Article Per Year (5 Year)
p-Index From 2021 - 2026
2.282
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Majalah Ilmiah Ekonomi Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Algoritma JURNAL ISTEK JOIN (Jurnal Online Informatika) Al-Fikri: Jurnal Studi dan Penelitian Pendidikan Islam Jurnal Pendidikan UNIGA Jurnal Publik : Jurnal Ilmiah Bidang Ilmu Administrasi Negara Atthulab: Islamic Religion Teaching and Learning Journal JISKa (Jurnal Informatika Sunan Kalijaga) Indonesian Journal of Electrical Engineering and Computer Science JIIP (Jurnal Ilmiah Ilmu Pendidikan) Journal of Applied Data Sciences Edukasi: Journal of Educational Research Jurnal Algoritma Jurnal Lemhannas RI
Muhammad Ali Ramdhani
UIN Sunan Gunung Djati Bandung
Religion Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

Published : 29 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 29 Documents
Search

 1   2   3 
Deep sequential pattern mining for readability enhancement of Indonesian summarization Maylawati, Dian Sa'adillah; Kumar, Yogan Jaya; Kasmin, Fauziah; Ramdhani, Muhammad Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp782-795

Abstract

In text summarization research, readability is a great issue that must be addressed. Our hypothesis is readability can be accomplished by using text representations that keep the meaning of text documents intact. Therefore, this study aims to combine sequential pattern mining (SPM) in producing a sequence of a word as text representation with unsupervised deep learning to produce an Indonesian text summary called DeepSPM. This research uses PrefixSpan as an SPM algorithm and deep belief network (DBN) as an unsupervised deep learning method. This research uses 18,774 Indonesian news text from IndoSum. The readability aspect is evaluated by recall-oriented understudy for gisting evaluation (ROUGE) as a co-selection-based analysis; Dwiyanto Djoko Pranowo metrics, Gunning fog index (GFI), and Flesch-Kincaid grade level (FKGL) as content-based analysis; and human readability evaluation with two experts. The experiment result shows that DeepSPM yields better than DBN, with the F-measure value of ROUGE-1 enhanced to 0.462, ROUGE-2 is 0.37, and ROUGE-L is 0.41. The significance of ROUGE results also be tested using T-Test. The content-based analysis and human readability evaluation findings are conformable with the findings of co-selection-based analysis that generated summaries are only partially readable or have a medium level of readability aspect.
Implementasi Quad Helix Sebagai Upaya Peningkatan Daya Saing Bangsa Ramdhani, Muhammad Ali
Jurnal Lemhannas RI Vol 7 No 3 (2019)
Publisher : Lembaga Ketahanan Nasional Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55960/jlri.v7i3.76

Abstract

Peningkatan teknologi, khususnya pada bidang teknologi informasi memberikan dampak yang signifikan terhadap perubahan tata kehidupan dunia. Dimensi kreativitas dan inovasi memainkan penting dalam meningkatkan kapasitas ekonomi suatu negara. Quad Helix merupakan sistem kolaborasi yang memberikan dorongan pada tumbuhnya industri kreatif dan inovatif . Tujuan penulisan ini adalah membahas tentang implementasi Quad Helix yang dibingkai dalam konsep sismennas sebagai upaya peningkatan daya saing bangsa.
Polarization of Religious Issues in Indonesia’s Social Media Society and Its Impact on Social Conflict Faizin, Barzan; Fitri, Susanti Ainul; AS, Enjang; Maylawati, Dian Sa'adillah; Rizqullah, Naufal; Ramdhani, Muhammad Ali
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.447

