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All Journal ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA J-SAKTI (Jurnal Sains Komputer dan Informatika) Majalah Ilmiah Warta Dharmawangsa Jurnal UNITEK Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Sistem Pendukung Keputusan dengan Aplikasi DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Jurnal Pengabdian Masyarakat Maneggio Journal of Computer Science Artificial Intelligence and Communications JPPM : Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Ilmu Komputer dan Teknik Informatika
Eka, Muhammad
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Religion Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Implementasi Algoritma Fp-Growth pada Sistem Persediaan Obat-Obatan Zulham, Zulham; Eka, Muhammad; Hayuni, Sabrina; Hasugian, Buyung Solihin
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 1: JUNI 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i1.6695

Abstract

Persaingan industri farmasi semakin ketat, para pelaku bisnis harus berpikir keras untuk menyusun strategi guna menghadapi persaingan. Salah satu strategi yang digunakan adalah memanfaatkan teknologi. Teknologi informasi dianggap membantu perusahaan melakukan bisnis dan perusahaan dapat menggunakan data yang dihasilkan oleh sistem informasi untuk membantu pengambilan keputusan bila ditangani dengan benar, data dapat menghasilkan informasi berharga. Cara yang dilakukan untuk pengolahan data dan menghasilkan pengetahuan baru dari data tersebut adalah dengan menggunakan teknik data mining. Teknik yang digunakan adalah algoritma FP-Growth, yaitu algoritma yang menghasilkan frequent itemset digunakan dalam proses penentuan aturan yang dapat menghasilkan pilihan. Algoritma Fp-Growth merupakan pengembangan algoritma Apriori. Algoritma Fp-Growth menggunakan konsep tree development saat mencari frequent itemset. Data digunakan adalah 26 jenis produk obat-obatan dan 60 data transaksi. Pada penelitian ini ditentukan nilai support minimal 10% dan nilai confidence minimal 30%. Dari hasil pengujian yang dilakukan diperoleh aturan dengan nilai kepercayaan 30% bahwa jika konsumen membeli antasida maka mereka juga membeli guaifenesin.
A Narrative Exploring the Potential of ChatGPT: How AI Models Are Changing the Way We Interact with Technology Eka, Muhammad; Asih, Munjiat Setiani; Damayanti, Fera; Saragih, Rusmin; Supiyandi, Supiyandi
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 1 (2024): May 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i1.5

Abstract

This study explores the perceptions, attitudes, and ethical considerations surrounding the use of ChatGPT among university students. By combining quantitative and qualitative research methods, including surveys and a review of existing literature, the study examines how ChatGPT is utilized in academic settings and its impact on learning outcomes, academic integrity, and scholarly achievements. The findings suggest that ChatGPT significantly enhances students' productivity, learning experiences, and writing abilities. However, concerns regarding its potential misuse, particularly about academic integrity, plagiarism, and over-reliance on AI tools, were also identified. The research highlights the importance of establishing clear ethical guidelines and policies to regulate the use of AI in educational settings. Future research should focus on the long-term effects of ChatGPT on students' academic development and investigate strategies for promoting responsible AI usage in higher education.
Impact of Mobile Technology Use on Knowledge Management in the Education Sector Eka, Muhammad; Lubis, Yessi Fitri Annisah; Handoko, Divi; Rismayanti, Rismayanti; Supiyandi, Supiyandi
Journal of Computer Science, Artificial Intelligence and Communications Vol 2 No 1 (2025): May 2025
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v2i1.21

Abstract

The integration of mobile technology into knowledge management (KM) practices has reshaped the landscape of information sharing and learning in the education sector. This study explores how mobile devices and applications contribute to the efficiency, accessibility, and effectiveness of KM processes among educators, students, and administrators. With the growing adoption of smartphones, tablets, and mobile learning platforms, educational institutions are experiencing a shift from traditional knowledge repositories to dynamic, real-time knowledge exchange environments. The research employs a mixed-method approach involving surveys and in-depth interviews with teachers, students, and IT staff across several secondary and higher education institutions. The findings reveal that mobile technology enhances knowledge acquisition and dissemination by enabling anytime-anywhere access to learning materials, collaborative tools, and institutional knowledge databases. However, challenges such as data security, digital literacy gaps, and resistance to change remain significant barriers to optimal utilization. Furthermore, the study highlights the role of institutional policies and support systems in facilitating effective mobile-based KM adoption. The results indicate that institutions with clear mobile technology strategies and investments in user training are more likely to achieve improved knowledge-sharing outcomes. This research provides practical insights into leveraging mobile technology to strengthen KM frameworks in education and emphasizes the need for continuous adaptation to technological advancements to sustain knowledge-based performance improvements.
Pengaruh Parameter Learning Rate terhadap Konvergensi Model Neural Network dalam Proses Pelatihan Chinthia, Maulidania Mediawati; Cynthia, Eka Pandu; Eka, Muhammad; Nursalisah, Febi
Jurnal Ilmu Komputer dan Teknik Informatika Vol. 1 No. 1 (2025): Januari 2025
Publisher : CV. Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/juikti.v1i1.45

