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Syaiful Zuhri Harahap
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Jl. S.M Raja No. 126 A Km 3.5 Aek Tapa, Rantauprapat, Kabupaten Labuhanbatu, Sumatera Utara, Indonesia
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Informatika
Published by Universitas Labuhanbatu
ISSN : 23032863     EISSN : 26151855     DOI : 10.36987
Core Subject : Science, Education, Engineering,
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Library & Information Science Other
INFORMATIKA : Jurnal Ilmiah Fakultas Sains & Teknologi Universitas Labuhanbatu diterbitkan oleh Universitas Labuhanbatu melalui Lembaga Penelitian dan Pengabdian Masyarakat, dimaksudkan sebagai media pertukaran informasi dan karya ilmiah antara staf pengajar, alumni, mahasiswa dan masyarakat pada umumnya yang terbit tiga kali dalam setahun (Januari-Mei-September), yang mulai awal terbit sejak tahun 2013.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 277 Documents
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Pengembangan Sistem Absensi Berbasis Real-Time Face Recognation Di Lingkungan Sekolah Menggunakan You Only Look Once (Yolo) Rahmat Fardi Asli; Ahmad Selao; Untung Suwardoyo
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.7968

Abstract

The increasing demand for efficient and reliable student attendance systems highlights the limitations of conventional manual methods, which are often time-consuming, prone to fraud, and lack accuracy. This study develops a real-time attendance system based on facial recognition using the YOLOv8 deep learning model integrated with TensorFlow. The system is designed to automatically detect and recognize students’ faces through a webcam and record attendance data in real time. The research method involved three main stages: face registration, model training, and attendance recording. A dataset of 4,200 face images from 14 students was collected to train the model. The recognition process used cosine similarity with a threshold of 0.7 to balance accuracy and avoid false recognition. The results showed that the system could effectively recognize student faces under varying lighting and expression conditions with high accuracy, while also recording attendance automatically and reliably. The system proved to be efficient in reducing time consumption, minimizing fraud, and ensuring more accurate attendance records. This study demonstrates that YOLOv8-based face recognition can provide an effective solution for modernizing school attendance management.
Pengembangan Evidence Monitoring Tingkat PH dan Kekeruhan Air Untuk Menentukan Kelayakan Konsumsi Air Andi Fatri; Muhammad Basri; Untung Suwardoyo
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.7918

Abstract

Development of Evidence Monitoring of PH Levels And Water Turbidity to Determine the Feasibility of Water Consumption. (Supervised by Muhammad Basri and Untung Suwardoyo). The most common method for detecting water quality parameters is by manually collecting samples and sending them to a laboratory for detection and analysis. However, with the advancement of time and technology, this method has become somewhat less relevant due to its manual nature. For that reason, a study was conducted titled "Development of Evidence-Based Monitoring for pH and Turbidity Levels to Determine Drinking Water Feasibility." This study aims to develop a monitoring process that also simplifies the assessment of water feasibility through an automated system, making the process more efficient and relevant. This monitoring system uses two indicators: turbidity and pH. The system is developed using a pH sensor SEN0161-V2 and a turbidity sensor DF Robot-SEN0189, with an ESP32 microcontroller.(Permenkes RI, 2010) It is designed to monitor changes in values in real time, which are then displayed through an Android application. The device is also equipped with a filtration system. Test results showed a change in turbidity levels from an initial value of 29.8 NTU (not suitable for consumption) to 4.8 NTU (suitable for consumption), within a water filtration cycle duration of 24 minutes and 56 seconds.
Perancangan Sistem Informasi Promosi dan Penjualan Berbasis Web Pada Unit Produksi SMKN 1 Ampek Angkek Menggunakan Framework CodeIgniter Nurul Abdillah; Oki Dahwanu; Hamzah Alghifari; Niko Akbar
Jurnal Informatika Vol 12, No 3 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.8165

