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Pengembangan Media Pembelajaran Untuk Meningkatkan Unjuk Kerja Siswa Pada Mata Pelajaran Produk Kreatif dan Kewirausahaan Gigih Perkasa; Didik Dwi Prasetya; Marsono Marsono
BRILIANT: Jurnal Riset dan Konseptual Vol 9 No 3 (2024): Volume 9 Nomor 3, Agustus 2024
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/briliant.v9i3.1744

Abstract

The purpose of this research is to produce the development of running text led P10 learning media that has a level of media validity and improves student performance in creative product and entrepreneurship subjects. In this study researchers took the ADDIE development method which was felt to be simpler, practical and did not require a relatively long time. Based on data analysis and discussion, the results of the validity of the Running Text Led Dot Matrix P10 learning media with Arduino Uno show the validity of the material obtaining a percentage of 82.14% and the validity of the media 90.62% both of which are included in the criteria for a high level of validity and deserve to be applied. improved learning outcomes in the implementation of the pre-test, then the value increased during the implementation of the post-test with the Running Text Led Dot Matrix P10 learning media with Arduino Uno and was able to increase the effectiveness of the learning media on creative and entrepreneurial product subjects.
Pengembangan Buku Digital Interaktif pada Mata Pelajaran Matematika SMK Mokhamad Nuryakin; Marsono Marsono; Didik Dwi Prasetya
BRILIANT: Jurnal Riset dan Konseptual Vol 9 No 3 (2024): Volume 9 Nomor 3, Agustus 2024
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/briliant.v9i3.1746

Abstract

The industrial revolution is currently developing very rapidly and has an impact on all lines of life, including the world of education. Digitalization of education needs to be carried out in order to keep up with world developments. Based on the results of observations, data was obtained that SMK Islam 1 Blitar only has 1 textbook title to support the implementation of the teaching and learning process for students and teachers in mathematics subjects using the independent curriculum. The textbooks owned are said to be available in the form of printed books so they require a large enough storage space. Therefore, it is necessary to develop media in the form of interactive digital books to improve student learning outcomes. The type of research and development used is the R&D model of the ADDIE. Data collection uses questionnaires and written tests. The validation results by all research subjects were declared valid with details of obtaining scores of 91% of material experts, 88% of media experts, 94% of teacher users, and student users in small groups 92%. Based on the results of the feasibility test carried out, an average percentage score of 87% was included in the eligibility criteria. In addition, the product developed was also declared effective for use with an achievement score of 87%.
Anatomy of Sentiment Analysis in Ontological, Epistemological, and Axiological Perspectives Fadli Hidayat, M. Noer; Dwi Prasetya, Didik; Widiyaningtyas, Triyanna; Patmanthara, Syaad
JOIN (Jurnal Online Informatika) Vol 10 No 1 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i1.1228

Abstract

The aim of this article was to examine sentiment analysis methods from the perspective of the philosophy of science with three approaches, ontological, epistemological and axiological. This research used a qualitative research method (descriptive-analysis) with an ontological, epistemological and axiological approach that uses library research and document studies of previous research results. Data collection was carried out through books and reputable scientific journals on Scopus, ScienceDirect, IEEEXplore and Springer Link. The results of this research showed that sentiment analysis from an ontological perspective describes the definition, development and relationship of sentiment with social reality. Meanwhile, from an epistemological perspective, sentiment analysis is viewed from how the source of knowledge is obtained, explaining the production of sentiment analysis knowledge, and several ways of working that can be applied in studies. Axiologically, sentiment analysis can see the function and value resulting from sentiment analysis, as well as discussing the results of interpretation from sentiment analysis studies. These findings showed the development of sentiment analysis in answering various problems to improve the quality of sustainable services in various fields.
An enhanced pivot-based neural machine translation for low-resource languages Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almuíini
International Journal of Advances in Intelligent Informatics Vol 11, No 2 (2025): May 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i2.2115

