Article Per Year (5 Year)
p-Index From 2021 - 2026
7.6
P-Index
This Author published in this journals
All Journal Jurnal Sains Materi Indonesia JOURNAL OF APPLIED INFORMATICS AND COMPUTING Communications in Science and Technology Jurnal Informatika Universitas Pamulang INTECOMS: Journal of Information Technology and Computer Science JSiI (Jurnal Sistem Informasi) Indonesian Physical Review Building of Informatics, Technology and Science Infotekmesin Piston: Journal of Technical Engineering Journal of Innovation and Future Technology (IFTECH) Jurnal Sistem Komputer & Kecerdasan Buatan Buletin LOUPE (Laporan Umum Penelitian) Journal of Applied Sciences and Advanced Technology Indonesian Journal of Computing, Engineering, and Design Jurnal Pengendalian Pencemaran Lingkungan (JPPL) Jurnal Teknologi Informatika dan Komputer Akrab Juara : Jurnal Ilmu-ilmu Sosial Jurnal Mesin Nusantara Jurnal Pengabdian kepada Masyarakat Jurnal Abdimas Indonesia : Jurnal Abdimas Indonesia International Journal of Engagement and Empowerment (IJE2) JURNAL ILMIAH GLOBAL EDUCATION Jurnal Penelitian Inovatif Journal Of Sustainable Research In Management Of Agroindustry (SURIMI) ACROPORA: Jurnal Ilmu Kelautan dan Perikanan Papua JAMAIKA: Jurnal Abdi Masyarakat Abdi Jurnal Publikasi Jurnal Teknologi Pangan dan Industri Perkebunan Metalurgi OKTAL : Jurnal Ilmu Komputer dan Sains Hikmayo: Jurnal Pengabdian Masyarakat Jurnal Ilmiah Multidisiplin Indonesia MULTIPLE: Journal of Global and Multidisciplinary JARI Acta Solum Food and Agro-industry (FAGI) Journal Jurnal Ilmu Komputer
Murni Handayani
Universitas Pamulang
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

Published : 54 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 54 Documents
Search

 2   3   4   5   6 
Analysis and Evaluation of Qur’an Translation Topics Using Classical, Neural, and Transformer-Based Topic Modelling Akhmad Rinaldy Kurnia; Sajarwo Anggai; Murni Handayani
Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID) Vol. 5 No. 02 (2026): Jurnal Ilmiah Multidisplin Indonesia (JIM-ID), February 2026
Publisher : Sean Institute

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

Abstract

Topic modelling is an important approach for extracting latent thematic structures from text corpora, including religious texts that are characterized by dense semantics and short documents. This study aims to compare the performance of several topic modelling methods Latent Dirichlet Allocation (LDA), Biterm Topic Model (BTM), Combined Topic Model (CombinedTM), and BERTopic in extracting topics from the Indonesian translation of the Qur’an. The dataset consists of 6,236 verses, with each verse treated as a single document. Topic quality is evaluated using two main metrics: coherence score (C_v) and topic diversity. The experimental results show that CombinedTM achieves the highest coherence score, with a maximum value of approximately 0.52 at K = 10 topics, followed by BTM, which demonstrates relatively high and stable coherence scores (around 0.50) across certain topic number variations. LDA yields the highest topic diversity, exceeding 0.90, but with lower coherence scores compared to the other models, indicating its limitations in preserving semantic coherence in short texts. Meanwhile, BERTopic exhibits consistently high topic diversity (0.85–0.88) across different numbers of topics, although its bag-of-words–based coherence scores do not always increase significantly. These findings highlight that the choice of topic modelling method should be aligned with the characteristics of the corpus and the objectives of thematic analysis, particularly in the context of short-form religious texts.
Implementation of Split Sampling for Decision Tree and K-Nearest Neighbor Algorithms in the DKI Jakarta Legislative Election Bambang Wisnu Widagdo; Muhammad Rizky Fadillah; Mochamad Adhari Adiguna; Sudarno Wiharjo; Murni Handayani
Jurnal Penelitian Inovatif Vol 5 No 4 (2025): JUPIN November 2025
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jupin.1704

