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All Journal Pendas : Jurnah Ilmiah Pendidikan Dasar SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Informatika Global Jurnal Teknologi Terpadu Jurnal Informasi dan Teknologi Reswara: Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) TEACHER : Jurnal Inovasi Karya Ilmiah Guru Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Software Engineering and Computational Intelligence
Purnamasari, Evi
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Pembuatan Aplikasi Pengelolaan Arsip Surat Dinas PU.BMTR Prov. SumSel Destria, Abel; Purnamasari, Evi; Irfani, M.Haviz; Nazori Suhandi
Jurnal Software Engineering and Computational Intelligence Vol 2 No 01 (2024)
Publisher : Informatics Engineering, Faculty of Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jseci.v2i01.4100

Abstract

Kemajuan teknologi di era globalisasi telah mempermudah berbagai kegiatan, termasuk manajemen administrasi di lembaga pemerintah. Pengelolaan arsip surat, baik surat masuk maupun surat keluar, merupakan elemen penting dalam administrasi lembaga pemerintah. Banyak lembaga yang masih menggunakan metode konvensional penyimpanan dokumen dalam bentuk fisik, yang menyebabkan tantangan seperti kompleksitas manajemen, kesulitan pencarian, dan risiko kerusakan dokumen. Penelitian ini menawarkan solusi menggunakan teknologi berbasis web untuk mengelola arsip surat di Bidang Penataan Ruang Dinas Pekerjaan Umum Bina Marga dan Tata Ruang Provinsi Sumatera Selatan dengan metode pengembangan perangkat lunak System Development Life Cycle (SDLC), yang mencakup tahap perencanaan, analisis, desain, dan implementasi. Sistem baru ini dirancang untuk meningkatkan efisiensi dan efektivitas pengelolaan arsip surat, dengan fitur pencarian surat yang cepat dan akurat, serta manajemen data yang lebih aman dan terorganisir. Implementasi sistem ini diharapkan dapat meningkatkan produktivitas kerja dan mengurangi risiko kesalahan dalam mengelola arsip surat di Dinas PU.BMTR Provinsi Sumatera Selatan.
PROBLEMATIKA KETERAMPILAN MEMBACA PERMULAAN PESERTA DIDIK KELAS RENDAH PADA PEMBELAJARAN BAHASA INDONESIA SEKOLAH DASAR Purnamasari, Evi
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 02 (2025): Volume 10, Nomor 02 Juni 2025 t
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i02.23977

Abstract

Early reading is a very important basic skill for elementary school students, especially in the lower grades. Students often face difficulties in developing their reading skills. This article aims to identify the problems of early reading skills and the factors that influence them. The research method used is a qualitative method using case studies and a descriptive approach. The results of the study explain that the main problems in early reading include difficulty in recognizing letters, lack of understanding of the meaning of reading, and low interest in reading. Factors that play a role and influence include ineffective learning methods, a less supportive reading environment, and differences in cognitive abilities of each student. Educators are expected to be able to develop more effective learning strategies to improve students' reading skills.
Model Data-Driven untuk Prediksi Digitalisasi UMKM Menggunakan GMM dan XGBoost Purnamasari, Evi; Asa Verano, Dwi
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 5 No 2 (2025): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v5i2.984