Abstract

This study examines the efficacy of employing Indonesian as an intermediary language to improve the quality of translations from Javanese to Madurese through a pivot-based approach utilizing neural machine translation (NMT). The principal objective of this research is to enhance translation precision and uniformity among these low-resource languages, hence advancing machine translation models for underrepresented languages. The data collecting approach entailed extracting parallel texts from internet sources, followed by pre-processing through tokenization, normalization, and stop-word elimination algorithms. The prepared datasets were utilized to train and assess the NMT models. An intermediary phase utilizing Indonesian is implemented in the translation process to enhance the accuracy and consistency of translations between Javanese and Madurese. Parallel text corpora were created by collecting and preprocessing data, thereafter, utilized to train and assess the NMT models. The pivot-based strategy regularly surpassed direct translation regarding BLEU scores for all n-grams (BLEU-1 to BLEU-4). The enhanced BLEU ratings signify increased precision in vocabulary selection, preservation of context, and overall comprehensibility. This study significantly enhances the current literature in machine translation and computational linguistics, especially for low-resource languages, by illustrating the practical effectiveness of a pivot-based method for augmenting translation precision. The method's dependability and efficacy in producing genuine translations were proved through numerous studies. The pivot-based technique enhances translation quality, although it possesses limitations, including the risk of error propagation and bias originating from the pivot language. Further research is necessary to examine the integration of named entity recognition (NER) to improve accuracy and optimize the intermediate translation process. This project advances the domains of machine translation and the preservation of low-resource languages, with practical implications for multilingual communities, language education resources, and cultural conservation.
Minangkabau Language Stemming: A New Approach with Modified Enhanced Confix Stripping Ahda, Fadhli Almu'iini; Aji Prasetya Wibawa; Didik Dwi Prasetya; Danang Arbian Sulistyo; Andrew Nafalski
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6511

Abstract

Stemming is an essential procedure in natural language processing (NLP), which involves reducing words to their root forms by eliminating affixes, including prefixes, infixes, and suffixes. The employed method assesses the efficacy of stemming, which differs according to language. Complex affixation patterns in Indonesian and regional languages such as Minangkabau pose considerable difficulties for traditional algorithms. This research adopts the enhanced fixed-stripping method to tackle these issues by integrating linguistic characteristics unique to Minangkabau. This study has three phases: data acquisition, pseudocode development, and algorithm execution. Testing revealed an average accuracy of 77.8%, indicating the algorithm's proficiency in managing Minangkabau’s intricate morphology. Nevertheless, constraints persist, particularly with irregular affixation patterns. Possible improvements could include adding more datasets, improving the rules for handling affixes, and using machine learning to make the system more flexible and accurate. This study emphasizes the significance of customized solutions for regional languages and provides insights into the advancement of NLP in various linguistic environments. The findings underscore the progress made in processing Minangkabau text while also emphasizing the need for further research to address current issues.
Enhancing Semantic Similarity in Concept Maps Using LargeLanguage Models Wiryawan, Muhammad Zaki; Prasetya, Didik Dwi; Handayani, Anik Nur; Hirashima, Tsukasa; Pratama, Wahyu Styo; Putra, Lalu Ganda Rady
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i3.4727

