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All Journal Elkom: Jurnal Elektronika dan Komputer Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Proceeding International Conference on Information Technology and Business International conference on Information Technology and Business (ICITB) Jurnal Cendikia Jurnal Pengabdian kepada Masyarakat Nusantara ABDI MOESTOPO: Jurnal Pengabdian pada Masyarakat Jurnal Media Informatika Journal of Information Systems and Technology Research RISTEC : Research in Information Systems and Technology Journal of Informatics, Electrical and Electronics Engineering Seminar Nasional Teknologi dan Multidisiplin Ilmu Jurnal Pengabdian Masyarakat Jurnal Pengabdian UMKM JPEMAS: Jurnal Pengabdian Kepada Masyarakat Journal of Software Engineering And Technology PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya
Rosyana Fitria Purnomo
Universitas Mitra Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Workshop Dasar Python untuk Guru TIK SMK dalam Meningkatkan Kompetensi Digital: - Purnomo, Rosyana Fitria; Sari, Resy Anggun; Hendri, Romi; Fawaati, Teuku Muhammad
JPEMAS: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2025): JPEMAS : Jurnal Pengabdian Kepada Masyarakat
Publisher : Yayasan Pendidikan Tanggui Baimbaian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71456/adc.v3i2.1237

Abstract

Perkembangan teknologi digital yang pesat menuntut peningkatan kompetensi guru, khususnya guru Teknologi Informasi dan Komunikasi (TIK), dalam penguasaan bahasa pemrograman. Salah satu bahasa pemrograman yang populer dan banyak digunakan saat ini adalah Python karena sintaksnya yang sederhana dan fleksibel. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memberikan pelatihan dasar pemrograman Python kepada guru-guru TIK di SMK Negeri 4 Bandar Lampung guna meningkatkan literasi digital dan kemampuan teknis mereka dalam mengembangkan media ajar berbasis teknologi. Metode pelaksanaan kegiatan meliputi ceramah interaktif, demonstrasi langsung, dan praktik pemrograman menggunakan Jupyter Notebook. Kegiatan dilaksanakan secara luring selama dua hari dengan total peserta sebanyak 20 guru TIK. Hasil kegiatan menunjukkan bahwa peserta mengalami peningkatan pemahaman konsep dasar Python seperti variabel, tipe data, perulangan, percabangan, dan fungsi. Selain itu, peserta juga mampu menyusun skrip sederhana untuk kebutuhan pembelajaran berbasis proyek. Evaluasi dilakukan melalui pre-test dan post-test yang menunjukkan peningkatan skor rata-rata sebesar 35%. Kegiatan ini mendapatkan respon positif dari peserta dan pihak sekolah yang mengharapkan keberlanjutan pelatihan dengan materi lanjutan di masa mendatang. Dengan adanya workshop ini, diharapkan guru-guru TIK dapat lebih percaya diri dalam mengintegrasikan Python ke dalam kegiatan pembelajaran dan mampu menjadi agen literasi digital di lingkungan sekolah.
Application of Bio-Inspired Particle Swarm Optimization Algorithm for Production Scheduling Optimization Yuniarthe, Yodhi; Purnomo, Rosyana Fitria; Sari, Resy Anggun; Dirayati, Fadhilah; Hartanto, M Budi
Journal of Information Systems and Technology Research Vol. 4 No. 2 (2025): May 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i02.1132