Abstract

[1]   “?Refleksi 2022 dan Outlook 2023, Kemenkop UKM Ungkap Pencapaian dan Rencana Untuk Pelaku UMKM .” Accessed: May 29, 2025. [Online]. Available: https://ukmindonesia.id/baca-deskripsi-program/refleksi-2022-dan-outlook-2023-kemenkop-ukm-ungkap-pencapaian-dan-rencana-untuk-pelaku-umkm [2]   F. Baderi, “UMKM Pilar Pemulihan dan Pertumbuhan Ekonomi Nasional,” Harian Ekonomi Neraca. Accessed: Dec. 07, 2024. [Online]. Available: https://www.neraca.co.id/article/209137/umkm-pilar-pemulihan-dan-pertumbuhan-ekonomi-nasional [3]   G. Godwin, S. R. P. Junaedi, M. Hardini, and S. Purnama, “Inovasi Bisnis Digital untuk Mendorong Pertumbuhan UMKM melalui Teknologi dan Adaptasi Digital,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 5, no. 2, pp. 41–47, Dec. 2024, doi: 10.34306/abdi.V5I2.1172. [4]    Eliza, F. Hadi, Zefriyenni, and K. Kunci, “Pengembangan E-Commerce di Era Digitalisasi pada UMKM Produk Kale Kota Padang Panjang,” Jurnal Pengabdian kepada Masyarakat Nusantara, vol. 5, no. 2, pp. 2732–2743, Jun. 2024, doi: 10.55338/jpkmn.v5i2.3342. [5]    R. Mardiana, Y. Fahdillah, M. Kadar, I. Hassandi, and R. Mandasari, “Implementasi Transformasi Digital dan Kecerdasan Buatan Sebagai Inovasi Untuk UMKM pada Era Revolusi Industri 4.0,” Jurnal Ilmiah Manajemen dan Kewirausahaan (JUMANAGE), vol. 3, no. 1, Jan. 2024, doi: 10.33998/jumanage.2024.3.1.1552. [6]    S. Baulkani, P. S. Nifasath, and M. M. Priyanga, “Machine Learning Technologies for Agricultural Prediction to Enhance Economic Growth,” Smart Technologies for Sustainable Development Goals, pp. 178–195, 2024, doi: 10.1201/9781003519010-11. [7]    D. Marcelina, A. Kurnia, and T. Terttiaavini, “Analisis Klaster Kinerja Usaha Kecil dan Menengah Menggunakan Algoritma K-Means Clustering,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 3, no. 2, pp. 293–301, Nov. 2023, doi: 10.57152/malcom.v3i2.952. [8]    A. Heryati, T. Terttiaavini, S. Cahyani, H. Romli, and I. Zaliman, “Optimasi Strategi Pemasaran E-Commerce Melalui Prediksi Konversi Berbasis Machine Learning,” JSAI: Journal Scientific and Applied Informatics, vol. 8, no. 1, pp. 66–73, 2025, doi: 10.36085. [9]    M. Alloghani, D. Al-Jumeily, J. Mustafina, A. Hussain, and A. J. Aljaaf, “A Systematic Review on Supervised and Unsupervised Machine Learning Algorithms for Data Science,” pp. 3–21, 2020, doi: 10.1007/978-3-030-22475-2_1. [10]  T. Terttiaavini, “A Hybrid Approach Using K-Means Clustering and the SAW Method for Evaluating and Determining the Priority of SMEs in Palembang City,” INSYST: Journal of Intelligent System and Computation, vol. 6, no. 1, pp. 46–53, Apr. 2024, doi: 10.52985/insyst.V6I1.392. [11]  H. Ren, B. Khailany, M. Fojtik, and Y. Zhang, “Machine Learning and Algorithms: Let Us Team Up for EDA,” IEEE Des Test, vol. 40, no. 1, pp. 70–76, Feb. 2023, doi: 10.1109/mdat.2022.3143427. [12]  T. Milo and A. Somech, “Automating Exploratory Data Analysis via Machine Learning: An Overview,” in Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, New York, NY, USA: ACM, Jun. 2020, pp. 2617–2622. doi: 10.1145/3318464.3383126. [13]  V. Çetin and O. Y?ld?z, “A comprehensive review on data preprocessing techniques in data analysis,” Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 28, no. 2, pp. 299–312, Apr. 2022, doi: 10.5505/pajes.2021.62687. [14]  J. Rashid and K. Waheed, “Missing Values and Outliers in Research Data,” Pakistan Postgraduate Medical Journal, vol. 31, no. 04, pp. 167–167, Jun. 2020, doi: 10.51642/ppmj.v31i04.404. [15]  V. Safak, “Min-Mid-Max Scaling, Limits of Agreement, and Agreement Score,” ArXiv, Jun. 2020, Accessed: May 20, 2025. [Online]. Available: https://arxiv.org/pdf/2006.12904 [16]  R. Addanki, A. McGregor, A. Meliou, and Z. Moumoulidou, “Improved Approximation and Scalability for Fair Max-Min Diversification,” Jan. 2022, Accessed: May 20, 2025. [Online]. Available: https://arxiv.org/pdf/2201.06678 [17] K. P. Sinaga and M.-S. Yang, “Unsupervised K-Means Clustering Algorithm,” IEEE Access, vol. 8, pp. 80716–80727, 2020, doi: 10.1109/access.2020.2988796. [18] L. Trento Oliveira, M. Kuffer, N. Schwarz, and J. C. Pedrassoli, “Capturing deprived areas using unsupervised machine learning and open data: a case study in São Paulo, Brazil,” Eur J Remote Sens, vol. 56, no. 1, Dec. 2023, doi: 10.1080/22797254.2023.2214690. [19]    T. Terttiaavini et al., “Clustering Analysis of Premier Research Fields,” International Journal of Engineering & Technology, vol. 7, no. 4.44, 2018, doi: 10.14419/ijet.v7i4.44.26860. [20]    A. Avram, O. Matei, C.-M. Pintea, P. C. Pop, and C. A. Anton, “Comparative Analysis of Clustering Techniques for a Hybrid Model Implementation,” in 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020), Á. Herrero, C. Cambra, D. Urda, J. JSedano, H. Quintián, and E. Corchado, Eds., Springer, Cham, 2021, pp. 22–32. doi: 10.1007/978-3-030-57802-2_3. [21]    E. Y. Boateng, J. Otoo, and D. A. Abaye, “Basic Tenets of Classification Algorithms K-Nearest-Neighbor, Support Vector Machine, Random Forest and Neural Network: A Review,” Journal of Data Analysis and Information Processing, vol. 08, no. 04, pp. 341–357, 2020, doi: 10.4236/jdaip.2020.84020. [22]    O. A. Montesinos López, A. Montesinos López, and J. Crossa, Overfitting, Model Tuning, and Evaluation of Prediction Performance. Springer International Publishing, 2022. doi: 10.1007/978-3-030-89010-0. [23]    S. Khodabandehlou and M. Zivari Rahman, “Comparison of supervised machine learning techniques for customer churn prediction based on analysis of customer behavior,” Journal of Systems and Information Technology, vol. 19, no. 1/2, pp. 65–93, Jan. 2017, doi: 10.1108/JSIT-10-2016-0061. [24]    R. Susmaga, “Confusion Matrix Visualization,” Intelligent Information Processing and Web Mining, pp. 107–116, 2004, doi: 10.1007/978-3-540-39985-8_12. [25]    M. Kuhn and K. Johnson, “Feature Engineering and Selection: A Practical Approach for Predictive Models,” Feature Engineering and Selection: A Practical Approach for Predictive Models, pp. 1–297, Jan. 2019, doi: 10.1201/9781315108230  
TRANSFORMASI PEMBELAJARAN BUDAYA NUSANTARA MELALUI GALERI VIRTUAL ARTSTEPS: STUDI IMPLEMENTASI DI SEKOLAH DASAR Ayumawarsih, Rika; Purnamasari, Evi; Hastuti, Yani Dwi
TEACHER : Jurnal Inovasi Karya Ilmiah Guru Vol. 6 No. 1 (2026)
Publisher : Pusat Pengembangan Pendidikan dan Penelitian Indonesia (P4I)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51878/teacher.v6i1.8956

