Article Per Year (5 Year)
p-Index From 2020 - 2025
3.249
P-Index
This Author published in this journals
All Journal Teknosains: Media Informasi Sains dan Teknologi Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Media Informatika Brilliance: Research of Artificial Intelligence Algoritme Jurnal Mahasiswa Teknik Informatika Informatics and Enginering Dedication Jurnal INFOTEL
gasim, Gasim
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics Physics Social Sciences Other

Published : 19 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 19 Documents
Search

 1   2 
Identifikasi Kadar Ikan Pada Pempek Menggunakan Teknik Blok Citra Dengan Fitur GLCM Dan Metode JST Saputri, Nurdiana Dewi; Gasim, Gasim
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 3 No 1 (2022): Oktober 2022 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

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

Abstract

As we know today, Indonesia has many unique foods, each in each region. For example, pempek is a typical food from Palembang, South Sumatra. The ingredients for making pempek do not only use fish, but there are many different dough formulas that create different flavor compositions. Differences that occur in the dough formula when making pempek will affect the texture and taste, because there is a mixture of fish and the amount of flour. The research uses image block techniques with GLCM (Gray Level Co-Occurrence Matrix) features and artificial neural network methods. The GLCM (Gray Level Co-Occurrence Matrix) feature extraction used consists of Entropy, Standard Deviation, Contrast, Angular Second Moment (ASM)/ Homogeneity, Correlation, and Inverse Different Moment (IDM)/ Energy. The dataset used in this study is to use the best results at a portrait distance of 13 cm from previous studies. There are 4 types of comparisons used, namely 1 fish 1 flour, 1.5 fish 1 flour, 2 fish 1 flour, and 1 fish 2 flour. The recognition results obtained in this study were 360 recognized training data and 89 recognized test data and obtained an accuracy rate of 37.08%.
Identifikasi Kadar Ikan Pada Pempek Dengan Fitur LBP Dan Metode Pengenalan SVM Suhanto, Kevita Titany; Gasim, Gasim
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 3 No 1 (2022): Oktober 2022 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i1.3363

Abstract

The main ingredients commonly used by the community in making pempek are ground fish and sago flour. The people of Palembang usually make pempek into several variants such as egg pempek, pempek pistel, pempek curly, pempek submarine, pempek roasted, pempek lenggang, etc. In the previous study, the dataset was 4 types of pempek lenjer with different levels of snakehead fish and flour, where each comparison was equal to 200 grams. The comparisons are: 1 snakehead fish to 1 sago flour, 1.5 snakehead fish to 1 sago flour, 2 snakehead fish to 1 sago flour, 1 snakehead fish to 2 sago flour. In this study, the dataset used is a photo image using a 2MP camera resolution which is the best dataset from previous research (Amatullah, 2021) which obtained an accuracy rate of 23.33% and the number of test data recognition was 56 out of 240 test data. Then this research was conducted using LBP feature extraction and the introduction of the Support Vector Machine method which resulted in an accuracy rate of 22.92%.
Identifikasi Kadar Ikan Pada Pempek Menggunakan Fitur GLCM dan SVM Naufal, Muhammad Afif; Gasim, Gasim
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 3 No 2 (2023): April 2023 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v3i2.4791

