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PELATIHAN PEMBUATAN GAME MENGGUNAKAN GDEVELOP UNTUK SISWA/I SMA NEGERI 6 PALEMBANG Yohannes Yohannes; Siska Devella; Meiriyama Meiriyama
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 5, No 1 (2021): Desember
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v5i1.6333

Abstract

ABSTRAKKegiatan pengabdian kepada masyarakat dalam bentuk pelatihan pembuatan game dengan menggunakan GDevelop memiliki tujuan yaitu untuk memberikan wawasan kepada siswa dan siswi SMA Negeri 6 Palembang dalam menggunakan aplikasi GDevelop yang dapat digunakan untuk membuat game sehingga dapat menambah keterampilan dan wawasan. Terdapat tiga tahapan utama yang dilakukan dalam pengabdian ini antara lain perencanaan, implementasi dan terakhir adalah evaluasi dengan memberikan tautan kuesioner berupa google form. Hasil kuesioner menunjukkan bahwa   didapatkan rata-rata 96,8% peserta merasakan manfaat dan sangat setuju dengan pelatihan yang telah dilakukan. Kata kunci: game; gdevelop; pelatihan; pengabdian kepada masyarakat. ABSTRACTCommunity service activities in the form of training in making games using GDevelope aim to provide insight to students of SMA Negeri 6 Palembang in using the GDevelop application for making of the video games, so the students can add skills and insights. There are three main stages carried out in this service, including planning, implementation and finally evaluation by providing a questionnaire link in the form of a google form. The results of the questionnaire showed that an average of 96.8% of participants feel the benefits and strongly agreed with the training that had been carried out. Keywords: community service activities; game; gdevelop training.
Disain Model Samba Primary Domain Controller (PDC) Sebagai Network Drive Pada Laboratorium Jaringan Komputer Molavi Arman; Meiriyama Meiriyama
Jurnal Informatika Global Vol 13, No 1
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v13i1.2062

Abstract

Many institutions and companies such as educational institutions and private sector or government find obstacles with file storage problems.  Current development requires institutions or companies to archive all events in the form of videos, documents, or images. What often happens is that many institutions still use conventional method of storage even though computer has been used. Besides they also do not have authorization about who could access the documents. Digital documents could be stored and accessed easily if the media of the document storage service is centralized. Companies or institutions usually share or send file documents in the workplace via email which highly depends on the file size limit and capacity and bandwidth resource, making it less effective for files with large amounts and files reaching gigabytes. One solution to cope with the problems is by designing and building centralized document sharing system using SAMBA protocol with Primary Domain Controller (PDC) and operating system using Linux Debian 9.4.  File sharing system could only be accessed locally by applying profile for each user and password in the form of network drive so that file storage and access is more secure and faster since file document do not pass through the internet network. It could also reduce computer workload in terms of storage resources.  Keywords: samba, primary domain controller , linux debian, network drive.
Klasifikasi Citra Buah berbasis fitur warna HSV dengan klasifikator SVM Meiriyama Meiriyama
Jurnal Komputer Terapan  Vol. 4 No. 1 (2018): Jurnal Komputer Terapan Mei 2018
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (999.729 KB)

Abstract

Klasifikasi citra dengan objek buah merupakan permasalahan klasik pada area klasifikasi citra yang hingga saat ini, masih menarik minat para peneliti. Dalam proses klasifikasi buah proses feature selection atau pemilihan fitur, merupakan salah satu faktor yang mempengaruhi tingkat keberhasilan dan tingkat akurasi. Pada buah terdapat beberapa jenis fitur yang dapat kita gunakan dalam proses klasifikasi, fitur warna merupakan salah satu fitur yang cukup dominan dan telah banyak digunakan pada penelitian terdahulu. Pada penelitian ini fitur model warna HSV akan digunakan pada proses klasifikasi buah dengan menggunakan klasifikator SVM. Metodologi yang diajukan adalah dengan menggunakan fitur histogram HSV yang telah dinormalisasi dan similarity dari citra training dengan citra target dengan menggunakan metode Bhattacharyya Coefficient. Fitur yang didapatkan akan digunakan pada proses training pada SVM untuk mendapatkan hyperplane yang ideal dengan margin maksimal. Setelah melakukan pengujian dengan klasifikator SVM, diketahui bahwa tingkat akurasi cukup baik, yaitu sebesar 94%, dimana SVM mampu melakukan klasifikas secara akurat terhadap jenis buah yang telah ditraining menggunakan klasifikator SVM.
Klasifikasi Daun Herbal Berdasarkan Fitur Bentuk dan Tekstur Menggunakan KNN Meiriyama Meiriyama; Siska Devella; Sandra Mareza Adelfi
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 3 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i3.2974

