Articles
<![CDATA[Analisis Performa Rasio Kompresi Pada Metode Differensiasi ASCII Dan Lempel Ziv Welch (LZW) ]]>
<![CDATA[Tommy Tommy]]>;
<![CDATA[Rosyidah Siregar]]>;
<![CDATA[Amir Mahmud Husein]]>;
<![CDATA[Mawaddah Harahap]]>;
<![CDATA[Ferdy Riza]]>
<![CDATA[ JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 1 No. 2 (2018): Jutikomp Volume 1 Nomor 2 Oktober 2018 ]]>
Publisher : <![CDATA[Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia ]]>
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DOI: 10.34012/jutikomp.v1i2.225
<![CDATA[ASCII differentiation is a compression method that utilizes the difference value or the difference between the bytes contained in the input character. Technically, the ASCII differentiation method can be done using a coding dictionary or using windowing block instead of the coding dictionary. Previous research that has been carried out shows that the ASCII differentiation compression ratio is good enough but still needs to be analyzed on performance from the perspective of the compression ratio of the method compared to other methods that have been widely used today. In this study an analysis of the comparison of the ASCII Difference method with other compression methods such as LZW will be carried out. The selection of LZW itself is done by reason of the number of data compression applications that use the method so that it can be the right benchmark. Comparison of the compression ratio performed shows the results of ASCII differentiation have advantages compared to LZW, especially in small input characters. Whereas in large input characters, LZW can optimize the probability of pairs of characters that appear compared to ASCII differentiation which is glued to the difference values in each block of input characters so that in large size characters LZW has a greater compression ratio compared to ASCII differentiation.]]>
<![CDATA[Analisa Frekuensi Hasil Enkripsi Pada Algoritma Kriptografi Blowfish Terhadap Keamanan Informasi ]]>
<![CDATA[Ferdy Riza]]>;
<![CDATA[Nurmala Sridewi]]>;
<![CDATA[Amir Mahmud Husein]]>;
<![CDATA[Muhammad Khoiruddin Harahap]]>
<![CDATA[ JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 1 No. 1 (2018): Jutikomp Volume 1 Nomor 1 April 2018 ]]>
Publisher : <![CDATA[Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia ]]>
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DOI: 10.34012/jutikomp.v1i1.233
<![CDATA[The ease of sending data with the development of internet technology technology is now a concern, especially the problem of data confidentiality, integrity and information security. Cryptography is one of the techniques used to maintain data confidentiality and information security, the application of cryptographic techniques for information security and data integrity is highly dependent on the formation of keys. In this study proposed a frequency analysis approach to measure the level of information security of blowfish encryption results to determine the distribution form of each character used in the text and find out the exact frequency of each character used in the test text data. The encryption algorithm and description of blowfish method against plaintext are proven to be accurate, but the longer the key character used will greatly affect the level of information security that came from encryption process, this is based on the results of the frequency analysis conducted.]]>
<![CDATA[Sales Digital Cashier Application Development Using Website (Case Study : Gogo Bakery) ]]>
<![CDATA[Andrew Louis]]>;
<![CDATA[Ferdy Riza]]>;
<![CDATA[Allwine Allwine]]>
<![CDATA[ Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 3, No 1 (2022) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Sumatera Utara, Indonesia ]]>
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DOI: 10.30596/jcositte.v3i1.9411
<![CDATA[Cash register technology can simplify and optimize payment transaction management. The activity of buying and selling goods cannot be separated from sales transactions and the sales transaction process cannot be separated from the cashier. GOGO Bakery is a trading shop engaged in the sale of bread. At this store, the transaction process, data processing, and report generation have not been managed computerized, until now this store still has not provided satisfactory and ineffective service, because the payment process at the cashier is not optimal and also the provision of product and price information is not listed properly, which causes consumers to not know the prices and the latest products in the store before buying. In stores, there are usually a lot of item data, transaction data, and others that are impossible to memorize. for that,]]>
<![CDATA[Design of Student Values Information System At Stmik Methodist College Binjai ]]>
<![CDATA[Aprida Br Tarigan]]>;
<![CDATA[Reza Alamsyah]]>;
<![CDATA[Ferdy Riza]]>
<![CDATA[ Indonesian Journal of Education, Social Sciences and Research (IJESSR) Vol 2, No 3 (2021) ]]>
Publisher : <![CDATA[Indonesian Journal of Education, Social Sciences and Research (IJESSR) ]]>