Abstract

This research uses advanced models, Generative Pre-trained Transformer-4 and Bidirectional Encoder Representations from Transformers, to generate embeddings that analyze semantic relationships in open-ended concept maps. The problem addressed is the challenge of accurately capturing complex relationships between concepts in concept maps, commonly used in educational settings, especially in relational database learning. These maps, created by students, involve numerous interconnected concepts, making them difficult for traditional models to analyze effectively. In this study, we compare two variants of the Artificial Intelligence model to evaluate their ability to generate semanticembeddings for a dataset consisting of 1,206 student-generated concepts and 616 link nodes (Mean Concept = 4, Standard Deviation = 4.73). These student-generated maps are compared with a reference map created by a teacher containing 50 concepts and 25 link nodes. The goal is to assess the models’ performance in capturing the relationships between concepts in an open-ended learning environment. The results show that demonstrate that Generative Pretrained Transformers outperform other models in generating more accurate semantic embeddings. Specifically, Generative Pre-trained Transformer achieves 92% accuracy, 96% precision, 96% recall, and 96% F1-score. This highlights the Generative Pretrained Transformer’s ability to handle the complexity of large, student-generatedconcept maps while avoiding overfitting, an issue observed with the Bidirectional Encoder Representationsfrom Transformer models. The key contribution of this research is the ability of two complex models and multi-faceted relationships among concepts with high precision. This makes it particularly valuable in educational environments, where precise semantic analysis of open-ended data is crucial, offering potential for enhancing concept map-based learning with scalable and accurate solutions.
Performance Evaluation of Artificial Intelligence Models for Classification in Concept Map Quality Assessment Pratama, Wahyu Styo; Prasetya, Didik Dwi; Widyaningtyas, Triyanna; Wiryawan, Muhammad Zaki; Putra, Lalu Ganda Rady; Hirashima, Tsukasa
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i3.4729

Abstract

Open-ended concept maps generated by students give better flexibility and present a complex analysis process for teachers. We investigate the application of classification algorithms in assessing openended concept maps, with the purpose of providing assistance for teachers in evaluating student comprehension. The method used in this study is experimental methods, which consists of data collection, preprocessing, representation generation, and modelling with Feedforward Neural Network, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, and Logistic Regression. Our dataset, derived from concept maps, consists of 3,759 words forming 690 propositions, scored carefully by experts to ensure high accuracy in the evaluation process. Results of this study indicate that K-NN outperformed all other models, achieving the highest accuracy and Receiver Operating Characteristic-Area Under the Curve scores, demonstrating its robustness in distinguishing between classes. Support Vector Machine excelled in precision, effectively minimizing false positives, while Random Forest showcased a balanced performance through its ensemble learning approach. Decision Tree and Linear Regression showed limitations in handling complex data patterns. FeedforwardNeural Network can model intricate relationships, but needs further optimization. This research concluded that Artificial Intelligence classification enables a better assessment for teachers, enables the path for personalized learning strategies in learning.
PENERAPAN MODEL KOOPERATIF TIPE TEAMS ASSISTED INDIVIDUALIZATION (TAI) UNTUK MENINGKATKAN HASIL BELAJAR SISWA KELAS X 3 SMAN 7 MALANG Wardani, Adi Wahyu; Prasetya, Didik Dwi; Setiawan, Ahmad Yusuf; Ratnaduhita, Nadiah Alma; Ridlo, Muhammad Zidni
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 03 (2025): Volume 10 No. 03 September 2025 In Proccess
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i03.25934

