
Integrative Perspectives of Social and Science Journal Vol. 3 No. 03 Maret (2026): Integrative Perspectives of Social and Science Journal
Publisher : PT Wahana Global Education

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Abstract

Pembelajaran Pendidikan Agama Kristen (PAK) di Sekolah Dasar seringkali melibatkan konsep-konsep abstrak (misalnya: kasih karunia, keselamatan) yang sulit dipahami oleh siswa usia konkret. Penelitian ini bertujuan untuk membandingkan efektivitas penggunaan media interaktif/visual (video animasi dan presentasi visual) dengan media konvensional (ceramah dan papan tulis) dalam meningkatkan minat belajar dan pemahaman konsep iman siswa. Penelitian ini menggunakan metode Eksperimen Semu (Quasi-Experiment) dengan dua kelompok: kelompok eksperimen (menggunakan media interaktif) dan kelompok kontrol (menggunakan media konvensional), melibatkan 60 siswa kelas IV. Data dikumpulkan melalui angket minat belajar dan tes pemahaman konsep. Hasil menunjukkan bahwa kelompok eksperimen mencapai peningkatan rata-rata skor pemahaman konsep sebesar 25% lebih tinggi dibandingkan kelompok kontrol. Selain itu, minat belajar siswa di kelompok eksperimen meningkat hingga 90% (kategori sangat tinggi). Kesimpulan penelitian ini adalah bahwa pemanfaatan media interaktif/visual secara signifikan meningkatkan keterlibatan siswa dan menjembatani kesulitan pemahaman konsep abstrak dalam PAK.
DIGITALISASI UMKM DESA LANGKAI : STRATEGI PENGUATAN EKONOMI LOKAL DI ERA DIGITAL Alfajri , Muhammad; Fahmi, Ali; Putra, Adi
Jurnal Abdimas UM Jambi Vol. 3 No. 1 (2026): Jurnal Abdimas UM Jambi
Publisher : LPPM Universitas Muhammadiyah Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53978/jaum.v3i1.657

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) merupakan tulang punggung perekonomian masyarakat Indonesia, termasuk di tingkat desa. Namun, tantangan yang dihadapi UMKM saat ini tidak hanya pada proses produksi barang berkualitas, tetapi juga bagaimana memperluas jangkauan pasar. Kegiatan pengabdian masyarakat ini dilakukan di Desa Langkai dengan tujuan mendampingi pelaku UMKM dalam memanfaatkan teknologi digital melalui pelatihan penggunaan media sosial, marketplace, dan aplikasi sederhana untuk promosi produk. Program ini dilaksanakan pada tanggal 07–08 Agustus 2025 dan melibatkan sejumlah UMKM lokal seperti Babussalam Mart, produsen santan kelapa segar, serta industri rumah tangga keripik pisang. Metode yang digunakan meliputi observasi, sosialisasi, dan pendampingan. Hasil kegiatan menunjukkan adanya peningkatan pemahaman pelaku usaha terhadap pentingnya digitalisasi, keterampilan dalam menggunakan platform digital, serta semangat untuk memperluas pasar dari lingkup lokal menuju regional bahkan nasional. Program ini memberikan dampak positif terhadap peningkatan daya saing UMKM sekaligus menjadi langkah awal menuju ekonomi kreatif desa.
Co-Authors Abd Haris, Abd Abdi, Hamdani Abdul, Wahid Afifah Aulia Fitri Alfajri , Muhammad Alfarizi, Nauval Amelia Amri, Mira Amri , Mira Amelia Annisa Dwi Nugraheni Ardian, Heri Arief Fath Atiya Arif, Maulana Arita Marini Arniwita, Arniwita Arya Bintang Prasetyo Astriani, Dea Aulia Rahma Kusumaningtyas Bansa, Yorina An'guna dadang, rahmatul Damayanti Firdaus, Efrida Dani Darmawan Desy Safitri Dewanti, Andini Dewi ANGGRAENI Diah Ayu Ramadhina Dicky Febri Hadi Dimas Alfandi Dudung Amir Sholeh Efendi, Roni Fadilla Zahrah Fahmi Muharomi Dzikri Fahmi, Ali Fauziah, Naila Gunawan Budi Susilo Hairunnisa, Salsa Nurul Harti, Sri Dwi Hasan Basri Irwansyah Irwansyah Islam Madina Januar, Ahmad Juliwis Kardi Kasmitha, Resty Keluanan, Yane Henderina Linda Zakiah Lydia, Prima Marsyaf, Agesha Maulidya, Aisyah Mira Amalia Amri Mira Amelia Amri, Mira Amelia Muhammad Amin Muhammad Sigit Darmawan Muhammad Syahputra Novelan Nadiva Freya Danella Nafa Elifah Khairunnisa Namang, Kezya Thresia Naufal al-Haq Nauval Alfarizi Nedawati, Rika Neldawaty, Rika Nikita Aura Marshanda Nisrina Indy Saqifa Nome, Nehemia Noprijon Nurdin Nurdin Nurzengky Ibrahim Pangestu, Yoga Pasla, Bambang Niko Paulus Suhendro Mbette , Petrus Petrus Suhendro Prima Lydia Yosophin Batubara Purwanto, Vivi Devriana Putra, Iwan Eka Putra, Pristian Hadi Putri Sugiharto, Anggie Putri, Kansa Aura R. Rully Mahendra Rahayu Ningsih, Sri Rahmawati, Sisca Raihan, Regghina Nasywa Ramadani , Laili Rina Wulandari Rizky Hidayat Rumawak, Sarah Agustina Sahari, Gunar Sahputra, Rilawadi Salim, Salsabila Nuramalia Sari Dewi, Lizabeth Satria Sinurat Selan, Yunus Shoalihin Shoalihin Silalahi, Dian Hardian Sinurat, Satria Soleh, Dudung Amir Sri Nuraini Suhendro, Petrus Suhendro, Petrus Paulus Mbette Suherman, Suherman Sujarwo Sunandar Sunandar Tamtomo, Hario Taufik Hidayat Usman, Herlina Uswatun Hasanah Utami, Adinda Desty Dian Veronica, Deca Veronica, Deka Yudi Darmawan Yuliati, Siti Rohmi Yunicha Harly, Aulia Zebua, Marta Novianti Zulhendra, Riko Zuliah, Azmiati