Abstract

Dalam pengembangan model neural network, proses pelatihan memegang peranan kunci dalam menentukan kualitas generalisasi dan performa akhir model. Salah satu parameter paling krusial dalam proses pelatihan adalah learning rate, yang mengatur seberapa besar langkah pembaruan bobot dilakukan terhadap gradien fungsi kerugian. Penentuan nilai learning rate yang tepat sangat mempengaruhi kecepatan konvergensi serta stabilitas pembelajaran. Penelitian ini bertujuan untuk menganalisis secara teoritis dan eksperimental pengaruh variasi parameter learning rate terhadap konvergensi model neural network. Studi dilakukan dengan menggunakan dataset standar MNIST dan CIFAR-10 pada model multilayer perceptron (MLP) dan convolutional neural network (CNN). Parameter learning rate divariasikan dalam beberapa skenario, mulai dari sangat kecil (1e-5) hingga besar (1e-1), dan dievaluasi berdasarkan laju konvergensi, kestabilan loss, serta akurasi validasi. Hasil penelitian menunjukkan bahwa learning rate yang terlalu kecil menyebabkan proses pelatihan lambat dan berisiko terjebak dalam local minima, sementara learning rate yang terlalu besar menyebabkan fluktuasi signifikan bahkan divergensi. Ditemukan bahwa terdapat kisaran nilai learning rate optimal yang bersifat kontekstual terhadap arsitektur model dan karakteristik data. Selain itu, implementasi teknik penyesuaian dinamis seperti learning rate decay atau adaptive learning rate methods (misalnya Adam, RMSprop) secara signifikan membantu mempercepat konvergensi dan meningkatkan kestabilan pelatihan. Temuan ini menegaskan pentingnya pemilihan dan penyetelan learning rate yang tepat untuk menghindari permasalahan underfitting maupun overfitting, sekaligus memaksimalkan efisiensi pelatihan model neural network secara keseluruhan.
PENINGKATAN PRODUKTIVITAS TAMBAK UDANG MELALUI DIGITALISASI DAN PELATIHAN KOMPUTER Rahmah, Sabrina Aulia; Simon, Jhon; Suhariyanti, Suhariyanti; Eka, Muhammad
JPPM : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 1, No 1 (2024): September
Publisher : Compart Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63854/jppm.v1i1.1

Abstract

Pengabdian kepada masyarakat ini bertujuan untuk meningkatkan produktivitas tambak udang melalui digitalisasi dan pelatihan komputer. Program ini memberikan pelatihan kepada petambak udang mengenai penggunaan teknologi komputer untuk manajemen tambak, seperti pemantauan kualitas air, pencatatan produksi, dan analisis data. Selain itu, peserta juga dibekali dengan keterampilan dasar komputer dan aplikasi yang relevan. Hasil kegiatan menunjukkan peningkatan efisiensi operasional dan pengelolaan tambak yang lebih baik. Petambak yang terlibat mampu mengimplementasikan teknologi dengan efektif, sehingga berpotensi meningkatkan hasil produksi dan profitabilitas tambak.
Implementasi Sistem Informasi Pengaduan Masyarakat Berbasis Web dengan Automatic Ticketing Workflow Hendry, Hendry; Supiyandi, Supiyandi; Rizal, Chairul; Eka, Muhammad; Zulham, Zulham
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 2 (2025): September 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i2.694