Abstract

ABSTRACT Education constantly evolves alongside technological advancements and social transformation. In such a context, selecting the appropriate teaching model is crucial to the success of the teaching and learning process. The aim of this study is to examine how the implementation of the Cooperative Learning Model of Team Assisted Individualization (TAI) can improve student learning outcomes in Digital Literacy material for Grade X students at SMAN 7 Malang. This study employed Classroom Action Research (CAR) conducted in two cycles, each consisting of planning, action, observation, and reflection stages. Data were collected through observation sheets, documentation, student activity records, and learning outcome tests. The findings indicate that the TAI model enhances both student achievement and participation. In the first cycle, 51% of students achieved the minimum mastery criteria (KKM), and this figure increased to 96% in the second cycle. The results show that cooperative learning using the TAI model can foster cognitive development and social interaction among students, making it an effective strategy for significantly improving digital literacy outcomes. ABSTRAK Pendidikan selalu berubah seiring kemajuan teknologi dan transformasi sosial. Dalam keadaan seperti ini, pemilihan model pengajaran yang tepat sangat penting untuk keberhasilan proses belajar-mengajar. Tujuan dari penelitian ini adalah untuk melihat bagaimana penerapan Model Pembelajaran Kooperatif tipe tim yang dibantu individualisasi (TAI) dapat meningkatkan hasil pembelajaran siswa pada materi Literasi Digital di kelas X di SMAN 7 Malang. Dalam penelitian ini, Penelitian Tindakan Kelas (PTK) dilakukan dalam dua siklus. Tahap perencanaan, tindakan, pengamatan, dan refleksi termasuk dalam masing-masing siklus. Data dikumpulkan melalui lembar observasi, dokumentasi, aktivitas siswa, dan tes hasil belajar. Temuan penelitian menunjukkan bahwa model TAI meningkatkan pencapaian dan partisipasi siswa. Pada siklus pertama, 51% siswa berhasil mencapai kriteria ketuntasan minila (KKM), dan pada siklus kedua, angka tersebut meningkat menjadi 96%. Hasil penelitian menunjukkan bahwa pembelajaran kooperatif dengan model TAI dapat meningkatkan perkembangan kognitif dan interaksi sosial siswa. Ini berarti bahwa ini adalah cara untuk meningkatkan hasil literasi digital yang luar biasa.
Gamified Web-Based Learning in Teaching Principles and Assessment Courses to Improve Learning Evaluation Skills of PPG Students Hidayat, Wahyu Nur; Widiyanti, Widiyanti; Ichwanto, Muhammad Aris; Prasetya, Didik Dwi; Akbar, Asna Isyarotul; Prihandicha, Adiftya Bayu; Cakir, Gulsun Kurubacak
Jurnal Inovasi Teknologi Pendidikan Vol. 12 No. 3 (2025): September (On Process)
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jitp.v12i3.79270

Abstract

Education is a key pillar in the development of individuals and society. In this digital era, technology has revolutionized learning by expanding access and improving the quality of the learning process. One of the recent innovations is the use of web-based learning (WBL), which although flexible, often lacks interaction elements thus reducing user engagement. To address this, this research proposes a platform "Meja Guru Academy" platform that integrates gamification elements in WBL to improve the learning evaluation skills of Teacher Professional Education (PPG) students. This research utilizes the Design Thinking approach which involves the stages of empathy, problem definition, idea development, prototyping, and evaluation. The data collection method through questionnaires produced quantitative and qualitative data for system validation. Content experts rated the platform's educational material at 85,33%, indicating exceptional alignment with learning objectives, while media experts provided a score of 89.60%, highlighting effective usability. User testing with PPG students yielded a strong System Usability Scale (SUS) score of 79, suggesting the platform is highly user-friendly. Additionally, the User Experience Questionnaire (UEQ) results indicated positive user perceptions across multiple aspects, with high ratings in pragmatic quality attributes such as perspicuity and efficiency, and hedonic qualities including stimulation and novelty. Overall, Meja Guru Academy presents an innovative and effective solution for advancing PPG students' evaluation competencies, fostering engagement and self-directed learning through gamified WBL.
SIPAS: Sistem Informasi Pengolahan Survei Untuk Optimalisasi Manajemen Data Survei Hidrografi Firdaus, Nabilah Zakiyah Salmaa; Nugroho, Muhammad Arief; Biantoro, Yudhi; Prasetya, Didik Dwi
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 4 No. 5 (2025): EDISI SEPTEMBER 2025
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v4i5.11507