Abstract

This study aims to describe the transformation of Indonesian cultural learning through the use of the Artsteps virtual gallery in elementary schools. The research background stems from low student engagement and the lack of contextual learning experiences in cultural learning, necessitating the need for immersive media capable of providing exploratory experiences. Using a qualitative approach with a case study design, this study involved teachers and fourth-grade students through observation, interviews, and documentation during the pre-implementation, implementation, and post-implementation processes. The results showed a significant increase in student learning engagement, marked by increased exploration, discussion, and question-asking activities during visits to the Artsteps virtual space. Students' understanding of cultural diversity also improved, as evidenced by their ability to identify, describe, and compare cultural elements across regions in greater depth. Furthermore, the teacher's role shifted from information provider to facilitator, enabling more collaborative and student-centered learning. However, this study also identified several challenges, such as network limitations, diverse digital literacies, and device constraints, all of which were overcome through adaptive instructional strategies. Overall, this study confirms that the Artsteps virtual gallery is effective in enriching cultural learning experiences and has the potential to be a pedagogical innovation that can be widely implemented in elementary schools. ABSTRAK Penelitian ini bertujuan mendeskripsikan transformasi pembelajaran budaya Nusantara melalui pemanfaatan galeri virtual Artsteps di sekolah dasar. Latar belakang penelitian berangkat dari rendahnya keterlibatan siswa dan minimnya pengalaman belajar kontekstual dalam pembelajaran budaya, sehingga diperlukan media imersif yang mampu menghadirkan pengalaman eksploratif. Menggunakan pendekatan kualitatif dengan desain studi kasus, penelitian ini melibatkan guru dan siswa kelas IV melalui observasi, wawancara, dan dokumentasi selama proses pra-implementasi, implementasi, dan pasca-implementasi. Hasil penelitian menunjukkan adanya peningkatan signifikan pada keterlibatan belajar siswa, ditandai dengan meningkatnya aktivitas eksplorasi, diskusi, dan pengajuan pertanyaan selama mengunjungi ruang virtual Artsteps. Pemahaman siswa terhadap keberagaman budaya juga meningkat, terlihat dari kemampuan mereka mengidentifikasi, mendeskripsikan, dan membandingkan unsur budaya antar daerah secara lebih mendalam. Selain itu, peran guru mengalami pergeseran dari pemberi informasi menuju fasilitator, yang memungkinkan terjadinya pembelajaran yang lebih kolaboratif dan student-centered. Kendati demikian, penelitian ini juga menemukan beberapa tantangan seperti keterbatasan jaringan, literasi digital yang beragam, dan kendala perangkat, namun semua dapat diatasi melalui strategi instruksional adaptif. Secara keseluruhan, penelitian ini menegaskan bahwa galeri virtual Artsteps efektif dalam memperkaya pengalaman belajar budaya dan berpotensi menjadi inovasi pedagogis yang dapat diimplementasikan luas di sekolah dasar.  
Co-Authors Asa Verano, Dwi Athalla, M. Radjab Ayumawarsih, Rika Destria, Abel DEWI SARTIKA Endang Sri Lestari gasim, Gasim Hastuti, Yani Dwi Heriasyah, Rudi Heryati, Agustina Ilyas, Meyfida Indah Permatasari Irfani, M.Haviz JABAR, Tri Ahmad Jabar Lazuarni, Syafira Lesi Hertati, Lesi Lilis Puspitawati Nazori Suhandi NI Wayan Priscila Yuni Praditya Pratama, M Duta Putri, Indah Pratiwi Rendra Gustriansyah Ricky Maulana Fajri Rudi Heriansyah, Rudi Saputra, Tedy Setiawan Terttiaavini, Terttiaavini Verano, Dwi Asa