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All Journal Elkom: Jurnal Elektronika dan Komputer JURNAL PENGABDIAN KEPADA MASYARAKAT Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ilmiah Universitas Batanghari Jambi Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Jurnal Mantik G-Tech : Jurnal Teknologi Terapan Journal of Applied Science, Engineering, Technology, and Education Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknologi Informasi dan Komunikasi IJISTECH Infotech: Jurnal Informatika & Teknologi KLIK: Kajian Ilmiah Informatika dan Komputer Al-Khidmah Jurnal Pengabdian Masyarakat Journal of Information Systems and Technology Research Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Edu Society: Jurnal Pendidikan, Ilmu Sosial dan Pengabdian Kepada Masyarakat Journal of Computers and Digital Business ABDINE Jurnal Pengabdian Masyarakat Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer International Journal of Science and Environment Journal of Artificial Intelligence and Digital Business Jurnal Mahasiswa Ilmu Komputer Journal of Software Engineering and Information System (SEIS) Jurnal Pengabdian Masyarakat Cosmic Jurnal Teknik
Suhardi, Suhardi
Universitas Islam Negeri Sumatera Utara
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Analisis Perbandingan Efisiensi Enkripsi Dan Dekripsi Algoritma Sandi Caesar Dan Sandi Vigenere Untuk Keamanan Pesan Siregar, Rahmat Abdillah Nur; Suhardi, Suhardi
Cosmic Jurnal Teknik Vol 2 No 3 (2025): Agustus
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosmic.v2i3.1294

Abstract

Tingginya kebutuhan akan perlindungan data pada sistem komunikasi digital menimbulkan permasalahan terkait efektivitas algoritma kriptografi klasik dalam menghadapi ancaman modern, sehingga diperlukan evaluasi empiris terhadap algoritma yang umum digunakan. Penelitian ini bertujuan untuk membandingkan efisiensi dan keamanan dua algoritma kriptografi klasik, yaitu Sandi Caesar dan Sandi Vigenere, guna menentukan tingkat kebermanfaatannya dalam lingkungan komputasi modern serta aplikasi dengan sumber daya terbatas. Metode yang digunakan adalah pendekatan kuantitatif dengan desain eksperimental, di mana kedua algoritma diimplementasikan menggunakan Python dan diuji menggunakan berbagai ukuran teks masukan (100–10.000 byte), kemudian dianalisis berdasarkan waktu eksekusi, penggunaan memori, serta ketahanan terhadap serangan kriptoanalisis. Hasil penelitian menunjukkan bahwa pada ukuran teks 10.000 byte, Sandi Caesar mencatat rata-rata waktu eksekusi sebesar 11,99 ms (enkripsi) dan 11,82 ms (dekripsi), sedangkan Sandi Vigenere mencapai 40,64 ms (enkripsi) dan 45,53 ms (dekripsi). Penggunaan memori pada ukuran teks yang sama juga lebih rendah pada Sandi Caesar (9,86 KB) dibandingkan dengan Sandi Vigenere (9,99 KB). Dari sisi keamanan, simulasi brute force menunjukkan bahwa Sandi Caesar menghasilkan 26 kemungkinan hasil dekripsi (rentan), sedangkan analisis frekuensi Vigenere memberikan distribusi huruf yang lebih acak meskipun metode Kasiski tidak berhasil mengidentifikasi panjang kunci yang benar. Temuan ini menegaskan adanya tradeoff antara efisiensi komputasi dan tingkat keamanan, sehingga pemilihan algoritma harus disesuaikan dengan kebutuhan aplikasi.
Application of the Certainty Factor Method for Mobile-Based Identification of Freshwater Fish Diseases Santoso, Heri; Suhardi, Suhardi; Ridho Pardomuan, Mohammad
Journal of Applied Science, Engineering, Technology, and Education Vol. 5 No. 2 (2023)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci2254