Abstract

The Production Unit (PU) plays an important role in fostering students’ entrepreneurial skills through the creation of economically valuable products and services. However, product promotion at the Production Unit of SMK N 1 Ampek Angkek has so far only been carried out through exhibitions held once every semester. The school’s less strategic location results in many products remaining unsold, and those stored for too long often become damaged. To address this issue, a web-based promotional and sales information system was designed using the CodeIgniter framework. The system was developed using UML (Unified Modeling Language) modeling with an object-oriented approach. The programming languages used were PHP with the CodeIgniter framework and JavaScript, while MySQL served as the database and Sublime Text 3 as the code editor. The result of this design is a web-based information system that can present craft product information more widely and efficiently. This system helps the Production Unit promote its products without time and location limitations and provides convenience for consumers to view and purchase products online.
ANALISIS PROYEK DATA GAJI PEGAWAI BIAYA OPERASIONAL DI SWAN CAFFEE & RESTO RANTAUPRAPAT MENGGUNAKAN METODE KNN Hadron Sofyan; Masrizal Masrizal; Sudi Suryadi; Budianto Bangun
Jurnal Informatika Vol 14, No 2 (2026): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v14i2.9069

Abstract

Pemanfaatan data operasional sebagai dasar pengambilan keputusan penting dalam pengelolaan usaha kuliner. Data gaji pegawai dan biaya operasional yang tercatat secara rutin memiliki potensi untuk dianalisis guna mengidentifikasi pola pengeluaran dan mendukung efisiensi operasional. Namun, data tersebut umumnya masih digunakan sebatas laporan administratif. Penelitian ini bertujuan untuk menganalisis dan mengklasifikasikan data gaji pegawai serta biaya operasional pada Swan Caffee & Resto Rantauprapat menggunakan pendekatan Knowledge Discovery in Databases (KDD) dengan algoritma K-Nearest Neighbor (KNN). Penelitian menggunakan pendekatan kuantitatif dengan desain studi kasus. Data dianalisis melalui tahapan pembersihan, transformasi, dan klasifikasi menggunakan KNN. Evaluasi model dilakukan dengan perangkat lunak Orange menggunakan skema random sampling dengan data pelatihan 70%. Hasil penelitian menunjukkan nilai akurasi sebesar 53,3% dan AUC sebesar 0,407, yang mengindikasikan keterbatasan model akibat ketidakseimbangan kelas. Meskipun demikian, KNN dapat dimanfaatkan sebagai alat eksploratif dalam mendukung pengambilan keputusan berbasis data pada usaha kuliner.Kata kunci: Data Mining, KNN, KDD, Gaji Pegawai, Biaya Operasional, usaha kuliner.
INTEGRASI CODING DAN ARTIFICIAL INTELLIGENCE (AI) DALAM PEMBELAJARAN UNTUK MENINGKATKAN KOMPETENSI DIGITAL PESERTA DIDIK Ali Akbar Ritonga; Elysa Rohayani Hasibuan; Rohani Rohani
Jurnal Informatika Vol 14, No 2 (2026): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v14i2.9633

Abstract

Perkembangan teknologi digital telah mendorong transformasi dalam dunia pendidikan, termasuk melalui integrasi Coding dan Artificial Intelligence (AI) sebagai bagian dari proses pembelajaran. Penguasaan kedua kompetensi tersebut tidak hanya mendukung kemampuan teknis peserta didik, tetapi juga berkontribusi terhadap pengembangan berpikir komputasional, kreativitas, pemecahan masalah, serta kompetensi digital yang dibutuhkan pada abad ke-21. Artikel ini bertujuan untuk mengkaji peran integrasi Coding dan AI dalam pembelajaran serta kontribusinya terhadap peningkatan kompetensi digital peserta didik. Penelitian menggunakan metode studi kepustakaan (library research) dengan pendekatan deskriptif kualitatif melalui analisis berbagai sumber ilmiah, meliputi artikel jurnal, buku, laporan penelitian, dan dokumen kebijakan pendidikan yang relevan. Hasil kajian menunjukkan bahwa integrasi Coding dan AI mampu menciptakan pembelajaran yang lebih interaktif, adaptif, dan berpusat pada peserta didik. Selain meningkatkan literasi digital, implementasi Coding dan AI juga mendorong kemampuan berpikir kritis, kolaborasi, komunikasi, kreativitas, serta kesiapan menghadapi tantangan transformasi digital. Namun demikian, implementasinya masih menghadapi berbagai tantangan, seperti keterbatasan kompetensi pendidik, infrastruktur teknologi, dan kesiapan kurikulum. Oleh karena itu, diperlukan dukungan kebijakan, penguatan kapasitas guru, serta penyediaan sarana pembelajaran yang memadai agar integrasi Coding dan AI dapat diterapkan secara optimal dan berkelanjutan dalam meningkatkan kompetensi digital peserta didik.
Analisis Tingkat Risiko Virus Komputer Menggunakan Metode Simple Additive Weighting SAW Ade Kurnia Kurnia Ramzani
Jurnal Informatika Vol 14, No 2 (2026): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v14i2.9613