Abstract

In this new era, people use social media to share information and discuss political, social, and religious issues, leading to pros and cons arguments. In Twitter’s hashtags and tweets, religious issues frequently trigger a hot conversation that causes disputes among citizens and even street movements. This study is intended to reveal the religious issues that often trigger polarization among Twitter users and how they influence horizontal conflict in society as what happened during the election period in 2019. This research applied mixed methods with social media analytics to conceal religious issues in Indonesia's social media society. The data collection was done by crawling data from the Indonesian Twitter users’ tweets regarding religious issues hashtags, which is a reference for further analysis. The research findings show that the top eight religious issues widely discussed based on 23,433 Twitter users’ tweets are the hashtags (#) salafi, wahabi, intoleransi (intolerance), taliban, anti-Pancasila, politisasi agama (politicization of religion), politik identitas (identity politics), and radikalisme (radicalism). In social conversation networks, these issues are related to each other and other issues such as political figures, the three presidential candidates, the general election, and the Republic of Indonesia presidential election in 2024. Concerning these issues, Twitter users believe that the issues, positive or negative, do not influence their religious and political stance. However, to a certain extent, they believe that religious issues impact social discourses regarding horizontal conflicts. 44% opinions prove this indicated that the debate over religious matters had little influence on their opinion of these topics, and 64.5% agreed that religious concerns can cause social strife. Finally, it is hoped that further studies will elaborate on how religious issues on Twitter and other social media directly impact social harmony in everyday life.
Efektivitas Evaluasi Proses Model Pembelajaran Berbasis Masalah Materi Qurban dan Aqiqah Dzulkifli, Muhamad Arham; Kamil, Muhammad Ihsan; Rizal, Muhammad; Ramdhani, Muhammad Ali; Rochman, Chaerul
Al-Fikri: Jurnal Studi dan Penelitian Pendidikan Islam Vol 5, No 1 (2022): Pendidikan Islam dalam Konteks Multikultural
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/jspi.v5i1.22678

Abstract

In essence, learning is a psychological process or personal event that occurs within each individual. Learning is not an automatic consequence of contemplating information into students' minds, learning requires mental involvement and students' own work. Explanation and demonstration alone will not produce good learning outcomes, but a learning experience that is more related to conceptual elements will make the learning process more effective. One alternative that can be applied in PAI learning is learning activities by applying a problem-based learning model that aims to improve student achievement and motivation in understanding and mastering PAI lessons. This study aims to examine the effectiveness of the problem-based learning model in Islamic religious education lessons on qurban and akikah material. This study uses a quantitative approach, which uses scores to describe the variables of student learning outcomes and the effectiveness of learning implementation. The population in this study were 29 students with 14 female groups and 15 male groups in class IX SMPN 54 Bandung. The data obtained were in the form of answers based on the evaluation of the learning process, namely 13 questions that were answered authentically. The data obtained were then analyzed descriptively. Data was collected using the method. Student learning outcomes showed an average above the KKM (≥80) which was 84%. So that the achievement of the effectiveness of the evaluation of problem-based learning in the qurban and akikah material for the female group was greater, namely 86% compared to the male group, which was lower at 83%.
Enhancing Abstractive Multi-Document Summarization with Bert2Bert Model for Indonesian Language Muharam, Aldi Fahluzi; Gerhana, Yana Aditia; Maylawati, Dian Sa'adillah; Ramdhani, Muhammad Ali; Rahman, Titik Khawa Abdul
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 1 (2025): January 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.1.110-121

Abstract

This study investigates the effectiveness of the proposed Bert2Bert and Bert2Bert+Xtreme models in improving abstract multi-document summarization for Indonesians. This research uses the transformer model to develop the proposed Bert2Bert and Bert2Bert+Xtreme models. This research utilizes the Liputan6 data set, which comprises news data along with summary references spanning 10 years from October 2000 to October 2010, and is commonly used in many automatic text summarization studies. The model evaluation results using ROUGE-1, ROUGE-2, ROUGE-L, and BERTScore indicate that the proposed model exhibits a slight improvement over previous research models, with Bert2Bert performing better than Bert2Bert+Xtreme. Despite the challenges posed by limited reference summaries for Indonesian documents, content-based analysis using readability metrics, including FKGL, GFI, and Dwiyanto Djoko Pranowo, revealed that the summaries produced by Bert2Bert and Bert2Bert+Xtreme are at a moderate readability level, meaning they are suitable for mature readers and align with the news portal’s target audience.
Analysis of Students' Higher Order Thinking Skills (HOTS) in PAI Learning at SMK Marhas Margahayu: Analisis Kemampuan Higher Order Thinking Skills (HOTS) Siswa Dalam Pembelajaran PAI di SMK Marhas Margahayu Fauzi, Rai Ahmad; Ramdhani, Muhammad Ali; Hambali, Adang
Edukasi: Journal of Educational Research Vol. 3 No. 2 (2023)
Publisher : CV. Media Publikasi Profesional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57032/edukasi.v3i2.127