Abstract

Freshwater fish its the food sources with profitable sales, consistent care can achieve the maintenance process until successful. Freshwater fish that have a high selling value include Gurami and Catfish. Gurami fish sales per seedling Rp. 3,000 and Lele fish sales start from Rp. 1000 to Rp. 0.500. Fish care needs to be considered to maintain its quality. Various problems are also experienced by farmers. The slow identification process makes fish affected by the disease faster and loses. Several factors inhibit the fish is of illegal drugs, overfeed, and environmental unhygiene conditions. The role of experts that is not sufficiently available makes limited information about controlling fish diseases so that it takes time and costs little. Utilizing technological progress, expert systems can help to solve problems that previously could only be solved by an expert. The Forward Chaining Method is a method on an expert system that is able to do a reasoning with advanced forward techniques. The Certainty Factor method is a method that can give a degree of confidence in a disease. An expert system built to identify freshwater fish diseases was built into the deep android operating system by the Waterfall development method. Data taken includes as many as 10 symptom data and 29 disease data implemented into the system. With this expert system in place, it aims to provide benefits to facilitate access in adding information about fish diseases so that countermeasures become faster
IMPLEMENTASI ALGORITMA HILL CIPHER DAN DISCRETE COSINE TRANSFORM DALAM KEAMANAN PESAN E-MAIL Wulan, Sri; Hasugian, Abdul Halim; Suhardi, Suhardi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3144

Abstract

Abstract: Regarding the security of email messages is very important in the digital era. So much data is sent via email every day. To improve the security of email messages, effective solutions can be applied to the Hill Cipher and Discrete Cosine Transform (DCT) algorithms. Hill Cipher is a classic encryption method that uses matrices to transform text. The combination of matrix operations can be decrypted without knowing the correct encryption key. Discrete cyclosine transform is a transformation method used in compressive images. In this study, we propose a combination of Hill cipher and DCT to protect email messages. Email messages are encrypted using the Hill Cipher algorithm, and the result is converted to the frequency domain using DCT. The step of improving upload security combines two mathematically different encryption methods. In addition, changing the frequency domain of the message reduces the success of attacks on the ciphertext. The researchers evaluated the performance of this combination of algorithms in terms of email message security, efficiency, encryption, decryption, and its impact on communication overhead. The Hill Cipher algorithm on messages in the form of voucher codes, speed and efficiency in cryptographic categorization are relatively fast, and for the insertion process with DCT, the MSE value is 130169.10 and the PSNR is -3.014 on an 8x8 image and 130169.10. 15920 x MPS. The combination of Hill Cipher and DCT is expected to improve the security of email messages without having a significant impact on system performance. Keyword: E-mail; Hill Cipher; Algoritma; DCT; Data Security Abstrak: Mengenai keamanan pesan email sangat penting di era digitalisasi. Begitu banyak data yang dikirim melalui email setiap hari. Untuk meningkatkan keamanan pesan email, solusi efektif dapat diterapkan pada algoritma Hill Cipher dan Discrete Cosine Transform (DCT). Hill Cipher adalah metode enkripsi klasik yang menggunakan matriks untuk mengubah teks. Kombinasi operasi matriks dapat didekripsi tanpa mengetahui kunci enkripsi yang benar. Transformasi siklosin diskrit adalah metode transformasi yang digunakan dalam gambar kompresif. Dalam studi ini, kami mengusulkan kombinasi kata sandi Hill dan DCT untuk melindungi pesan email. Pesan email dienkripsi menggunakan algoritma Hill Cipher, dan hasilnya diubah ke domain frekuensi menggunakan DCT. Langkah meningkatkan keamanan pengunggahan menggabungkan dua metode enkripsi yang secara matematis berbeda. Selain itu, mengubah domain frekuensi pesan mengurangi keberhasilan serangan terhadap ciphertext. Para peneliti mengevaluasi kinerja kombinasi algoritma ini dalam hal keamanan pesan email, efisiensi, enkripsi, dekripsi, dan dampaknya terhadap overhead komunikasi. Algoritma Hill Cipher pada pesan berupa kode voucher kecepatan dan efisiensi dalam kategorisasi kriptografi tergolong cepat, dan untuk proses penyisipan dengan DCT diperoleh nilai MSE sebesar 130169.10 dan PSNR sebesar -3.014 pada citra berukuran 8x8 dan 130169.10. 15920 x MPS. Kombinasi Hill Cipher dan DCT diharapkan dapat meningkatkan keamanan pesan email tanpa berdampak signifikan pada kinerja sistem. Kata kunci: E-mail; Hill Cipher; Algoritma; DCT; Keamanan Data 
PENERAPAN WATERFALL SDLC PADA PERANCANGAN SISTEM PENGELOLAAN IZIN KELUAR KANTOR DI KANREG VI BKN MEDAN Aznawi, Nasrul Mahruf; Fachroza, Siti Dian; Ermaliza; Ritonga, Dedek Juliani; Suhardi
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 6 No. 1 (2026)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v6i1.10788