Abstract

Survei hidrografi menghasilkan volume data yang besar dan kompleks, sehingga memerlukan sistem pengelolaan yang sistematis, efisien, dan terstruktur untuk menjamin akurasi serta konsistensi dalam pengolahan data. Penelitian ini bertujuan untuk merancang dan mengembangkan SIPAS (Sistem Informasi Pengolahan Survei), sebuah sistem informasi berbasis web yang mendukung manajemen data survei hidrografi serta pemantauan progres pengolahan data secara real-time. Pengembangan sistem dilakukan menggunakan pendekatan model Waterfall, yang mencakup tahapan analisis kebutuhan, perancangan antarmuka pengguna dan basis data, implementasi sistem menggunakan framework Laravel dan basis data MySQL, serta pengujian fungsional menggunakan metode Black-Box. Hasil implementasi menunjukkan bahwa SIPAS mampu menyediakan autentikasi pengguna berbasis peran (Super Admin, Admin, dan User), pengelolaan data survei secara terorganisir, serta fitur pemantauan progres yang terintegrasi dan informatif. Pengujian menunjukkan seluruh fitur berfungsi sesuai dengan skenario uji, tanpa ditemukan kesalahan fungsi utama. Dengan demikian, SIPAS dinilai layak untuk digunakan sebagai alat bantu digital dalam mendukung efektivitas dan efisiensi pengolahan data survei hidrografi.
Co-Authors Abdul Wafi Adi Wahyu Wardani Ahmad Fajruddin Syauqi Ainun Nur Baiti Aji P Wibawa Aji Prasetya Wibawa Akbar, Asna Isyarotul Andika Dwiyanto, Felix Andrew Nafalski Anik Nur Handayani Anjar Dwi Rahmawati Arifiati Fitri Anggraini Aryo Pinandito Ashar, Muhammad Azhar Ahmad Smaragdina Bagaskoro Biantoro, Yudhi Bintang Romadhon Cakir, Gulsun Kurubacak Denis Eka Cahyani Dwi Widiyasari Dyah Ayu Langening Tyas Ella Amelia Widodo Erlik Prasetyo Wahyudi F.ti Ayyu Sayyidul Laily Fadhli Almu’iini Ahda Fadli Hidayat, M. Noer Fatrisna Salsabila, Reni Firdaus, Nabilah Zakiyah Salmaa Gigih Perkasa Gradiyanto Radityo Kusumo Hafid, Ahmad Hakkun Elmunsyah Hanifah Muslimah Az-Zahra, Hanifah Muslimah Haq, Salsabila Thifal Nabil Hariyanto Hariyanto Hayashi, Yusuke Hirashima, Tsukasa I Nyoman Gede Arya Astawa Ida Agus Setyani Intan Sulistyaningrum Sakkinah Iskandar Syah, Abdullah KHOIRUL ANWAR Kusumo, Gradiyanto Radityo Laily, F.ti Ayyu Sayyidul Lalu Ganda Rady Putra Langlang Gumilar Lismi Animatul Chisbiyah Lutfi Budi Ilmawan, Lutfi Budi M. Ajie Kalifatullah Marsono Marsono Maulana Nur Antoro Putro Mayadi, Mayadi Mega Oktaviana Moh. Nur Zamzami Moh. Zainul Falah Mokhamad Nuryakin Muhammad Arief Nugroho Muhammad Aris Ichwanto muhammad hafiizh, muhammad Muhammad Jauharul Fuady Muhammad Mushawwir Mukhamad Angga Gumilang Muladi Nafalski, Andrew Nanscy Evi Wardani Natalina Wahyu Siswijayanti Nena Erviana Nunung Nurjanah Nur Hidayat, Wahyu Prasetya, Luhur Adi Prasetyo, Muchamad Wahyu Pratama, Wahyu Styo Prihandicha, Adiftya Bayu Ratnaduhita, Nadiah Alma Reni Fatrisna Salsabila Ridlo, Muhammad Zidni Rofiudin, Amir Ryan Kurniawan Samodra, Joko Setiadi Cahyono Putro Setiawan, Ahmad Yusuf Sigit Perdana Siti Sendari Sofiya Anggraini Sucipto Sucipto Sucipto Sucipto Sulistyo, Danang Arbian Syaad Patmanthara Syaichul Fitrian Akbar Syamsul Arifin Triyanna Widiyaningtyas Triyanna Widyaningtyas Triyanna Widyaningtyas, Triyanna Tsukasa Hirashima Tsukasa Hirashima Tsukasa Hirashima Tuwoso Utomo Pujianto Wahyu Sakti Gunawan Irianto Wahyu Tri Handoko Wardani, Adi Wahyu Wibawa, Aji P Wibisono Sukmo Wardhono, Wibisono Sukmo Widiyanti Widiyanti, Widiyanti Wiryawan, Muhammad Zaki Yana Andayani Yusril Imamuddin Zainul Falah, Moh.