Abstract

This study aims to analyse students' higher order thinking skills (HOTS) in Islamic Religious Education (PAI) subjects, especially at the levels of analysis (C4), evaluation (C5), and creation (C6). This research is important considering the low achievement of Indonesian students' HOTS in the national education evaluation. The method used was descriptive quantitative, with data collection techniques through Google Form-based written tests to 18 students of class XII SMK Marhas Margahayu. The data was analysed using percentage and average score techniques to measure students' ability levels. The results showed that the majority of students were in the low to very low category, with an average score of 51.85. Only a small number of students reached the high category, indicating the potential for HOTS development through appropriate learning strategies. This finding indicates that PAI learning is still dominantly focused on memorisation and has not optimally developed critical and reflective thinking. The implication of this study is the need to improve learning and evaluation strategies in PAI to better encourage students' higher order thinking skills. In an original way, this research contributes to the development of contextualised HOTS-based evaluative instruments in PAI learning at the vocational level and offers an alternative approach in improving the quality of religious learning in vocational schools.
Determinant Factors in the Implementation of Information Technology Strategic Management to Academicians' Performance in Higher Education Institution Slamet, Cepy; Rahman, Aedah binti Abdul; Ramdhani, Muhammad Ali
JOIN (Jurnal Online Informatika) Vol 6 No 2 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i2.829

Abstract

This study aimed to understand the determinant factors of information technology (IT) strategic management to individual (lecturer) performance using data samples from selected higher education institutions in Indonesia. Since the use of IT innovation in (HEI) is often considered a lens representing the strength of strategy, competitiveness, and quality within a corporate view, it is vague on its impact on individual performance. The investigation included data collection based on an online survey conducted on 325 respondents to investigate the relationship between strategic factors, elaborated into several relevant criteria. The results of statistical data processing showed that of all the strategic factors involved, the business model and strategic alignment categorized in high determinations in influencing academicians' performance at HEI.
Analysis of Final Semester Assessment and Fiqih Independent Examination Higher Order Thingking Skill Type Nurhalizah, Teti; Ramdhani, Muhammad Ali; Nurmila, Nina
Atthulab: Islamic Religion Teaching and Learning Journal Vol. 8 No. 1 (2023): Atthulab: Islamic Religion Teaching and Learning Journal
Publisher : Laboratory of Islamic Religious Education Faculty of Tarbiyah and Teacher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ath.v8i1.19145

Abstract

This study aims to describe the questions based on the level of thinking, type of stimulus and operational verbs used to make questions. This study uses a descriptive approach to document analysis that aims to analyze the questions, provide direction and assess questions according to the cognitive level at the Madrasah Tsanawiyah level. The results showed that of the 135 questions, half of them were about Higher Order Thinking Skills and some were about Lower Order Thinking Skills. The questions in the Higher Order Thinking Skills category were mostly found in 7th grade material regarding Thaharah material, 8th grade material regarding zakat fitrah and 9th grade material regarding the timing of qurban and fasting. The types of stimulus contained in the questions are tables and discourses where the most widely stimulated discourse questions are found in more than 60% of the total questions.Penelitian ini bertujuan untuk mendeskripsikan soal-soal berdasarkan level berpikir level Lower Order Thinking Skills (LOTS) atau Middle Order Thinking Skills (MOTS) atau Higher Order Thinking Skills (HOTS) serta mengelompokkan soal berdasarkan jenis stimulus dan KKO (Kata Kerja Oprasional) yang digunakan untuk membuat pertanyaan. Penelitian ini menggunakan pendekatan deskriptif analisis dokumen. Dokumen yang dianalisis yaitu bertujuan untuk menganalisis lebih mendalam serta memberikan soal-soal rekomendasi HOTS yang bisa digunakan dalam pembelajaran nantinya. Hasil penelitian menunjukkan bahwa dari 135 soal  hanya terdapat setengahnya merupakan soal Higher Order Thinking Skills (HOTS), dan sebagiannya soal Lower Order Thinking Skills (LOTS). Soal kategori Higher Order Thinking Skills (HOTS) paling banyak ditemukan pada materi kelas VII mengenai materi Thoharah, materi kelas 8 mengenai zakat fitrah dan materi kelas 9 mengenai waktu pelaksanaan kurban dan materi puasa, belum ada soal yang memenuhi kriteria Higher Order Thinking Skills (HOTS). Jenis stimulus yang terdapat pada soal adalah table dan wacana dimana penggalan kasus merupakan stimulus yang paling banyak ditemukan lebih dari 60% dari keseluruhan soal. 
Feature Engineering for Tropical Rainfall Forecasting Using Random Forest and Support Vector Regression Slamet, Cepy; Imron, Rizka M; Wahana, Agung; Maylawati, Dian Sa'adillah; Zulfikar, Wildan Budiawan; Ramdhani, Muhammad Ali
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1111