Abstract

The handling of office leavepermits at the Regional Office VI of the State Civil Service Agency (BKN) in Medan is still done manually, causing various problems such as delays in approval, lack of transparency, potential data manipulation, and the unavailability of well-documented employee permit histories. This condition has a direct impact on work effectiveness and the accuracy of personnel administration. This study aims to design and develop a web-based office leave management system to improve the efficiency and transparency of the administrative process. The system development method used is the Software Development Life Cycle (SDLC) with the Waterfall model, which includes the stages of requirements analysis, system design, implementation, testing, and maintenance. Data collection was carried out through observation and interviews to ensure that the system meets user needs. The results of the study show that the developed system is capable of managing the process of submitting, approving, and recording office leave digitally and in an integrated manner. System testing using the Black Box Testing method showed that all main functions ran according to system requirements. This system is capable of increasing the speed of the service process, reducing administrative errors, and providing a well-documented history of permits.
KLASIFIKASI JENIS TANAMAN ANGGREK BERDASARKAN DAUN MENGGUNAKAN METODE PRINCIPAL COMPONENT ANALYSIS DAN K-NEAREST NEIGHBOR Nazhifa Ahmad Fauzan; Muhammad Siddik Hasibuan; Suhardi
STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Vol. 5 No. 1 (2026): Februari
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/storage.v5i1.7086

Abstract

Anggrek merupakan tanaman hias dengan keragaman spesies yang tinggi sehingga diperlukan metode identifikasi yang akurat dan konsisten. Penelitian ini bertujuan mengembangkan sistem klasifikasi jenis anggrek berbasis citra daun menggunakan metode Principal Component Analysis (PCA) dan K-Nearest Neighbor (K-NN). PCA digunakan untuk mengekstraksi fitur utama sekaligus mereduksi dimensi data guna meningkatkan efisiensi komputasi, sedangkan K-NN berperan dalam proses klasifikasi berdasarkan tingkat kemiripan fitur menggunakan Euclidean Distance. Dataset terdiri dari 56 citra daun anggrek yang terbagi menjadi 35 citra latih dan 21 citra uji dari tujuh kelas jenis anggrek. Tahapan penelitian meliputi akuisisi citra, ekstraksi ciri, reduksi dimensi menggunakan PCA, serta klasifikasi menggunakan K-NN. Evaluasi menggunakan confusion matrix menunjukkan akurasi sebesar 85,71%, dengan precision 90,71%, recall 85,71%, dan F1-score 84,39%. Hasil tersebut menunjukkan bahwa kombinasi PCA dan K-NN efektif dalam mengklasifikasikan daun anggrek dan berpotensi dikembangkan sebagai sistem identifikasi otomatis untuk mendukung penelitian botani, konservasi tanaman, dan industri tanaman hias.
Implementasi Data Mining Dalam Memprediksi Penjualan Parfum Terlaris Menggunakan Metode K-Nearest Neighbor Mhd Angga Sabda; Suhardi Suhardi
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7194

Abstract

Ahlinyaparfum is a perfume shop that provides various kinds of fragrance oils. To run his business, Ahlinyaparfum must send perfume variants to his shop from the place where the perfume is made, which requires shipping costs. Often, the perfume variants offered by Ahlinyaparfum do not match the wishes of customers, which has a negative impact on the number of store sales. The best-selling prediction process is needed based on previous sales data to help stores know which perfumes are most popular with customers and the level of best-selling in the future. By applying data mining using the K-Nearest Neighbor method, this research aims to overcome this problem. This method was tested using perfume sales data from January to June 2023 with a total of 215 data. To test and ensure its performance with the help of the Jupyter Notebook application with Python. The process of predicting perfume sales for the next month uses the parameter k = 3 with Euclidean distance calculations. The best-selling result predicted for the 7th month is Aigner Blue Emotion with total sales of 153 ml. Based on the evaluation algorithm, the overall average value of MSE is 0.52, which shows that the results are very good in determining next month's perfume sales. This is due to the fact that the calculation results are closer to the actual value the lower the MSE value.
Peramalan Stok Produk Meubel Menggunakan Metode Single Moving Average dan Exponential Smoothing Ritonga, Tomi; Nasution, Yusuf Ramadhan; Suhardi, Suhardi
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 5 No. 1 (2026): Februari - April
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v5i1.7126