Abstract

Production scheduling is a fundamental aspect of manufacturing systems that significantly affects operational efficiency, resource allocation, and delivery performance. Traditional scheduling methods often struggle to solve complex, dynamic scheduling problems, resulting in suboptimal job sequencing and increased makespan. This research aims to develop a hybrid optimization algorithm by integrating Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to address inefficiencies in job shop scheduling. The proposed hybrid PSO-GA method leverages the global exploration ability of PSO and the local refinement strength of GA. The algorithm was tested on several benchmark datasets using performance metrics such as makespan, tardiness, and machine utilization. Experimental results demonstrate that the hybrid approach achieved a 12.7% improvement over standard PSO and a 15.4% improvement over GA in terms of makespan. The convergence curve also showed stable and faster optimization. These findings confirm that the hybrid PSO-GA model provides a more effective and robust solution for complex production scheduling and has strong potential for real-time application in Industry 4.0 environments
Pelatihan Pemrograman Dasar bagi Siswa SMK Miftahul Ulum dalam Rangka Mempersiapkan Kompetensi di Era Industri 4.0 dirayati, fadhilah; Purnomo , Rosyana Fitria; Sari , Resy Anggun; Susanti, Ino
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 1 (2025): Jurnal Pengabdian kepada Masyarakat Nusantara Edisi Januari - Maret
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i1.5003

Abstract

Era Industri 4.0 memengaruhi berbagai sektor, termasuk dunia kerja, sehingga lulusan SMK dituntut memiliki kompetensi teknologi informasi, seperti keterampilan pemrograman. Kegiatan pengabdian ini bertujuan meningkatkan kemampuan pemrograman dasar siswa SMK Miftahul Ulum sebagai persiapan menghadapi era digital. Pelatihan dilakukan dengan metode hands-on learning, yang melibatkan siswa secara langsung dalam membuat program sederhana. Kegiatan ini diikuti oleh 30 siswa dengan materi meliputi logika algoritma, dasar-dasar Python, dan implementasi program sederhana. Hasil pelatihan menunjukkan peningkatan pemahaman siswa hingga 80% berdasarkan pre-test dan post-test, serta kemampuan siswa membuat aplikasi sederhana. Program ini menjadi langkah awal membangun kompetensi digital siswa untuk menghadapi dunia kerja di era transformasi digital. Keberlanjutan pelatihan dengan materi lanjutan diperlukan untuk meningkatkan kesiapan mereka menghadapi tantangan global.
Penerapan Algoritma C4.5 untuk Klasifikasi Tingkat Kedisiplinan Siswa Sekolah Menengah selipuri; Rosyana Fitria Purnomo; Yodhi Yuniarthe
Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 1 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v5i1.2630

Abstract

Abstract?This study aims to evaluate the performance of the Decision Tree algorithm based on the entropy criterion (C4.5) in classifying student eligibility by considering both academic and non-academic data. The dataset consists of 200 entries with nine attributes, including attendance percentage, number of lateness incidents, disciplinary violations, average academic scores, participation, study hours, and extracurricular activities. Data processing was carried out through several stages, namely cleaning, transformation, feature selection, training and testing data splitting, and model evaluation using a confusion matrix. The experimental results show that the proposed model achieved an accuracy of 87.5%, an average precision of 85.6%, an average recall of 84.2%, and an F1-Score of 84.8%. These findings confirm that the C4.5 algorithm can be effectively applied to support student performance classification with a fairly high level of reliability.
Pelatihan Python untuk Sistem Prediksi Hasil Tangkapan Ikan di Pulau Pasaran, Bandarlampung Pramono, Doni Eko Hendro; Sukri, Hamdan; Purnomo, Rosyana Fitria; Hartanto, M Budi
PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya Vol 3 No 1 (2025): PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pengamatanv3i1p27-36

Abstract

The Python training program for a fish catch prediction system in Pasaran Island, Bandarlampung, aims to enhance the efficiency and accuracy of fishery forecasts for local fishermen. Utilizing machine learning algorithms, the system processes environmental data such as sea surface temperature, chlorophyll levels, and weather conditions. This training introduces participants to Python basics, data processing, and the implementation of predictive algorithms like linear regression and artificial neural networks. Results from the training indicate an improvement in participants' understanding of predictive technology, directly supporting decision-making in fisheries activities. Furthermore, the application of this technology is expected to reduce reliance on less precise traditional methods. By integrating spatial and temporal data, this program delivers a prediction system that adapts to changing marine ecosystems, supporting sustainable fishery resource management. The study contributes to the coastal community's capacity to address challenges posed by climate change and marine economic dynamics.
ANALISIS PENGOLAHAN POLA CITRA BACKGROUND PADA WEBSITE PEMERINTAH KABUPATEN PRINGSEWU Handoko, Dwi; Purnomo, Rosyana Fitria
Journal of Software Engineering and Technology. Vol 2, No 2 (2022): SEAT: Journal Of Software Engineering and Technology
Publisher : Institut Teknologi dan Bisnis Diniyyah Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69769/seat.v2i2.66