Abstract

The complex dynamics of weather variability in Indonesia, influenced by multiple climatic drivers, make rainfall forecasting in tropical regions a significant scientific challenge. This study proposes an automated feature engineering pipeline to enhance the performance of Random Forest Regression (RFR) and Support Vector Regression (SVR) models for tropical rainfall prediction. Monthly rainfall data spanning 388 months (1993–2025) from a BMKG station were used as the basis for model development. The pipeline systematically generates temporal, seasonal, statistical, and anomaly-based features to provide domain-informed representations for non-sequential learning algorithms. Model performance was evaluated under four temporal data partitioning scenarios using R², RMSE, and probabilistic confidence intervals derived from bootstrap residual simulations. Results indicate that RFR achieved the highest predictive accuracy (R² = 0.93; RMSE = 31.01 mm) and demonstrated superior temporal–seasonal stability (Rolling CV: R² = 0.81 ± 0.07; RMSE = 55.44 ± 16.18), with comparable performance between wet and dry seasons. Conversely, SVR showed greater sensitivity to seasonal variability, with R² dropping to 0.55 during the wet season, indicating higher uncertainty under extreme rainfall conditions. Robustness and drift analyses further revealed that RFR adapts better to temporal and seasonal shifts, while SVR remains relevant as an adaptive model for extreme risk analysis. Overall, this study contributes to the development of automated feature engineering, reproducible climatological forecasting pipelines, and probabilistic modeling frameworks for rainfall prediction under uncertainty in tropical regions.
Co-Authors Abdullah Ramdhani Abdurahman, Ade Mohamad Abdusy Syakur Amin Adam Faroqi Adang Hambali, Adang Adi Putra Andriyandi Agung Wahana Ahmad Fathonih, Ahmad Azwar Tsabit Barzan Faizin Bebeh Wahid Nuryadin Cepy Slamet Dian Sa'adillah Maylawati Dian Sa’adillah Maylawati Dian Sa’adillah Maylawati Diena Rauda Ramdania Dzulkifli, Muhamad Arham Enjang AS, Enjang Fauzi, Rai Ahmad Fitri, Susanti Ainul Hamdan Sugilar Hasan Basri Hilmi Aulawi Imron, Rizka M Irfan Safrudin Kamil, Muhammad Ihsan Kasmin, Fauziah Kumar, Yogan Jaya lia kamelia Maman, Maman Maylawati, Dian Sa'adillah Muhamad Fahmi Amrillah MUHAMMAD RIZAL Muharam, Aldi Fahluzi Nina Nurmila Nuraeni, Eneng Nurhalizah, Teti Rahman, Aedah binti Abdul Rahman, Titik Khawa Abdul Rakhman, Deny Fauzy Rinaldy Maulidiansyah Rinda Cahyana Rizqullah, Naufal Rochman, Chaerul Septya Egho Pratama Teddy Mantoro Tedi Priatna Teti Nurhalizah Wahyudin Darmalaksana Wildan Budiawan Zulfikar Yana Aditia Gerhana, Yana Aditia Yosep Bustomi