Abstract

Pempek merupakan makanan khas kota Palembang, Sumatera Selatan. Pempek dibuat dari olahan daging ikan giling yang sebelumnya telah dikuliti dan dipisahkan dari duri halus. Perbandingan pada pempek tersebut selain dapat diketahui oleh orang awam melalui rasa dapat juga diketahui melalui media elektronik yakni melalui kecerdasan buatan. Penelitian ini dilakukan untuk mengetahui perbandingan kadar ikan pada pempek dengan empat jenis kadar perbandingan yakni kadar 1 terdiri dari 1 ikan gabus 1 tepung (1:1), kadar 2 terdiri dari 1.5 ikan gabus 1 tepung (1.5:1), kadar 3 terdiri dari 2 ikan gabus 1 tepung (2:1), dan kadar 4 terdiri dari 1 ikan gabus 2 tepung (1:2). Metode pengenalan yang digunakan Support Vector Machine dengan ekstraksi fitur GLCM dengan dua jenis parameter yang berbeda yakni menggunakan GLCM dengan 4 parameter yang terdiri dari nilai Contras, Homogeneity, Correlation, dan Energy. Dan GLCM dengan 2 parameter yang terdiri dari nilai Homogeneity dan Correlation. Klasifikasi menggunakan metode SVM dengan ekstraksi GLCM dua parameter berbeda pada penelitian ini mendapatkan nilai akurasi sebesar 25.83% pada ekstraksi GLCM empat parameter, sedangkan hasil dari SVM dengan ekstraksi GLCM dua parameter hanya 25%.
Pelatihan Desain Grafis Untuk Para Siswi MA Muqimus Sunnah Palembang Pratama, Dicky; Alamsyah, Derry; Gasim, Gasim; Elizabeth, Triana; Yoannita, Yoannita; Tinaliah, Tinaliah
FORDICATE Vol 1 No 1 (2021): November 2021
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (333.917 KB) | DOI: 10.35957/fordicate.v1i1.1622

Abstract

Community service activity in the form of providing training wereheld on Friday, July 5, 2019 at the MA Muqimus Sunnah School inPalembang. This training aims to conduct graphic design training usingAdobe Photoshop application for 25 students to improve their knowledge inpractice about how to create two dimensional design using Adobe Photoshopapplication such as logo design, poster design, and photo editing. This activityinclude substantial information of the activity, followed by demonstrations inpracticing the application to create designs and testing activities to know howmuch the students can understand the training materials that have beenprovided. At practical session on designing logo and poster, participants weregiven guidance on concepts of how to make good logo such as in choosingcolors, shapes, sizes, and letters or numbers used on logo, The results of thetraining show the students can understand and use tools in Adobe Photoshopapplication to add and organize text, cut and move images, students cancreate logos, posters, and edit images/photos using Adobe Photoshopapplications.
Pelatihan Digital Marketing Dengan Market Place Toko Talk Pada Usaha Kuliner RM Pondok Kolam Sangabut Hartati, Ery; Gasim, Gasim; Inayatullah, Inayatullah; Michael, Michael
FORDICATE Vol 1 No 2 (2022): April 2022
Publisher : Universitas Multi Data Palembang, Fakultas Ilmu Komputer dan Rekayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (716.697 KB) | DOI: 10.35957/fordicate.v1i2.2414

Abstract

Tri Dharma perguruan tinggi adalah kewajiban bagi setiap dosen yang harus dijalankan setiap semester dalam tahun ajaran. Adapun Tri Dharma Perguruan Tinggi meliputi pengajaran, penelitian, dan pengabdian kepada masyarakat. Pengabdian kepada masyarakat memberikan esensi penting secara sosial agar memberikan manfaat secara langsung bagi masyarakat umum. Selain itu juga memberikan pengalaman bagi dosen yang bersangkutan agar dapat melakukan inovasi pengetahuan. Pengabdian kepada masyarakat ini dilaksanakan di RM Kuliner dan Pemancingan Sangabut Kayu Agung. Pengabdian ini dilaksanakan oleh dosen lingkungan Universitas MDP dengan persetujuan dari Rektor Universitas MDP. Usaha yang akan hadir yaitu para Usaha Kuliner untuk mengikuti Workshop Pemanfaatan Digital marketing dan Pembuatan Laporan Keuangan Bagi Usaha Usaha Kuliner. Dalam pelatihan ini nanti diharapkan para usaha dapat melakukan pembuatan Digital marketing dan Pembuatan Laporan Keuangan guna membantu dalam kegiatan operasional usaha mereka dan selain itu juga dapat lebih meningkatkan kompetensi para Usaha Kuliner RM Pondok Kolam Sangabut di Kota Kayu Agung.
Analisis Sentimen Supporter Sriwijaya FC Berbasis Manchine Learning Farhan, Muhammad; Puspasari, Shinta; Gasim, Gasim
Algoritme Jurnal Mahasiswa Teknik Informatika Vol 6 No 1 (2025): Oktober 2025 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v6i1.11288