Abstract

Website sebagai media visual, untuk menyusun halaman website memerlukan perhatian dari segi presentasi dan desain, sehingga seorang desainer website membuat keputusan apa saja yang ada di halaman website, seperti grafis, tipe warna, tata letak. Meskipun konten website memegang peranan yang penting untuk menarik minat pengunjung, perbaikan kombinasi warna pada website juga merupakan faktor penting untuk membuat tampilan website yang menarik. Penelitian menggunakan metode eksperimen partisipatif, dimana peneliti terlibat langsung dengan obyek penelitian. Obyek penelitian adalah Kabupaten Pringsewu. Teknik pengumpulan data yang dilakukan yaitu studi literatur, studi lapangan, dan wawancara. Studi literatur yaitu mencari pustaka yang berhubungan dengan penelitian, studi lapangan yaitu melakukan observasi dan pengamatan dalam pengumpulan data, wawancara yaitu turun ke lokasi penelitian untuk medapatkan sebuah data. Hasil dari analisis pengolahan pola citra background pada website pemerintah kabupaten pringsewu dapat mendeteksi warna dominan pada web pemerintahan sesuai dengan satuan dinas dan dapat memberikan suatu data yang dapat digunakan sebagai acuan pembuatan website pemerintahan dengan pola warna yang dapat menunjukan karakteristik dari suatu pemerintahan tersebut dan sesuai dengan penerimaan penggunanya. Mengetahui kombinasi warna dari website Pemerintah Kabupaten Pringsewu, mengetahui kombinasi warna pada webisite pemerintah Kabupaten Pringsewu dan mengetahui tingkat penerimaan dari kombinasi warna yang lama dengan warna yang baru.
Implementasi Program Cakap Digital dalam Peningkatan Literasi Digital Masyarakat Pramono, Doni Eko Hendro; Oktaria, Intan; Purnomo, Rosyana Fitria
Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2025): Desember 2025
Publisher : Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/japamas.v4i2.284

Abstract

The rapid development of digital technology requires society to possess adequate digital literacy and skills in order to use technology safely, ethically, and responsibly. However, various challenges are still faced by the community, including low awareness of social media ethics, personal data security, and risks in digital transactions. This community service activity aims to improve community digital literacy through the implementation of the Cakap Digital Program. The method of implementation was carried out through digital literacy socialization and educational activities using a participatory approach, including material delivery, interactive discussions, and question-and-answer sessions. The materials presented covered social media ethics, account and personal data security, safe online transactions, and an introduction to the development of artificial intelligence technology. The results of the activity indicate an improvement in participants’ understanding and awareness of the importance of using digital technology wisely and responsibly. Participants became more aware of digital risks and challenges and were able to apply digital literacy principles in their daily activities. This community service activity demonstrates that the Cakap Digital Program is effective in supporting the improvement of community digital literacy and digital competence.
Analisis Performansi Pendekatan Machine Learning pada Deteksi Penyakit Daun Tanaman Kopi Yodhi Yuniarthe; Rosyana Fitria Purnomo; Hilda Dwi Yunita; Fatimah Fahurian; Ahmad Ikhwan
Seminar Nasional Teknologi dan Multidisiplin Ilmu (SEMNASTEKMU) Vol. 5 No. 1 (2025): SEMNASTEKMU
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/p2t2nm71