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DOI: 10.30596/ijessr.v2i3.8553
<![CDATA[Information technology in this modern era has developed so fast and sophisticated. Every education sector is expected to be able to utilize information technology as a support for operational activities in producing information. STMIK Methodist Binjai is one of the institutions that uses computerization in its data processing, such as processing academic grades and making final grades in the form of Study Result Cards (KHS). The problems that occur today are related to the procedures carried out in the process of processing academic grades. Such as when filling out the KRS which still uses handwriting, and the printing of the KHS which is not updated because it is not well organized between lecturers and the study program.]]>
<![CDATA[Analisis dan Prediksi Data Penjualan Menggunakan Machine Learning dengan Pendekatan Ilmu Data ]]>
<![CDATA[Ferdy Riza]]>
<![CDATA[ Data Sciences Indonesia (DSI) Vol. 1 No. 2 (2021): Article Research Volume 1 Number 2, Desember 2021 ]]>
Publisher : <![CDATA[ITScience (Information Technology and Science) ]]>
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DOI: 10.47709/dsi.v1i2.1308
<![CDATA[Pendekatan Data Science (ilmu data) memberi peluang besar untuk menggunakan data history dan mengubahnya menjadi wawasan yang berguna untuk membangun model prediksi penjualan masa depan. akan tetapi, model prediksi membutuhkan analisis data tertentu untuk menghasilkan model yang kuat, termasuk jumlah pelanggan, jumlah pelanggan yang hilang, tingkat penjualan rata-rata serta kecenderungan musiman. Makalah ini menganalisis data penjualan menggunakan kerangka kerja ilmu data dengan desain sesuai prinsip CRIS-DM yang terdiri dari tahapan pemahaman bisnis, pemahaman data, persiapan data, pemodelan, evaluasi, dan penerapan. Pemodelan digunakan algoritma Machine Learning untuk memprediksi penjualan di masa depan yang hasil kinerjanya dievaluasi dengan RMSE, MEA dan R^2. Berdasarkan hasil pengujian algoritma XGBoost dan LightGBM menghasilkan nilai R^2 mencapai 60% dengan tingkat kesalahan deteksi terendah dibandingkan algoritma lainnya..]]>
<![CDATA[Perancangan Sistem Arsip Berbasis Online Pada BPP Medan Krio ]]>
<![CDATA[Farid Akbar Siregar]]>;
<![CDATA[Fatma Sari Hutagalung]]>;
<![CDATA[Ferdy Riza]]>
<![CDATA[ Jurnal ABDIMAS Budi Darma Vol 3, No 2 (2023): Februari 2023 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/pengabdian.v3i2.5413
<![CDATA[Saat ini sistem arsip pada BPP Medan Krio masih menggunakan cara manual, yaitu dengan harus mendatangi tim arsip langsung ke lokasi dan memberikan berkas yang akan diarsip kepada tim arsip, hal ini menjadi kurang efisien karena memakan waktu dalam pengumpulan arsip dan beresiko arsip hilang. Sumber Daya Manusia yang ada di BPP Medan Krio bukan berasal dari profesional bidang pengembangan sistem, sehingga penggunaan teknologi belum optimal dilakukan dikarenakan keterbatasan dari kemampuan dan wawasan staff. Maka dari itu kami memberikan solusi berupa pembuatan dan pelatihan sistem arsip online sehingga berkas-berkas pengarsipan dapat dikumpulkan dari jauh (online) tanpa harus mendatangi tim arsip ke lokasi. Rencana kegiatan yang nanti akan tim lakukan yaitu dimulai dengan sosialisasi mengenai sistem yang akan ditawarkan kepada pihak mitra dan pengumpulan data yang diperlukan, lalu kemudian tim membuat aplikasi yang diusulkan kepada mitra bersama dengan modul penggunaan aplikasi dan simulasi penggunaan aplikasi oleh tim. Setelah aplikasi dan modul sudah rampung kemudian tim akan melakukan pelatihan penggunaan aplikasi kepada BPP medan krio yang diakhiri dengan evaluasi pelatihan serta penyusunan laporan akhir.Dengan harapan pelatihan tersebut dapat membantu para staff untuk meningkatkan pelayanan sistem pengarsipan yang ada di BPP medan Krio dengan cara online.]]>
<![CDATA[Base-Delta Dynamic Block Length and Optimization on File Compression ]]>
<![CDATA[Tommy]]>;
<![CDATA[Ferdy Riza]]>;
<![CDATA[Rosyidah Siregar]]>;
<![CDATA[Manovri Yeni]]>;
<![CDATA[Andi Marwan Elhanafi]]>;
<![CDATA[Ruswan Nurmadi]]>
<![CDATA[ Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023 ]]>
Publisher : <![CDATA[Information Technology and Science (ITScience) ]]>
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DOI: 10.47709/cnahpc.v5i1.1993