Abstract

The 2009 legislative election was contested by 44 political parties, consisting of national and local parties. In the 2009 Legislative Election for DKI Jakarta, there were 2,268 candidates for the Regional House of Representatives (DPRD) from 44 parties competing for 94 seats in the DKI Jakarta Regional People's Representative Council. Data mining is a series of processes aimed at discovering added value in the form of information that has not been previously known manually from a database. The classification method can be used to predict the results of legislative elections. In this study, the author employs the Decision Tree and K-Nearest Neighbor classification algorithms. This research utilizes several data sampling techniques, namely Linear Sampling, Shuffled Sampling, and Stratified Sampling. The data split partition used in this study was 80% for training and 20% for testing. The software tool utilized was RapidMiner. The performance variables measured include Recall, Precision, and Accuracy. The results of this study indicate that, overall, Linear Split Sampling outperforms Shuffled Split Sampling and Stratified Split Sampling. For the Decision Tree algorithm, Linear Split Sampling achieved a Recall of 100%, Precision of 82.05%, and Accuracy of 98.46%. Shuffled Split Sampling recorded a Recall of 81.82%, Precision of 85.71%, and Accuracy of 98.46%. Meanwhile, Stratified Split Sampling obtained a Recall of 100%, Precision of 82.05%, and Accuracy of 97.80%. Meanwhile, for the K-Nearest Neighbor (KNN) algorithm, Linear Split Sampling achieved a Recall of 93.75%, Precision of 75%, and Accuracy of 97.36%. Shuffled Split Sampling recorded a Recall of 59.09%, Precision of 81.25%, and Accuracy of 97.36%. Stratified Split Sampling obtained a Recall of 31.58%, Precision of 85.71%, and Accuracy of 96.92%.
PELATIHAN PEMANFAATAN ARTIFICIAL INTELLIGENCE PADA ERA DIGITAL UNTUK MENINGKATKAN KREATIVITAS DAN PRODUKTIVITAS BELAJAR SISWA SMA BINA INSAN MANDIRI KOTA BOGOR Tukiyat Tukiyat; Murni Handayani; Uliyatunisa; Isykariman Biridlwanillah; Djukardi Kurniawan; Erland Sumantri
Abdi Jurnal Publikasi Vol. 5 No. 1 (2026): September
Publisher : Abdi Jurnal Publikasi

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

Abstract

The rapid development of Artificial Intelligence (AI) has created new opportunities in education by supporting more effective, adaptive, and interactive learning processes. However, the utilization of digital technology among students is still predominantly focused on entertainment rather than academic purposes. Therefore, efforts are needed to improve digital literacy and students’ ability to use AI productively and responsibly. This community service program aimed to enhance students’ understanding of Artificial Intelligence and its application to support learning creativity and productivity. The activity was conducted at SMA Bina Insan Mandiri Bogor involving 31 students. The implementation methods included lectures, demonstrations, hands-on practice, discussions, and mentoring. Training materials covered AI fundamentals, AI-based learning assistance, academic presentation development, project idea generation, and ethical use of AI in education. Evaluation was conducted through pre-test and post-test assessments, participant observation, and satisfaction questionnaires. The results indicated an increase in participants’ understanding, with average achievement rising from 96.3% in the pre-test to 100% in the post-test. Furthermore, 93.6% of participants stated that the training improved their understanding of AI, while 93.5% agreed that AI could enhance creativity and learning productivity. Participant satisfaction was categorized as very good. The program successfully improved digital literacy, creativity, learning productivity, and awareness of ethical AI usage. This training model can be adopted as an educational strategy to prepare students for the challenges of Industry 4.0, Society 5.0, and future digital transformation.
Hybrid CNN-BiLSTM-Attention Modeling for Air Temperature Prediction Using LOF-iForest-RFE Multi-Stage Preprocessing on Soekarno-Hatta Meteorological Station AWS Data (2021–2025) Nur Fuat, Muhamad; Anggai, Sajarwo; Handayani, Murni
Journal of Applied Informatics and Computing Vol. 10 No. 5 (2026): October 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i5.13785