Abstract

Indonesia has an abundance of biodiversity. From a total of 40,000 types of herbal plants known in the world, there are approximately 30,000 types of herbal plants in Indonesia. Herbal plants are plants that are commonly used by people, especially in Indonesia, which have biodiversity as ingredients for making herbal medicines. Herbal plants are certainly not easy to recognize even though they often grow around the environment. Because there is still a lack of community knowledge about herbal plants, it is not possible to use these herbal plants. This study aims to classify the leaves of herbal plants using the K-Nearest Neighbor (KNN) method with k value is 3 and feature extraction of Histogram of Oriented Gradient (HOG) and Local Binary Patterns (LBP). The research was conducted on 15 types of herbal plants. Accuracy HOG method with KNN is 92.67%, Accuracy LBP with KNN is 88.67% and accuracy combination of HOG and LBP features with KNN method is 92.67%. Based on the three experiment scenarios that have been carried out, it shows that the combination of HOG and LBP features does not affect the accuracy of leaf classification of herbal plants.
Penerapan Algoritma Random Forest Untuk Klasifikasi Jenis Daun Herbal Meiriyama Meiriyama; Sudiadi Sudiadi
Jurnal Teknologi Sistem Informasi Vol 3 No 1 (2022): Jurnal Teknologi Sistem Informasi
Publisher : Program Studi Sistem Informasi, Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jtsi.v3i1.3176

Abstract

Indonesia memiliki potensi yang besar dalam penyediaan sumberdaya tumbuhan obat atau tanaman herbal yang dapat dimanfaatkan dengan baik sebagai media pengobatan tradisonal. Obat tradisional merupakan warisan lama turun temurun dari zaman dahulu, baik itu dalam bentuk ramuan maupun jamu. Tanaman obat merupakan spesies tanaman yang dipercaya sebagai obat alami tanpa kandungan kimia. Akan tetapi masih minimnya pengetahuan masyarakat mengenai jenis – jenis tanaman herbal. Oleh karena itu penelitian ini bertujuan untuk Klasifikasi Jenis Daun Herbal menggunakan Random Forest berdasarkan fitur HOG. Citra yang telah dipisah antara data latih dan data uji di ubah menjadi greyscale dan di resize menjadi 816x612 piksel, kemudian citra di ekstraksi menggunakan fitur HOG sehingga menghasilkan vektor sepanjang 1x3168. Algoritma Random Forest yang digunakan untuk klasifikasi daun herbal memiliki akurasi keseluruhan sebesar 85,33%.
Implementasi Sistem Pengelolaan Dokumen pada PT Sri Aneka Karyatama Juwita Maya sari; Meiriyama Meiriyama
Jurnal Teknologi Sistem Informasi Vol 4 No 1 (2023): Jurnal Teknologi Sistem Informasi
Publisher : Program Studi Sistem Informasi, Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jtsi.v4i1.4430

Abstract

PT Sri Aneka Karyatama, also known as PT.SAK, is a company that offers construction, engineering, supply and cleaning services. Founded in 1987, this company is a subsidiary of PT. Pupuk Sriwidjaja and has 26 years of experience in various business fields, with the main focus on building maintenance and cleaning services. Even so, PT. Sri Aneka Karyatama experienced problems in archiving letters, such as data collection, storage, and data corruption. Therefore, to overcome this problem, a new information system was created which included the process of inputting incoming and outgoing mail, user input, mail search, and mail reporting. The methodology used is an iterative methodology, and users of the new information system are HRD, managers and directors of PT. Sri Aneka Karyatama. The result of creating this new information system is to help simplify the incoming and outgoing mail process, save time, and reduce the obstacles experienced by company staff.
Pemanfaatan Microsoft Office dan Prezi untuk Membuat Laporan dan Presentasi di Brimob Polda Sumatera Selatan Meiriyama, Meiriyama; Yohannes, Yohannes; Irsyad, Hafiz; Farisi, Ahmad; Devella, Siska; Al Rivan, Muhammad Ezar; Rachmat, Nur
FORDICATE Vol 3 No 1 (2023): November 2023
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v3i1.6449