Abstract

This study analyzes the sentiment of Sriwijaya FC supporters toward the club's management through comments on Instagram. Data was collected from 6,601 comments on the official @SriwijayaFC account and processed through text preprocessing stages with an 80:20 split for training and testing data. The analysis was conducted using four machine learning algorithms: SVM, Random Forest, Naïve Bayes, and KNN. The results indicate that neutral sentiment dominates (50.92%), followed by positive (25.07%) and negative (24.01%) sentiment, suggesting that most comments are informative or impartial, although there are both supporting and opposing opinions. Model performance evaluation using a confusion matrix and accuracy, precision, recall, and F1-score metrics shows that SVM achieved the highest accuracy (89%), followed by Random Forest (82%), Naïve Bayes (74%), and KNN (65%). These findings demonstrate that machine learning is effective in classifying social media sentiment. Future research may explore deep learning algorithms and expand data sources to other platforms for a more comprehensive analysis.
Pelatihan Canva Dan Capcut Untuk Meningkatkan Kemampuan Komunikasi Dan Kreativitas Guru Dan Peserta Didik Sekolah Dasar Mair, Zaid Romegar; Sartika, Dewi; Heriasyah, Rudi; Gasim, Gasim; Permatasari, Indah; Purnamasari, Evi
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 7 No. 3 (2024): Juli 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v7i3.3331

Abstract

Abstract: One of the prioritized areas of knowledge is mastery of information technology on computers as a sustainable generation prepares to welcome Golden Indonesia in 2045. Canva and capcut training are part of efforts to develop 21st-century skills. This training is carried out to prepare teachers and students to become people who have innovative ideas for carrying out learning. SD Negeri 150, located at Jl. TP Demsi Husin Darmajaya Gandus, Pulo Kerto, Gandus District, Palembang City, served as the venue for this activity. The results of the observations made showed that the level of enthusiasm, communication skills, and creativity of teachers and students increased significantly, as evidenced by the publication of projects carried out during the training, which were shared via social media and teacher and principal communication groups.Keywords: canva dan capcut; innovation; teacherAbstrak: Salah satu bidang ilmu pengetahuan yang diprioritaskan adalah penguasaan teknologi informasi pada komputer, sebagai generasi keberlanjutan dalam menyiapkan tokoh berikutnya untuk menyambut Indonesia Emas 2045. Tuntutan abad ke-21 merujuk pada keterampilan, pengetahuan, dan sikap yang dianggap penting untuk sukses dalam era globalisasi dan teknologi yang berkembang pesat. Pelatihan Canva dan capcut merupakan bagian dari upaya untuk mengembangkan keterampilan abad 21. Pelatihan ini dilaksanakan  untuk mempersiapkan para guru dan peserta didik menjadi orang yang memiliki ide inovasi dalam melaksanakan pembelajaran. Kegiatan ini dilakukan di SD Negeri 150, yang beralamatkan di Jl. TP Demsi Husin Darmajaya Gandus, Pulo Kerto, Kecamatan Gandus, Kota Palembang. Metode yang digunakan dalam kegiatan ini mencakup pengumpulan data dari bahan pustaka, observasi, dan wawancara. Hasil pengamatan yang dilakukan, bahwa tingkat antusias, keterampilan berkomunikasi, kreativitas guru, dan peserta didik meningkat secara signifikan, dibuktikan dengan publikasi projek yang dikerjakan selama pelatihan yang dibagikan melalui medsos, dan grup komunikasi guru dan Kepala Sekolah.Kata kunci: canva dan capcut; inovasi; guru
Improving the Accuracy of Concrete Mix Type Recognition with ANN and GLCM Features Based on Image Resolution Gasim, Gasim; Heriansyah, Rudi; Puspasari, Shinta; Irfani, Muhammad Haviz; Purnamasari, Evi; Permatasari, Indah; Samsuryadi, Samsuryadi
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1201