Abstract

The rapid advancement of information technology has led to increased computer and network usage across various activities; however, it has also heightened the risk of cyberattacks, particularly those involving computer viruses or malware. Since each type of malware possesses distinct characteristics and varying levels of danger, a method is required to objectively assess the risk level of each virus. This study aims to analyze computer virus risk levels using the Simple Additive Weighting (SAW) method. The alternatives evaluated in this study include Trojans, Worms, Spyware, Ransomware, and Adware. The criteria employed encompass the rate of spread, system damage, data theft capability, detection difficulty, and impact on system performance. The SAW method was applied through a process involving criteria weighting, decision matrix normalization, preference value calculation, and alternative ranking. The results indicate that Ransomware achieved the highest preference value (0.96), thereby ranking first as the virus with the highest risk level. This was followed by Trojans (0.81), Worms (0.74), Spyware (0.71), and Adware (0.48). These findings demonstrate that the SAW method facilitates a systematic and objective analysis of computer virus risk levels, serving as a basis for prioritizing responses to malware threats
SISTEM PENDUKUNG KEPUTUSAN PRIORITAS EKSPANSI RT/RW NET BERBASIS PROFITABILITAS DAN PEMILIHAN TEKNOLOGI ADAPTIF MENGGUNAKAN METODE BWM-CRITIC-MABAC Khaidir Khaidir; Jesika Simanjuntak; Maysarah Anggita Harahap; Salfa Azzahra Siregar
Jurnal Informatika Vol 14, No 2 (2026): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v14i2.9587

Abstract

Pemerataan akses internet di Indonesia masih terkendala di wilayah berkepadatan rendah yang kurang terlayani penyedia besar, sehingga usaha RT/RW Net berbasis komunitas berperan penting. Ketika usaha ini berkembang, pengelola menghadapi keputusan strategi dalam memilih wilayah ekspansi yang paling menguntungkan dengan sumber daya terbatas. Penelitian ini bertujuan membangun sistem pendukung keputusan untuk menentukan prioritas perluasan wilayah RT/RW Net berbasis profitabilitas, yang mengintegrasikan pemilihan teknologi penyaluran bandwidth secara adaptif. Model dirancang dalam dua tahap: tahap pertama penyaringan kelayakan dan pengaturan teknologi backhaul secara berjenjang berdasarkan biaya terendah, sedangkan tahap kedua memeringkat wilayah berdasarkan enam kriteria profitabilitas. Pembobotan kriteria menggunakan metode integrasi Best-Worst Method dan Criteria Importance Through Intercriteria Correlation, sedangkan pemeringkatan menggunakan Multi-Attributive Border Approximation Area Comparison. Penerapan pada lima wilayah kandidat menghasilkan urutan prioritas yang jelas dengan tingkat konsistensi penilaian yang sangat baik. Hasil menunjukkan wilayah dengan potensi pendapatan tinggi namun berbiaya backhaul rendah memenuhi prioritas utama, sedangkan wilayah berpenduduk terbanyak justru tidak menjadi prioritas terbaik akibat biaya investasi dan persaingan yang tinggi. Analisis sensitivitas membuktikan peringkat dua wilayah teratas stabil terhadap variasi pembobotan, sehingga rekomendasi yang dihasilkan andal

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