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All Journal Computer Based Information System Journal Indonesian Journal of Electrical Engineering and Computer Science Jurnal Computer Science and Information Technology (CoSciTech) Majalah Ilmiah UPI YPTK Jurnal Ipteks Terapan : research of applied science and education Jurnal Pustaka Mitra : Pusat Akses Kajian Mengabdi Terhadap Masyarakat Jurnal Sains Informatika Terapan (JSIT) Indonesian Journal of Informatic Research and Software Engineering JOURNAL OF COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS) The Indonesian Journal of Computer Science Jurnal Pustaka Paket
Muhammad, Abulwafa
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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ALGORITMA K-MEANS CLUSTER UNTUK SEGMENTASI PELANGGAN Fazri, Ahmad Harya; Muhammad, Abulwafa; Purnama, Pradani Ayu Widya
Computer Based Information System Journal Vol. 11 No. 2 (2023): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v11i2.7156

Abstract

Consumer data for business transactions in retail agricultural products has not been managed digitally. This can be seen from consumer data which is still stored manually, some customer data is stored only based on purchase receipts and others have logbooks so that consumer data can be lost at any time. To improve service to consumers, sales analysis is carried out using the k-means algorithm. The aim is to be able to group consumers based on the number of transactions, the number of products purchased, and the frequency of transactions made. The data processed was 127 transaction data and grouped by name of the consumer, 116 consumers made transactions in the last 1 months. From this data, 5 clusters were determined including: Superstar, Golden, Typical, Occasional, Everyday. Of the 5 clusters, there were 4 consumers including Superstar, 12 Golden consumers, 34 Typical consumers, 29 Occasional consumers and 37 Everiday consumers.
Analisis Sistem Pengambilan Keputusan Terhadap Risiko Keselamatan Kerja Dan Lingkungan Kerja Dalam Bongkar Muat Kapal Pada PT Pelabuhan Indonesia (Persero) Regional 2 Teluk Bayur Dengan Menggunaka Metode Analytical Hierarchy Process (AHP) Wahyudi, Indra; Muhammad, Abulwafa; Ariandi, Vicky
Jurnal Sains Informatika Terapan Vol. 4 No. 2 (2025): Jurnal Sains Informatika Terapan (Juni, 2025)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v4i2.569

Abstract

This study aims to analyze the decision-making system related to occupational safety and environmental risks in the loading and unloading activities of ships at PT Pelabuhan Indonesia (Persero) Regional 2 Teluk Bayur. With the increasing complexity and risks faced in port operations, it is essential to apply a systematic method in decision-making. The Analytical Hierarchy Process (AHP) method was chosen as an analytical tool to evaluate various factors affecting safety and environmental work.Through this research, data were collected from loading and unloading activities over the past five years, which included an analysis of potential risks. The results of the study indicate that the application of AHP can assist in identifying and prioritizing risk factors, as well as providing recommendations for more effective hazard control. This research also found that with a good decision-making system, PT Pelabuhan Indonesia (Persero) Regional 2 Teluk Bayur can enhance occupational safety and minimize negative impacts on the environment. From the analysis results, it is hoped that this research can make a significant contribution to the development of risk management systems in the port sector and serve as a reference for other companies in managing occupational safety and the environment.
Pelatihan Penggunaan Aplikasi Canva Untuk Meningkatkan Kualitas Desain Produk Bagi Usaha Menengah Syafnur, Afdhal; Yusda, Riki Andri; Muhammad, Abulwafa
Jurnal Pustaka Paket Vol 3 No 1 (2024): Jurnal Pustaka PAKET
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakapaket.v3i1.540

Abstract

Pelatihan ini bertujuan untuk meningkatkan kualitas desain produk bagi usaha menengah melalui pemanfaatan aplikasi Canva. Peserta pelatihan diberikan pemahaman mendalam tentang antarmuka dan fitur dasar Canva, serta diajak untuk mengembangkan kemampuan desain mereka. Fokus utama adalah penerapan identitas merek ke dalam desain produk, menciptakan konsistensi visual yang mendukung citra merek. Melalui pendekatan praktis dan studi kasus, peserta diajak untuk menjadi lebih kreatif dan inovatif dalam penggunaan elemen desain serta memahami pentingnya desain produk dalam mempengaruhi persepsi pelanggan. Diskusi antara peserta juga menjadi bagian integral dari pembelajaran, memfasilitasi pertukaran pengalaman dan umpan balik untuk mencapai hasil yang optimal. Dengan demikian, pelatihan ini diharapkan memberikan kontribusi positif terhadap peningkatan kualitas desain produk dan daya saing usaha menengah di pasar yang semakin kompetitif.
Digital Entrepreneurship with Training in Making Handicraft Accessories for Students at the PGAI Padang Orphanage MUHAMMAD, ABULWAFA; Mutiana Pratiwi; Rima Liana Gema
Journal of Community Service and Application of Science Vol. 4 No. 2 (2025): COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS)
Publisher : KPN Kopertis X