Abstract

Abstract. Detection and identification of plant diseases is critical to the success and efficiency of agricultural production. Plant disease outbreaks are becoming more frequent throughout the world, and the presence of these diseases in cultivated plants has a significant impact on productivity. Therefore, researchers are focusing on developing effective and reliable plant disease detection methods. Thus, farmers can take advantage of early detection of this disease to minimize future losses. This article discusses machine learning approaches as well as decision trees, K-nearest neighbors, naive Bayes, support vector machines (SVM), and random forests for detecting coffee leaf diseases using leaf images. The above-mentioned classifications were researched and compared to determine the most suitable plant disease prediction model with the highest accuracy. Compared with other classification algorithms, the SVM algorithm achieves the highest accuracy of 99.75%. All the models trained above will be used by farmers to quickly identify and classify new diseases in images as a prevention strategy. As a preventive measure, farmers can detect and classify new diseases in images early.   Keywords: Coffee Classification, Image Processing, Machine Learning, Plant Disease Detection.  
Analisis Performansi Pendekatan Machine Learning Pada Deteksi Penyakit Daun Tanaman Kopi Purnomo, Rosyana Fitria; Yodhi Yuniarthe; Hilda Dwi Yunita; Fatimah Fahurian; Ahmad Ikhwan
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3302

Abstract

Detection and identification of plant diseases is critical to the success and efficiency of agricultural production. Plant disease outbreaks are becoming more frequent throughout the world, and the presence of these diseases in cultivated plants has a significant impact on productivity. Therefore, researchers are focusing on developing effective and reliable plant disease detection methods. Thus, farmers can take advantage of early detection of this disease to minimize future losses. This article discusses machine learning approaches as well as decision trees, K-nearest neighbors, naive Bayes, support vector machines (SVM), and random forests for detecting coffee leaf diseases using leaf images. The above-mentioned classifications were researched and compared to determine the most suitable plant disease prediction model with the highest accuracy. Compared with other classification algorithms, the SVM algorithm achieves the highest accuracy of 99.75%. All the models trained above will be used by farmers to quickly identify and classify new diseases in images as a prevention strategy. As a preventive measure, farmers can detect and classify new diseases in images early.
Pelatihan dan Penerapan Manajemen SDM untuk Meningkatkan Produktivitas UMKM Berbasis Komunitas di Desa Padang Cermin, Kabupaten Pesawaran Yudhinanto, Cahyo Nugroho; Zuhri, Khozainuz; Pramono, Doni Eko Hendro; Purnomo, Rosyana Fitria; Sari, Resy Anggun; Ikhwan, Ahmad; Hartanto, M Budi
ABDI MOESTOPO: Jurnal Pengabdian Pada Masyarakat Vol 9, No 1 (2026): Januari 2026
Publisher : Universitas Prof. Dr. Moestopo (Beragama)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32509/abdimoestopo.v9i1.6197

Abstract

This community service activity aims to improve the productivity of community-based Micro, Small, and Medium Enterprises (MSMEs) in Padang Cermin Village, Pesawaran Regency through training and the application of human resource management (HRM) principles. The program was implemented using a participatory approach that included workshops, mentoring, and evaluation sessions. The training focused on HR planning, motivation, performance appraisal, and team collaboration to strengthen the internal capacity of MSME actors. The results showed that after the training and mentoring process, participants demonstrated a better understanding of HR management concepts and were able to apply them to their daily business operations. The productivity of MSME members increased, as reflected in improved time management, teamwork, and output quality. The conclusion of this activity indicates that the application of HRM practices can significantly enhance the efficiency and sustainability of community-based MSMEs.
Co-Authors Ahmad ikhwan Alie, Maria S Anggun Sari, Ressy Budi Hartanto Dirayati, Fadhilah Dwi Handoko Fatimah Fahurian Fawaati, Teuku Muhammad Hartanto, M Budi Hendri, Romi Hendro Pramono, Doni Eko Herwanto, Riko Hilda Dwi Yunita ikhwan, Ahmad Ino Susanti Intan Oktaria Khozainuz Zuhri Luh Putu Ratna Sundari Oktaria, Eka Travilta Putra, Billy Sistian Resy Anggun Sari Riko Herwanto Rini, Prima Sekarsari, Meita selipuri Sriyanto - Sukri, Hamdan Yodhi Yuniarthe Yudhinanto, Cahyo Nugroho