Abstract

Air temperature is a critical meteorological parameter that dynamically affects density altitude and Maximum Take-Off Weight (MTOW) calculations in aviation operations. Although the 10-minute resolution Automatic Weather Station (AWS) data at Soekarno-Hatta International Airport effectively captures micrometeorological fluctuations, it is chaotic and prone to anomalies, often causing prediction failures in conventional models. This study aims to propose an artificial intelligence-based short-term framework to predict air temperature for the next 10-minute horizon by integrating multi-level preprocessing with a hybrid CNN-BiLSTM-AM (Convolutional Neural Network, Bidirectional Long Short-Term Memory, Attention Mechanism) architecture. Utilizing a Data-Centric AI approach on observational data from 2021–2025, the methodology begins with local and global anomaly purification via Local Outlier Factor (LOF) and Isolation Forest (iForest) algorithms. Multicollinearity is then mitigated through hybrid feature selection using Pearson Correlation and Recursive Feature Elimination (RFE). In the modeling phase, the 1D-CNN layer extracts spatial correlations among variables, the BiLSTM evaluates bidirectional temporal dependencies, and the attention mechanism adaptively distributes probability weights to prevent lag response during extreme weather oscillations. The findings demonstrate that data purification is strictly necessary to avoid model generalization failures, and RFE successfully isolated the four most optimal physical predictors: maximum temperature, relative humidity, air pressure, and solar radiation. Comparatively, the proposed CNN-BiLSTM-AM model proved to be the most superior, achieving the highest accuracy with an RMSE of 0.8151 °C, MAE of 0.6329 °C, and R² of 0.9106. The addition of attention and convolution mechanisms was shown to reduce the root mean square error (RMSE) by 16.44% and the mean absolute error (MAE) by 13.64% compared to the pure BiLSTM baseline model. In conclusion, achieving an extreme error deviation (RMSE) consistently below the 1.0 °C operational tolerance confirms that this architecture is highly feasible, robust, and has strong potential as a highly reliable meteorological reference to support Density Altitude and MTOW estimations in equatorial climates.
Co-Authors Abu Khalid Rivai Ahmad Gunawan Wibisono Ahmad Musyafa Ahmad Musyafa Ahmad Randy Akhmad Rinaldy Kurnia Al Habib, Irsyad Allam Ramzy Allam Ramzy Amartya Natayu Anggai, Sajarwo Annisa Yuliana Angeline Any Kurniawati, Any Ari Kristiningsih Arken Abdullah Arrozi , Ubed Sonai Fahruddin Arsita Nur Rizkia Putri Arya Adhyaksa Waskita Astuti, Wijayanti Dwi Aza Fauziana, Noer Bambang Wisnu Widagdo Budi Hadisujoto Charlene Tiara Rehueliah Pingak Choirunnisa Firdaus Ivana Da, Oh Wen Dahlan Hidayat Dawam Agung Pribadi Destiny, Keysi Devain Dewanto, Hizkia Alpha Dewi Sondari Djukardi Kurniawan Dr TUKIYAT, M.Si Dwi, Sadina Sahitya Dwityaningsih, Rosita Eko Sulistiyono Erland Sumantri Evi Triwulandari Evila Purwanti Sri Rahayu, Theresia Fadillah Fajar Hidayanto, Fajar Felix Firdiyono Feni Aryanti Fitri Khoerunnisa Giyanto Gunawarman Hartanto Heryandi Suradiradja, Kahfi Hesti Rahayuningsih Hizam, Fadli Iasya, Yurin Karunia Apsha Albaina Ilma Fadlilah Ipung Saputra Irnanda, Istifhamy Isykariman Biridlwanillah Iwan Dwi Antoro Iwan Setiawan Iwan Setiawan Jatmoko Awali Joko Setia Pribadi Jon Affi, Jon Kanim Kristiningsih, Ari Kushendarsyah Saptaji Latifatul Khusna Lutfi Syafirullah Mahendra, Brillian Ardy Makhsun Makhsun Makhsun Mardiyana Mardiyana Mardiyana Mardiyana Maulana, Romdon Mila Prametha, Novika Mochamad Adhari Adiguna Moh. Triyana Abbas Mohammad Nurhilal Mohammad Rayhan Afdillah Muhamad Sibli Muhammad Rizky Fadillah Muji Mulyani Mustofa, Rizki Nabila, Najwa Natasya Arifah Natasya Arifah Nikolas Krisma Hadi Fernandez Nur Fuat, Muhamad Nur Indah Wardani Nur Rohmat Nuraini Sitepu Nuraini Sitepu Nurhayati, Mita Nurlinda Ayu Triwuri Oto Prasadi putri, raekhanrahmah Putri, Restiani Alia Raekhan Rahmah Putri Rafli Rafli Rafli Rafli Ramses Maur Ragaventrand Reno Saeprani Retno Tri Purnamasari Rifqi Fakhri Yogi Syafruddin Rizki Agustian Rizki Ahmad Darmawan Rosita Dwityaningsih Rosita, Rosita Dwityaningsih Saefudin Saefudin Saefuloh, Iman Sajarwo Anggai Sajarwo Anggai Salma Maulikhatun Zulfa Santika, Ariel Sari Widya Utami Sari Widya Utami Satrio Herbirowo, Satrio Septian Pratama Siti Cici Carliah Siti Khoirunnisa Slamet Raharjo Slamet Raharjo Sudarno Sudarno Sudarno Wiharjo Sumardiono, Arif Surya, Surya Ariwibowo Syadilla Ega Maharani Taswanda Taryo Taswanda Taryo Tukiyat Tukiyat Tukiyat Tukiyat Tukiyat, Tukiyat Ulikaryani Uliyatunisa Uliyatunisa Uliyatunisa, Uliyatunisa Waskita, Arya Adhyaksa Widuri Indana Saleha Widuri Indana Saleha Witriansyah, Khoeruddin Wittriansyah, Khoeruddin Yessi Permana Yuli Yetri Yunita Triana, Yunita Yunus Yunus Yuswono Yuswono Zain, Rafi Mahmud Zeni Ulma Zikrullah, Mochamad Fachrudin