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62769/deagn415

Abstract

  The PGAI Foundation (Persatuan Guru Agama Islam) is a foundation that manages orphanages, schools and several other units in the city of Padang. Specifically, the children living in the orphanages come from various backgrounds and school age levels. They live and attend school at schools managed by the foundation, and some also attend public schools. One of the problems faced by these children is that they are accustomed to waiting for donations from donors for various activities. Although this is not the case for every child, it is certainly not good for their future. We provide handicraft training in the form of making accessories using digital technology. The students are given several product design examples and then given the freedom to develop their own products. The products produced are accessories such as bracelets, necklaces, rings and others made from beads. After the students are able to make the products, they are given knowledge on how to package the products. The students are also equipped with knowledge on how to utilise digital technology in obtaining product design references, promotion and marketing of their products. After this training, the children in the orphanage have acquired the skills to make various accessory products and have knowledge of digital entrepreneurship. This training has produced over 50 pieces of accessory products, including bracelets, rings, and several other items that are ready for marketing.
Penerapan Metode Trend Moment Untuk Memprediksi Penjualan Kayu Dalam Meningkatkan Efisiensi Stok Pada CV Intan Jaya Tinsky, Muhammad Jaya; Muhammad, Abulwafa; Syahputra, Hadi
Jurnal Sains Informatika Terapan Vol. 5 No. 1 (2026): Jurnal Sains Informatika Terapan (Februari, 2026)
Publisher : Riset Sinergi Indonesia (RISINDO)

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

Abstract

Pengelolaan persediaan yang efektif sangat diperlukan untuk mencegah masalah kelebihan atau kekurangan barang yang dapat merugikan perusahaan, khususnya perusahaan perdagangan kayu. Metode Trend Momentdipilih karena kemampuannya dalam menganalisis data masa lalu dan memperkirakan kebutuhan persediaan di masa mendatang.Studi ini dimulaidengan mengumpulkan data penjualan kayu pada CVIntan Jaya dengan jenis kayu yaitu Kayu Banio, Kayu Timbalun,dan Kayu Bayua dalam jangkawaktu 2 tahun (Januari 2023 sampai dengan Desember 2024).Data ini dianalisis untuk mengetahui tren dan pola musiman yang dapat berdampak pada permintaan produk. Hasil analisis menunjukkan bahwa metode Trend Momentdapat memberikan ramalan yang tepat mengenai perkembangan penjualan produk. Dengan menerapkan metode ini, perusahaan dapat merumuskan strategi pemasaran yang lebih fokus, menyesuaikan volume produksi berdasarkan permintaan pasar, serta meminimalkan risiko kelebihan ataukekurangan persediaan. Temuan dari penelitian ini mengindikasikan bahwa pendekatan ini dapat menghasilkan tingkat akurasi yang tinggi dalam memperkirakan volume penjualan. Dengan memanfaatkan data uji ramalan untuk kayu banio 4cm*6cm pada bulan Januari 2025, nilai Absolute Percentage Error(APE) yang diperoleh adalah sebesar 1.0309%. Pada penelitian ini Metode Trend Momentterbukti efektif dalam mendukung peramalan produk guna meningkatkan ketepatan pengelolaan persediaan.
Twitter Sentiment Analysis of Public Space Opinions using SVM and TF-IDF Methods Arsyah, Ulya Ilhami; Pratiwi, Mutiana; Muhammad, Abulwafa
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3594

Abstract

Public space opinion reviews are currently a source of information for interested parties and decision-makers. Twitter is a social media that is a means of expressing themselves for people to express their opinions and criticize the current situation. This becomes information for readers. Information published on Twitter contains elements of commentary on a situation or object Sentiment analysis of public space opinion on Twitter using Machine Learning with the Support Vector Machine (SVM) method with the data weighting process using the Term Frequency-Inverse Document Frequency (TF-IDF) method. Dataset obtained by scraping using the Twitter API as much as 5000 data then labeled where the goal is to get accuracy on positive, negative, or neutral sentiment. The results of research conducted experiments on three Machine Learning algorithms with the extraction function "TF-IDF" obtained an accurate training model with good classification capabilities, especially SVM of 91,6% on data distribution 70: 30; SVM is 92.8% in the case of data distribution of 80: 20; the SVM is 91,8% in the case of 90:10 decomposition data.
Co-Authors Abda Abda Aggy Pramana Gusman Ariandi , Vicky Ariandi, Vicky Arsyah, Ulya Ilhami Asrizal, Erick Dhio Saputra Dinul Akhiyar Eka Praja Wiyata Mandala Fazri, Ahmad Harya Gema, Rima Liana Guslendra Guslendra Hadi Syahputra Indra Wahyudi, Indra Kurnia, Nensi Lusinia, Shary Armonitha Muhammad Rio Akbar Mutiana Pratiwi Pratiwi, Mutiana Purnama, Pradani Ayu Widya Rhayatun Aviqah Riki Iskandar Rini Sovia Sarjon Defit Sarjon Defit Sumijan Syafnur, Afdhal Syafri Arlis Tinsky, Muhammad Jaya Vivi Nila Sari yanto, heri Yuki Saputra Yuliandri, Mario Yusda, Riki Andri