Abstract

Penanganan pengaduan masyarakat sering terhambat oleh proses manual yang tidak terstruktur, menyebabkan respons yang lambat dan hilangnya riwayat penanganan. Penelitian ini mengembangkan dan menerapkan Sistem Informasi Pengaduan Masyarakat berbasis web yang dilengkapi dengan mekanisme automatic ticketing workflow untuk memastikan setiap laporan tercatat, terverifikasi, dan dialirkan ke unit terkait secara otomatis. Sistem dirancang menggunakan arsitektur modular dengan fitur inti berupa pelacakan status tiket, notifikasi otomatis, serta dashboard analitik untuk memantau kinerja penanganan. Metode pengembangan yang digunakan adalah pendekatan waterfall dengan tahapan analisis kebutuhan, desain sistem, implementasi, dan pengujian. Hasil penerapan menunjukkan bahwa otomatisasi alur tiket mampu mempersingkat waktu disposisi, meningkatkan akurasi distribusi laporan, dan memberikan transparansi proses bagi pengguna maupun admin. Pengujian fungsional juga menunjukkan tingkat keberhasilan fitur sebesar lebih dari 95%, menandakan sistem berjalan stabil dan memenuhi kebutuhan operasional. Temuan ini menegaskan bahwa integrasi automatic ticketing dalam sistem pengaduan mampu meningkatkan efisiensi, akuntabilitas, serta kualitas pelayanan publik.
Pelatihan Dan Penerapan Sistem Surat Digital Untuk Meningkatkan Efisiensi Administrasi di Kantor Kepala Desa Dalu Sepuluh Zulham, Zulham; Hasugian, Buyung Solihin; Eka, Muhammad; Wahyuni, Sri
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.v4i2.305

Abstract

The rapid development of information technology, particularly artificial intelligence (AI), requires teachers to integrate digital tools into the learning process. However, many teachers still face difficulties in creating engaging, systematic, and communicative presentation media due to limited time, insufficient design skills, and high administrative workloads. This problem was also found among teachers at SMA Negeri 5 Medan, who mostly relied on conventional presentation media. As a solution, this community service activity was conducted through training on the utilization of the Gamma Application, an AI-based platform that enables automatic presentation creation using text-based commands. A total of 30 teachers participated in this activity. The methods applied included workshops, hands-on practice, and interactive discussion sessions. Teachers were guided from the introduction of Gamma’s features to content development and the production of ready-to-use presentation slides. This activity aimed to improve teachers’ digital competence and support the development of more innovative, attractive, and effective learning media. Its main contribution lies in enhancing teachers’ skills in using AI-based technology and strengthening digital-based learning practices in schools. The results showed that all participants were able to operate the Gamma Application and produce more visually appealing, well-structured, and communicative learning presentations. Furthermore, teachers’ understanding of the role of technology in supporting the learning process significantly improved. Therefore, this activity had a positive impact on the quality of instructional media and teachers’ insights into the use of digital technology.
PENERAPAN ALGORITMA K-MEANS CLUSTERING PADA APLIKASI MENENTUKAN BERAT BADAN IDEAL Nasution, Yusuf Ramadhan; Eka, Muhammad
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 2, No 1 (2018): April 2018
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (380.867 KB) | DOI: 10.30829/algoritma.v2i1.1620

Abstract

One application of computer technology in the medical world is to determine the ideal body weight (BMI) of a patient by comparing the body weight, height, and size of the patient's own skeleton, so doctors can determine the diet menu that is most suitable for such patients. This becomes very important, especially in the field of medicine, such as the field of beauty, athletes, or other fields that require ideal body shapes such as models, artists and so forth. This ideal body weighting system is done by the ratio of height to body weight, and the size of the patient's frame. While the K-Means Clustering algorithm is an algorithm that can classify data based on benchmark values given and calculate the data group. This system can be used to determine ideal body weight by applying BMI values as X coefficients and the patient frame size values as the Y coefficients and cluster central points are set first. However, this system still needs further development because there is no change facility to clustering data category, grouping process is shown in the form of animation, and the need of clustering category in store in one structured database. Keywords: Ideal Weight, K-Means Clustering Algorithm
Co-Authors Abbrar, Rayhan Sultan Arief Budiman Asih, Munjiat Setiani Buyung Solihin Hasugian Chinthia, Maulidania Mediawati Damayanti, Fera David David Eka Pandu Cynthia Hafizah, Akhwani Shifa Handoko, Divi Hayuni, Sabrina Hendry Ibnu Rusydi Laura Lahindah, Laura Lestari, Yuyun Dwi Novita Anggraini nursalisah, febi Ramadhan, Deri Rismayanti Rismayanti Rizal, Chairul Rusmin Saragih, Rusmin Sabrina Aulia Rahmah Setiawaty, Susanti Siahaan, Melva Aliyah Royani Simon, Jhon Siregar, Rara Astili Sri Wahyuni Suhariyanti, Suhariyanti Supiyandi Supiyandi Usadani , Sih Ramping Yessi Fitri Annisah Lubis Yusuf Ramadhan Nasution, Yusuf Ramadhan Zulham Zulham