Abstract

Permasalahan perekonomian global yang terjadi dalam beberapa tahun terakhir memberikan dampak signifikan terhadap berbagai sektor industri, termasuk industri meubel. Ketidakstabilan kondisi pasar menyebabkan fluktuasi permintaan yang berdampak langsung pada perencanaan produksi dan pengelolaan persediaan barang. Kesalahan dalam memperkirakan jumlah permintaan sering menimbulkan penumpukan stok atau kekurangan barang, sehingga perusahaan berpotensi mengalami kerugian akibat biaya penyimpanan yang tinggi maupun kehilangan peluang penjualan. Kondisi ini juga terjadi pada PT. Wira Utama yang beralamat di Jl. Prof. H. M. Yamin No. 23, Gg. Buntu, Kota Medan yang bergerak di bidang penjualan meubel di Kota Medan, dimana proses peramalan sebelumnya masih dilakukan secara konvensional berdasarkan perkiraan tanpa perhitungan matematis yang terukur. Penelitian ini bertujuan untuk meramalkan kebutuhan stok dan produksi pada periode berikutnya dengan menerapkan metode Single Moving Average dan Exponential Smoothing berbasis data historis penjualan tahun 2019–2022. Kedua metode dibandingkan menggunakan parameter pengukuran kesalahan, yaitu Mean Absolute Deviation (MAD), Mean Squared Error (MSE), dan Mean Absolute Percentage Error (MAPE) untuk menentukan tingkat akurasi peramalan. Hasil penelitian menunjukkan bahwa penerapan metode peramalan berbasis time series mampu menghasilkan estimasi yang lebih objektif dan sistematis dibandingkan metode manual. Nilai rata-rata MAPE sebesar 14% menunjukkan tingkat kesalahan yang relatif rendah, sehingga model yang diterapkan dinilai layak digunakan sebagai dasar pengambilan keputusan dalam perencanaan produksi, pengendalian persediaan, dan optimalisasi manajemen stok perusahaan.
Klasifikasi Kualitas Tandan Buah Segar Kelapa Sawit Menggunakan Support Vector Machine dengan Kernel Radial Basis Function Latifa Khoirani; Suhardi
Journal of Computers and Digital Business Vol. 5 No. 2 (2026)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56427/jcbd.v5i2.993

Abstract

Kualitas Tandan Buah Segar (TBS) kelapa sawit menentukan mutu minyak sawit yang dihasilkan. Klasifikasi kualitas TBS di lapangan masih dilakukan secara manual berdasarkan pengamatan visual yang subjektif dan tidak konsisten. Penelitian ini menerapkan metode Support Vector Machine (SVM) dengan kernel Radial Basis Function (RBF) untuk mengklasifikasikan kualitas TBS secara otomatis berbasis data numerik parameter laboratorium sebagai alternatif yang lebih praktis dan efisien. Data yang digunakan sebanyak 1.500 dataset hasil pemeriksaan laboratorium periode Februari 2025 dari PT XYZ, dengan parameter berat tandan, kandungan minyak, kadar air, dan brondol lepas. Preprocessing meliputi data cleaning, normalisasi Min-Max Scaling, dan encoding label, dengan pembagian data 80:20 menghasilkan 1.200 data training dan 300 data testing. Model dibangun dengan parameter C = 1,0 dan gamma (γ) = 1,0542 yang dihitung secara dinamis dari distribusi data training, menggunakan strategi klasifikasi multikelas One-vs-One (OvO).  Evaluasi model menggunakan confusion matrix dengan metrik akurasi, precision, recall, dan F1-score. Hasil penelitian menunjukkan model SVM mampu mengklasifikasikan kualitas TBS ke dalam tiga kategori mentah, matang, dan lewat matang dengan akurasi 95%. Penelitian ini berkontribusi dalam meningkatkan objektivitas, konsistensi, dan efisiensi proses klasifikasi kualitas TBS berbasis machine learning.
Pelatihan Koding Kecerdasan Artifisial untuk Peningkatan Kompetensi Guru Yusuf Ramadhan; Reza Ade Putra; Ilka Zufria; M. Fakhriza; Puji Sari Ramadhan; Rita Novita Sari; Lailan Sofinah Harahap; Suhardi Suhardi; Oktopanda Oktopanda
Al-Khidmah Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2026): MEI-AGUSTUS
Publisher : Institute for Research and Community Service (LPPM) of the Islamic University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56013/jak.v6i2.5496

