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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknoin Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmiah Informatika Komputer Jurnal Ilmiah Teknologi dan Rekayasa Prosiding KOMMIT TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnas Nasional Teknologi dan Sistem Informasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) J-SAKTI (Jurnal Sains Komputer dan Informatika) Journal of Information Systems and Informatics International Journal of Engineering, Science and Information Technology J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal of Engineering Continuity
Emy Haryatmi
Universitas Gunadarma
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 Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Herbal Plant Leaves Classification Using Convolutional Neural Network Models: A Literature Review Fauzi, Alfharizky; Haryatmi, Emy; Riyadi, Tri Agus; Murniyati, Murniyati
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.723

Abstract

Plants are essential to human beings because plants are considered most as foods. Plants can be used for food ingredients, medical purposes, and industrial applications. People inspect plants using traditional methods, such as using the naked eye, which can be time-consuming and expensive. Therefore, the effectiveness and high quality of automated crop identification classification systems are needed for adequate crop protection. This study aims to identify and classify nine plant species using different datasets, focusing on transfer learning from models trained on plant leaf datasets. Most research has shown that increasing the dataset size would significantly improve classification accuracy. The accuracy of the first test using the modified N1 classification model was 99.45%. In the second experiment, the accuracy of the N2 model was 99.65%. The accuracy of the N3 model, despite being slightly less accurate than AlexNet, was 99.55%, and it performed better, while the accuracy of AlexNet was 99.73%. Compared to the AlexNet model, the proposed model performed better and required less training time. The N1 model reduced the training time by 34.58%, the N2 model by 18.25%, and the N3 model by 20.23%. The N1 and N3 resulted in the same size, namely 14.8MB, and the compactness was 92.67%. The size of the N2 model was 29.7MB, and the compactness was 85.29% compactness. The proposed models provide more accuracy and efficiency in classifying plant leaves and can be used as a standalone mobile application that benefits farmers.
Implementasi Metode Moving Average Sebagai Prediksi Penjualan Perlengkapan Pertanian Pada CV. Aneka Tani Hanum, Fatmi Aulia; Haryatmi, Emy
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.380

Abstract

CV. Aneka Tani is a shop that sells various agricultural equipment. The problems in CV. Aneka Tani are the process of recording transactions that are still done manually with a sales book and there is no sales prediction system. It causes waste of paper, human error in transactions, and bad stock management. The purpose of this research is to predict sales of agricultural equipment, applying the Moving Average algorithm to CV. Aneka Tani’s data to generate sales prediction models, and analyze predictive models. The research method used is the CRISP-DM (Cross Industry Standard Process for Data Mining) which consists of business understanding, data understanding, data preparation, modeling, evaluation, and implementation. The process of collecting data is done by conducting interviews with business owners. There were 6 products used in Moving Average method. The stable product is Dafat with MAD value is 0,9 and MSE value is 1,2. The non stabel product is Phonska with MAD value is 13,6 and MSE value is 245,7.
Implementasi Metode Moving Average Sebagai Prediksi Penjualan Perlengkapan Pertanian Pada CV. Aneka Tani Hanum, Fatmi Aulia; Haryatmi, Emy
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.380

Abstract

CV. Aneka Tani is a shop that sells various agricultural equipment. The problems in CV. Aneka Tani are the process of recording transactions that are still done manually with a sales book and there is no sales prediction system. It causes waste of paper, human error in transactions, and bad stock management. The purpose of this research is to predict sales of agricultural equipment, applying the Moving Average algorithm to CV. Aneka Tani’s data to generate sales prediction models, and analyze predictive models. The research method used is the CRISP-DM (Cross Industry Standard Process for Data Mining) which consists of business understanding, data understanding, data preparation, modeling, evaluation, and implementation. The process of collecting data is done by conducting interviews with business owners. There were 6 products used in Moving Average method. The stable product is Dafat with MAD value is 0,9 and MSE value is 1,2. The non stabel product is Phonska with MAD value is 13,6 and MSE value is 245,7.
Design and Implementation of FTTB Network Transmission in High-Rise Buildings Using GPON Yuhani, Ahmad; Haryatmi, Emy; Haryadi, Deni; Arafat, Yunus Bakhtiar
International Journal of Engineering Continuity Vol. 4 No. 1 (2025): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v4i1.375

Abstract

The advancement of digital communication technology has significantly increased the demand for reliable network infrastructure, particularly in high-rise buildings such as hotels and resorts. This study aims to design and evaluate a Fiber To The Building (FTTB) network system based on Gigabit Passive Optical Network (GPON) technology at The Anvaya Beach Resort Bali. The system is designed to distribute integrated communication services including data voice, and video, through a zoning approach based on the functional layout of the building. The Waterfall method is employed in the system development, encompassing the stages of requirement analysis, topology design, field implementation, and optical performance testing. The findings indicate that most zones have optical attenuation values within the standard range (15–28 dB), and the received signal power remains within the acceptable threshold (-28 dBm). However, several areas exhibit suboptimal signal performance, particularly those with long distribution paths and a high number of optical splitters. Zone C1.1 demonstrates the best performance, with stable attenuation levels and signal strength within standards, without requiring additional active devices. The study concludes that a GPON-based FTTB system can efficiently and flexibly meet the data communication needs of high-rise buildings and other complex building environments with similar systems.
Implementation of Intrusion Detection System Using Snort and Log Visualization Using ELK Stack Robbani, Fatih Dien; Haryatmi, Emy; Riyadi, Tri Agus; Supono, Riza Adrianti; Bima Kurniawan, Ary; Rosdiana, Rosdiana
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.901

Abstract

Cyber threats like malware, ransomware, and DDoS attacks demand fast and integrated detection systems. Traditional network monitoring tools often struggle to identify complex real-time attack patterns. This study evaluates the integration of Snort, an Intrusion Detection System (IDS), with the ELK Stack (Elasticsearch, Logstash, Kibana) to detect and visualize cyberattacks effectively. The system was tested against three attack scenarios: a Windows ping flood, port scanning using Zenmap, and SSH brute force attacks via Nmap Scripting Engine (NSE). Wireshark was employed as a supporting tool to monitor raw network traffic. The results indicate that Snort detected all simulated attacks in real time, and the ELK Stack efficiently processed and visualized the alert data. However, limitations in Kibana's dashboard refresh rate slightly hindered real-time monitoring capabilities. Overall, the integration of Snort and the ELK Stack proves effective for network threat detection and analysis, with room for future improvements in visualization performance and automated response mechanisms.
Analisa Prediksi Kelayakan Pemberian Kredit Pinjaman dengan Metode Random Forest Prasojo, Budi; Haryatmi, Emy
Jurnal Nasional Teknologi dan Sistem Informasi Vol 7 No 2 (2021): Agustus 2021
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v7i2.2021.79-89

Abstract

Perkembangan di Indonesia saat ini tidak terlepas dari pernanan lembaga keuangan dengan salah satunya adalah perbankan. Bank memiliki peran dalam meningkatkan pertumbuhan dan perkembangan suatu Negara [1]. Perbankan memiliki fungsi sebagai lembaga yang memiliki peran sentral dalam meningkatkan pertumbuhan ekonomi suatu Negara. Dalam melakukan analisa pemberian kredit perbankan harus memerhatikan Prinsip-prinsip pemberian kredit[3]. besar kecilnya tingkat kredit yang disalurkan oleh bank kepada pihak lain ataupun masyarakat dipengaruhi oleh beberapa faktor [4]. Data dalam jumlah besar pada perbankan khususya perkreditan tersebut dapat diolah menggunakan beberapa metode tertentu akan memberikan informasi baru yang dapat mendukung dan membantu perbankan mengambil keputusan atau kebjakan, salah satu kebijakannya adalah dapat memprediksi kelayakan kredit pinjaman secara dini untuk mengetahui nasabah yang layak atau tidak layak, atau menggunakan salah satu teknik melakukan prediksi yang dapat digunakan adalah dengan teknik penggalian data atau data mining menggunakan algoritma random forest. Penelitian ini bertujuan untuk mengetahui penerapan metode klasifikasi dengan algoritma random forest serta menganalisis hasil terbaik dari algoritma random forest pada setiap kreditur. Variable yang dianalisis adalah V1 sampai dengan V20 dilakukan menggunakan perangkat lunak R. Tahapan metode penelitian menggunakan CRIPS-DM. untuk tahap pelatihan menggunakan 70% data dan Pengujian menggunakan 30% data secara acak dari 1000 data. Hasil performa dari algoritma random forest tersebut yaitu memiliki tingkat akurasi sebesar 0,77 atau 77% sehingga termasuk pada kategori klasifikasi fair model.
Co-Authors A. Benny Mutiara Abdul Rachman Rasyid Andhika Alif Arsadi Annisya Arini Islahul Nimah Arum TiaraSari Ary Bima Kurniawan Ayunda, Nur Azizah Bagaskoro Bagaskoro Bima Kurniawan, Ary Budi Prasojo Budi Prasojo, Budi Busono Soerowirdjo Busono Soerowirdjo Busono Soerowirdjo Dzulfikar, Laksamana Akbar E. Susy Suhendra Fathimah Nur Afifah Fauzi, Alfharizky Febrin Ludia Ramadini Hanum, Fatmi Aulia Haryadi, Deni Ilham Wijaya Murniyati, Murniyati Musa, Purnawarman Randy Rahmanto Rio Setiawan Riyadi, Tri Agus Riza Adrianti Supono, Riza Adrianti Robbani, Fatih Dien Rosdiana Rosdiana Sheila Pramita Hervianti Teddy Oswari Teddy Oswari Tubagus Maulana Kusuma Yuhani, Ahmad Yunus Bakhtiar Arafat