Abstract

Perkembangan ilmu pengetahuan dan teknologi suatu bangsa tergantung pada keberhasilan proses belajar mengajar di lembaga pendidikan. Penguasaan ilmu dan teknologi merupakan indikator pembangunan menuju kemajuan bangsa. Microsoft Office, termasuk Excel, Word, dan PowerPoint, adalah perangkat lunak aplikasi perkantoran yang dirancang untuk meningkatkan efisiensi kerja. Microsoft Word memfasilitasi pembuatan dokumen kantor, menghemat waktu, dan mengurangi penggunaan kertas. Microsoft Excel mempermudah pengolahan data numerik dengan fitur formula dan diagram. Microsoft PowerPoint mendukung pembuatan presentasi menarik dengan fitur sisipan teks, grafik, dan animasi. Selain itu, Prezi, alat presentasi berbasis internet, memungkinkan eksplorasi ide dengan konsep Zooming User Interface. Pelatihan ini ditujukan untuk staff dan anggota Brimob Polda Sumatera Selatan agar memiliki keterampilan dalam membuat dokumen, laporan, dan presentasi menggunakan Microsoft Office dan Prezi, sehingga dapat meningkatkan produktivitas dan kualitas pekerjaan.
Klasifikasi Motif Songket Palembang menggunakan Support Vector Machine berdasarkan Histogram of Oriented Gradients Yohannes, Yohannes; Al Rivan, Muhammad Ezar; Devella, Siska; Meiriyama, Meiriyama
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.1032

Abstract

Songket Palembang is one of the intangible cultural heritages with the domain of traditional craftsmanship and crafts. Songket Palembang has several motifs, including Chinese Flowers, Cantik Manis, and Pulir. Preservation efforts are carried out by providing an understanding of Palembang Songket patterns. This study classified Palembang Songket patterns based on shape features using the Histogram of Oriented Gradient (HOG) method. Based on the test results of 45 test data images, the HOG method can become a feature in the image classification of Palembang Songket patterns, namely Chinese Flowers, Cantik Manis, and Pulir. The Support Vector Machine (SVM) method is a classification method that can recognize Palembang Songket patterns with RBF, Linear, and Polynomial kernels. The results showed that the RBF kernel was the best kernel that produced an average accuracy value of 88.1%, a precision of 84.1%, a recall of 82.2%, and an f1-score of 82.6%, and the three Palembang Songket patterns tested, it was found that the Palembang Songket patterns that were easiest to classify well were the Cantik Manis patterns for all types of SVM kernels.
Ekstraksi Fitur Warna dengan Histogram HSV untuk Klasifikasi Motif Songket Palembang Yohannes, Yohannes; Al Rivan, Muhammad Ezar; Devella, Siska; Meiriyama, Meiriyama
JATISI Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.8110

Abstract

Palembang Songket is a type of traditional woven cloth that has been registered as Indonesia's intangible cultural heritage since 2013. Palembang Songket has many motifs including Bunga Cina, Cantik Manis, and Pulir. The motifs on Palembang Songket have different meanings which can influence the selling price of the Songket. Recognition and classification of Palembang Songket types and motifs can be done by utilizing computer technology such as digital image processing and machine learning. In this research, the classification of Palembang Songket motifs was carried out using color features with histograms in Hue, Saturation, and Value (HSV) space and the Support Vector Machine (SVM) machine learning algorithm. Testing was carried out on a classification system using 45 test images. The histogram of HSV and SVM methods with the best kernel, namely RBF, were able to classify Palembang Songket motifs with an accuracy of 0.956; precision of 0.94; recall of 0.933; and f1-score of 0.931.
Pelatihan Moodle Sebagai Aplikasi Learning Management System untuk Administrator Sekolah di SMA Negeri 18 Palembang Rachmat, Nur; Devella, Siska; Meiriyama, Meiriyama
FORDICATE Vol 4 No 1 (2024): November 2024
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/fordicate.v4i1.9597

Abstract

The Covid-19 pandemic requires every school to take innovative steps by utilizing technology in teaching and learning activities. Among various technological advancements in the world of education, Learning Management System (LMS) has emerged as a platform and Moodle is one of the most well-known and widely used LMS by educational institutions. Moodle has comprehensive features and is easy to understand for users. Through the Moodle LMS, educators can easily present comprehensive learning materials, create assessments, establish grading systems, track learning progress, view reports, and analyze learning outcomes. This technology is certainly desired to be adopted by State High School 18 Palembang to support a more effective learning process when conducted online. The schools action to support the smooth use of this LMS is to organize a training for school administrators. The training activities were attended by 5 staff members through direct practice methods, discussions and interactive question-and-answer sessions in the Computer Laboratory of Multi Data Palembang University.