Abstract

Concrete is an essential construction material that is often used due to its strength and durability, but its mix type identification often relies on conventional methods that are less efficient and accurate. This research aims to evaluate the effect of image resolution on the accuracy of concrete mix type recognition using Artificial Neural Network (ANN) and Gray-Level Co-Occurrence Matrix (GLCM) features. The method used involves analysing concrete images at various resolutions: 200 x 200, 300 x 300, 400 x 400, 500 x 500, 600 x 600, and 700 x 700 pixels. The experimental results show that higher image resolutions tend to improve recognition accuracy. all types of image sizes using 1,250 training data and 250 test data. Image sizes of 200 x 200 and 300 x 300 pixels give low accuracy of 42% and 45% respectively, while sizes of 400 x 400 and 500 x 500 pixels show an increase in accuracy to 60.5% and 62.5%. The higher resolutions of 600 x 600 and 700 x 700 pixels produced the highest accuracy of 68% and 70%, respectively. These results indicate that larger image resolutions are able to capture more details and characteristics required for more accurate concrete mix type recognition. This research has implications for improving efficiency and consistency in concrete inspection in the construction industry through the use of AI-based image recognition methods.
Identifikasi Kualitas Batik Berdasarkan Jarak Pengambilan Gambar Menggunakan K-Nearest Neighbor Faza Nujjiya, Muhammad Alief; Gasim, Gasim; Mair, Zaid Romegar
Jurnal Media Informatika Vol. 6 No. 6 (2025): Edisi Nopember - Desember 2025
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jumin.v6i6.7130

Abstract

Penelitian ini bertujuan untuk mengevaluasi pengaruh jarak pengambilan gambar terhadap akurasi identifikasi kualitas kain batik menggunakan metode K-Nearest Neighbor (K-NN) dengan ekstraksi fitur tekstur Gray Level Co-occurrence Matrix (GLCM). Data yang digunakan berupa citra lima motif batik tradisional yang diambil pada enam variasi jarak: 10, 20, 30, 40, 50, dan 60 cm. Tahapan pra-pemrosesan meliputi auto-cropping citra ke ukuran 500×500 piksel, konversi ke grayscale, dan kuantisasi 8 level. Empat fitur utama GLCM contrast, energy, homogeneity, dan entropy diekstraksi dan digunakan sebagai masukan bagi K-NN dengan nilai k=1. Hasil penelitian menunjukkan bahwa jarak 30 cm memberikan akurasi tertinggi sebesar 100%, sedangkan jarak 20 cm dan 10 cm mencapai 80%, jarak 40–50 cm turun menjadi 60%, dan jarak 60 cm hanya 40%. Temuan ini menegaskan bahwa jarak pemotretan berpengaruh signifikan terhadap kualitas identifikasi berbasis tekstur. Kesimpulannya, jarak optimal untuk akuisisi citra batik adalah rentang 20–40 cm, khususnya 30 cm, yang direkomendasikan sebagai standar pada sistem identifikasi kualitas batik berbasis citra.
Co-Authors A, Satria Andika, Rizki Chandra B, Leonardo Derry Alamsyah Desy Iba Ricoida DEWI SARTIKA Dicky Pratama Dina Agustina, Dina Faza Nujjiya, Muhammad Alief Hartati, Ery Heriasyah, Rudi Inayatullah, Inayatullah Indah Permatasari Juniawan, Rycci Michael Michael Muhammad Farhan Muhammad Haviz Irfani Naufal, Muhammad Afif Purnamasari, Evi Rizani Teguh Rudi Heriansyah, Rudi rusbandi rusbandi, rusbandi Samsuryadi Samsuryadi Saputri, Nurdiana Dewi Shinta Puspasari Siregar, Muhammad Azwar Tsar Sudiadi, Sudiadi Suhanto, Kevita Titany Tanjungan, Erven Tinaliah, Tinaliah Triana Elizabeth, Triana Wilsen, Erick Brilliant Yoannita, Yoannita