<![CDATA[Delta compression uses the previous block of bytes to be used as a reference in the compression process for the next blocks. This approach is increasingly ineffective due to the duplication of byte sequences in modern files. Another delta compression model uses the numerical difference approach of the sequence of bytes contained in a file. Storing the difference value will require fewer representation bits than the original value. Base + Delta is a compression model that uses delta which is obtained from the numerical differences in blocks of a fixed size. Developed with the aim of compressing memory blocks, this model uses fixed-sized blocks and does not have a special mechanism when applied to file compression in general. This study proposes a compression model by developing the concept of Base+Delta encoding which aims to be applicable to all file types. Modification and development carried out by adopting a dynamic block size using a sliding window and block header optimization on compressed and uncompressed blocks giving promising test results where almost all file formats tested can be compressed with a ratio that is not too large but consistent for all file formats where the ratio compression for all file formats obtained between 0.04 to 12.3. The developed compression model also produces compression failures in files with high uncompressed blocks where the overhead of additional uncompressed blocks of information causes files to become larger with a negative ratio obtained of -0.39 to -0.48 which is still relatively small and acceptable.]]>
<![CDATA[Data Mining Dalam Analisis Faktor Drop Out Mahasiswa Menerapkan Algoritma Decision Tree ]]>
<![CDATA[Azhari, Mulkan]]>;
<![CDATA[Maulana, Halim]]>;
<![CDATA[Riza, Ferdy]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024 ]]>
Publisher : <![CDATA[Universitas Budi Darma ]]>
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DOI: 10.30865/mib.v8i2.7379
<![CDATA[Graduation accuracy is one of the indicators used in assessing the suitability of undergraduate programs as a functional unit of higher education. Knowing the factors that influence student graduation time helps study programs and faculties make decisions to increase the number of students who graduate on time. The purpose of this research is to obtain an overview of the factors that influence students in the accuracy of completing the study time by using the Machine Learning algorithm, namely Decision Tree, which is expected to have high classification efficiency and good description so that it can increase the number of students graduating on time. The methods used to determine student dropout factors are Classification and Regression Tree (CART) and LightGBM. The data used is the data of undergraduate students of Universitas Muhammadiyah Sumatera Utara in 2019. The quality of classification can be read from the accuracy, sensitivity and specification values. The result using CART is 95.1% with the most influencing factors are GPA, faculty, lecture time and predicate while Lightgbm is 83% with the most influencing factors are GPA, gender, lecture time and faculty. Decision tree can be used to determine student dropout factors because of its high accuracy with GPA being the main factor.]]>
<![CDATA[Android-Based Areca Plant Disease Detection Using Convolutional Neural Network (Cnn) Algorithm ]]>
<![CDATA[Khairunnisa]]>;
<![CDATA[Riza, Ferdy]]>
<![CDATA[ Bahasa Indonesia Vol 16 No 03 (2024): Instal : Jurnal Komputer ]]>
Publisher : <![CDATA[Cattleya Darmaya Fortuna ]]>
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DOI: 10.54209/jurnalinstall.v16i03.213
<![CDATA[Indonesia is included in a country that can be said to be the largest areca nut exporting country in the world with a presentation of 80%. The quality of crops is very influential on the agricultural sector and can affect the value of exports, so to maintain the quality of crops, an area nut disease detection application is designed. The purpose of this research is to present information quickly and accurately in problem solving to help detect diseases that exist in areca plants by building a Machine Learning model on the Android system using the Convolutional NEURAL Network (CNN) algorithm. Data is collected through the results of field studies and analysis of related documents to strengthen research data, so that test data is obtained as many as 10 types of diseases and 32 symptoms, image data is processed using a teachable machine. So that the test results obtained the average accuracy of the model in detecting diseases in areca nut plants is 98.7%.]]>
<![CDATA[Perancangan Absensi Dosen Berbasis IoT Memanfaatkan Rfid ]]>
<![CDATA[Harahap, Tri Martati]]>;
<![CDATA[Riza, Ferdy]]>
<![CDATA[ Al-DYAS Vol 4 No 1 (2025): FEBRUARI ]]>
Publisher : <![CDATA[Lembaga Yasin AlSys ]]>
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DOI: 10.58578/aldyas.v4i1.4073
<![CDATA[Attendance is an important element in the lecture system, but it is usually still done manually using attendance books and lists. This manual method is often inefficient in monitoring teacher discipline in terms of attendance and return time. To solve this problem, technologies such as Internet of Things (IoT) and radio frequency identification (RFID) offer a more efficient and accurate solution. IoT allows physical objects to connect to the internet for data exchange, and RFID can be used for automatic identification. This research aims to design an IoT-based lecturer attendance system using RFID and first-in-first-out (FIFO) algorithms. This system is expected to improve the accuracy and efficiency of the instructor attendance process and replace the existing manual method.]]>