Abstract

The development of artificial intelligence (AI) in education requires teachers to possess digital literacy and adapt to learning technology. However, there is still a competency gap among teachers in understanding basic AI and coding concepts, particularly in educational institutions that have not yet optimally utilized digital technology. Therefore, this community service activity was carried out with the aim of improving teachers' understanding and basic skills in artificial intelligence coding as a support for innovative learning. The community service method used was participatory and applied, implemented through preparation, implementation, and evaluation stages. The training activity involved 50 teachers and was conducted in the form of interactive lectures, discussions, and simple practical exercises related to coding and the use of AI in learning. Throughout the activity, a process evaluation was conducted through observation of participant participation, active participation in discussions, ability to participate in coding exercises, and completion of assigned tasks. This evaluation aimed to ensure that participants understood the material and actively participated in the training. Indicators of success at this stage were demonstrated by a minimum of 85% of participants completing the activity to completion and a minimum of 80% of participants completing the basic coding exercises and using the AI ​​tools provided during the training. After all the material was delivered, a final evaluation was conducted through a post-test, simple AI-based project assignments, and participant satisfaction questionnaires. The final evaluation was used to measure teacher competency improvement after participating in the training. The success of the program was demonstrated by an average post-test score increase of at least 30% compared to the pre-test results. In addition, at least 75% of participants were able to create simple AI-based projects or code according to the training material, and at least 80% of participants were able to integrate the use of AI technology into their learning designs. These findings confirm that artificial intelligence coding training is a strategic step in improving teacher competency and supporting technology-based learning transformation in educational environments.
Co-Authors Abdul Halim Hasugian Aditama, Yuda Ahmad Fariz Fuady Aidil Halim Lubis Aidil Halim Lubis Aisyiyah, Siti R Nur Ali Darta Alviona Marsya Amelia Anwar, Mufti Husain Armansyah Armansyah Armansyah Aznawi, Nasrul Mahruf Daulay, Darisma Diah Ayu Anggraini Dwi Anggreny, Anggy Dwiky Oldi Amsyah Ega Yolanda Endah Avilia Chandra Ermaliza Erwin Nasution Fachroza, Siti Dian Filza Salsabila, Putri Fitri, Wan Ilia Fitriani Fitriani Gina Fadhila Harahap, Hotma Rizki Harahap, Shopiah Heri Santoso Ibnu Rusydi Ichsan Rafisyah Ilham Hafiz Satrio Ilka Zufria Ilka Zufria Iskandar, Nabila La Saufa Yardha Lailan Sofinah Harahap Latifa Khoirani M. Fakhriza Maulana, Rexa Mhd Angga Sabda Mhd Furqan Mhd Ikhsan Rifki Mhd. Furqan Muhammad Ikhsan Muhammad Luthfi Muhammad Siddik Hasibuan Namirah Yasmine Raudah Nazhifa Ahmad Fauzan Nela Meilani Oktopanda Oktopanda Pramudya, Farhan Amar Puji Sari Ramadhan Rakhmat Kurniawan R Ramadhan, M Irsyad Rambe, Nia Sabrina Reza Ade Putra Ridho Pardomuan, Mohammad Rita Novita Sari Ritonga, Dedek Juliani Ritonga, Tomi Rizki Hasibuan, Indra Shabahal Khair, Herla Siagian, Qori Azmi Ayasy Silva Ukhti Filla Siregar, Muhammad Faisal Siregar, Rahmat Abdillah Nur Siti Afifah Siregar Sri Wulan, Sri Sriani Sriani Surbakti, Miftah Hadi Yusuf Ramadhan Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan