Article Per Year (5 Year)
p-Index From 2021 - 2026
2.765
P-Index
This Author published in this journals
All Journal Jurnal TIMES Jurnal Ilmiah Universitas Batanghari Jambi JURNAL MEDIA INFORMATIKA BUDIDARMA JurTI (JURNAL TEKNOLOGI INFORMASI) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Majalah Ilmiah Warta Dharmawangsa Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Tunas JPM: JURNAL PENGABDIAN MASYARAKAT EXPLORER Prosiding Snastikom Journal of Computer Science and Informatics Engineering Jurnal Pengabdian Masyarakat Inovasi Blend Sains Jurnal Teknik Prioritas : Jurnal Pengabdian Kepada Masyarakat Keris: Journal of Community Engagement DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) JUDIS : Jurnal Multidisiplin dan Sains CompTech : Jurnal Ilmu Komputer dan Teknologi
Tengku Mohd Diansyah, Tengku Mohd
Universitas Harapan Medan
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

Published : 24 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 24 Documents
Search

 1   2   3 
PENERAPAN KLASIFIKASI C4.5 DALAM MENENTUKAN PREDIKSI YANG MEMPENGARUHI JUMLAH PRODUKSI BAHAN DASAR DALAM INDUSTRI KONVEKSI Yusuf, Al; Diansyah, Tengku Mohd
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 2: DESEMBER 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i2.7449

Abstract

Industri konveksi menghadapi tantangan dalam menentukan jumlah produksi bahan dasar akibat fluktuasi permintaan pasar dan keterbatasan bahan baku. Penelitian ini bertujuan untuk menerapkan algoritma klasifikasi C4.5 sebagai solusi prediktif berbasis data mining untuk mendukung pengambilan keputusan produksi di CV. Eternal Group. Dengan menggunakan data historis bulan Maret–Agustus 2024, sistem dirancang melalui tahapan preprocessing, perhitungan entropy dan gain ratio, serta pembentukan pohon keputusan. Hasil klasifikasi menunjukkan bahwa atribut “Permintaan Pasar” memiliki pengaruh dominan terhadap keputusan produksi, diikuti oleh “Ketersediaan Bahan Baku” dan “Tren Penjualan.” Sistem dikembangkan menggunakan PHP dan MySQL, dan diuji melalui aplikasi yang menghasilkan tingkat akurasi tinggi berdasarkan evaluasi confusion matrix. Penelitian ini tidak hanya menghasilkan sistem prediksi yang adaptif dan akurat, tetapi juga memberikan kontribusi terhadap efisiensi operasional, pengurangan pemborosan bahan baku, serta pemahaman yang lebih baik terhadap preferensi pasar. Dengan demikian, penerapan algoritma C4.5 terbukti efektif dalam mendukung strategi produksi yang lebih terukur dan responsif dalam industri konveksi.
Teknologi Pengembangan Jaringan Internet Untuk Sekolah di Pedesaan Tengku Mohd Diansyah; Ilham Faisal; Dodi Siregar; Ade Zulkarnain Hasibuan; Sayuti Rahman
JPM: Jurnal Pengabdian Masyarakat Vol. 3 No. 3 (2023): January 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v3i3.413

Abstract

In this community service activity we are developing an internet network that will be used by schools in rural areas, one of the areas in Stabat City in building this internet network we use the ubnt antenna which is reliable in spreading signals in the countryside and our goal is to build an internet network in the village, namely to help the community in obtaining information that is currently very fast and the obstacles that the surrounding community has are very difficult to connect to the internet network after the team pays attention to the problem because of the large number of palm trees that make it very difficult to get a signal in the village and even the school when the school is very fast. The obstacle that the village has is that the signal in the village is not up to 2 bars so that the surrounding community is very difficult to connect to the internet network after the team noticed the problem because of the large number of palm trees which made the signal very difficult to get by local residents and even schools currently have difficulty in the learning process, let alone accessing dapodik owned by the school which must be connected to the internet network.
Pemanfaatan Teknologi AI untuk Mengembangkan Strategi Digital Marketing Berbasis Data bagi UMKM Desa Karim, Abdul; Syahrizal, Muhammad; Diansyah, Tengku Mohd.
Jurnal Pengabdian Masyarakat Inovasi Vol. 5 No. 1 (2026): February 2026
Publisher : Sekolah Tinggi Ilmu Manajemen Sukma Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35126/jpmi.v5i1.999

Abstract

This community service program aims to enhance the capacity of micro, small, and medium enterprises (MSMEs) in Aek Pamingke Village in utilizing artificial intelligence (AI) for data-driven digital marketing strategies. The activities were conducted through several stages, including needs analysis, intensive training, practical implementation, and evaluation. The initial analysis revealed that most MSME participants had limited knowledge and skills in digital marketing, with 60% categorized as having low understanding before the program. After the training, significant improvement was recorded, with 50% of participants reporting being very satisfied and 35% satisfied. The program’s impact was evident in the participants’ improved ability to design more effective data-driven marketing strategies. The main limitations of this program were the relatively small number of participants and the limited implementation time, indicating the need for extended programs with broader coverage in the future.
Klasifikasi Penyebaran Jaringan Wifi Provider Internet Menggunakan Algoritma XGBoost Berdasarkan Titik Koneksi Kabel Fiber Optik Manihuruk, Repaldo; Diansyah, Tengku Mohd
Explorer Vol 6 No 1 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v6i1.2544

Abstract

The rapid development of fiber-optic–based internet technology has led to an increasing demand for stable and evenly distributed WiFi networks. Although internet service providers such as XYZ have established extensive fiber-optic infrastructure, challenges in WiFi access point distribution remain common, particularly regarding uneven network coverage and limited data-driven analysis. These issues raise the question of how to determine optimal WiFi deployment locations to ensure consistent service quality. Therefore, this study aims to analyze the spatial distribution patterns of XYZ’s WiFi network based on fiber-optic connection points, apply the Extreme Gradient Boosting (XGBoost) algorithm to classify the feasibility of WiFi distribution, and evaluate the performance of the proposed model in improving network distribution efficiency. This research employs XGBoost as a classification method to predict suitable and unsuitable WiFi deployment locations using customer data connected via fiber-optic cables. The study focuses on data preprocessing, model construction using XGBoost, performance evaluation in classifying feasible and non-feasible locations, and data balancing techniques to address class imbalance. The dataset consists of 193 XYZ customer records, divided into 80% training data and 20% testing data. The results demonstrate that the XGBoost algorithm achieves high classification accuracy in WiFi network distribution. Consequently, the proposed model can serve as a data-driven recommendation tool for optimizing WiFi deployment, enabling service providers to deliver more evenly distributed, stable, and efficient internet services
Co-Authors Abdul Jabbar Lubis, Abdul Jabbar Abdul Karim Abid, Nuskhan Ardiansyah, Muhammad Fahri Ari Usman Arjulayana Arjulayana Baharuddin Baharuddin Dayu Rahma Turista, Dora Dewi Kusumaningsih Dodi Siregar Dodi Siregar Elza Ilyanda Faisal, Ilham Habibie, Ananda Halawa, Kerisman Handoko, Divi Hasibuan, Ade Zulkarnain Ilham Faisal Ilham Faisal Ilham Faisal Jaenal Arifin Liza, Risko Lubis, Abdul Jabar Manihuruk, Repaldo Muhammad Ikhsan Azhari Muhammad Syahrizal N. Sofianto, Eko Wahyu Nauval Alfarizi Prida Apriani Rachmat Aulia, Rachmat Rahman, Sayuti Risko Liza Rismayanti Rismayanti Robbi, Sabbiisma Salsabila, Salsabila Syahendra Surya Syamsiar, Syamsiar Tanjung, Aristu Fahri Yogi Exprada Yusuf, Al