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All Journal Teknika Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics Jurnal Informatika IJISCS (International Journal Of Information System and Computer Science) IndraTech SIENNA Seminar Nasional Teknologi dan Multidisiplin Ilmu
Sriyanto Sriyanto
Department Of Informatics Engineering, Institute Of Informatics And Business Darmajaya Lampung
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Library & Information Science Social Sciences Other

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Benchmark and comparison between hyperledger and MySQL Onno W. Purbo; Sriyanto Sriyanto; Suhendro Suhendro; Rz Abd. Aziz; Riko Herwanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.13743

Abstract

In this paper, we report the benchmarking results of Hyperledger,  a Distributed Ledger, which is the derivation Blockchain Technology.  Method to evaluate Hyperledger in a limited infrastructure is developed. Themeasured infrastructure consists of 8 nodes with a load of up to 20000 transactions/second. Hyperledger consistently runs all evaluation, namely, for 20,000 transactions, the run time 74.30s, latency 73.40ms latency, and 257 tps. The benchmarking of Hyperledger shows better than a database system in a high workload scenario. We found that the maximum size data volume in one transaction on the Hyperledger network is around ten (10) times of MySQL. Also, the time spent on processing a single transaction in the blockchain network is 80-200 times faster than MySQL. This initial analysis can provide an overview for practitioners in making decisions about the adoption of blockchain technology in their IT systems.
Design of a wideband strip helical antenna for 5G applications Mohammed Yousif Zeain; M. Abu; Z. Zakaria; Ahmed Jamal Abdullah Al-Gburi; R. Syahputri; A. Toding; Sriyanto Sriyanto
Bulletin of Electrical Engineering and Informatics Vol 9, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (485.426 KB) | DOI: 10.11591/eei.v9i5.2055

Abstract

This paper presents the design of wideband strip helical antenna for 5G application. The strip helical antenna is designed for 5G and wideband applications that provide a wide bandwidth and circular polarization. The helical antenna is planned on at 5.8 GHz frequency by using teflon material. The new designed strip is printed on a substrate then rolled into a helix shape to achieve circular polarization without an impedance matching and that the proposed antenna can be used for potential applications in wideband wireless communication. A wideband bandwidth of 2.41 GHz with a resonant frequency at 5.8 GHz is achieved by the helical antenna on the teflon substrate. The presented antenna on teflon substrate has achieved a gain of 11.2 dB. The antenna design parameters and the simulated results are achieved using the commercial software CST. The proposed antenna can be used for various wireless applications such as wideband, ultra wideband, 5G and wireless applications.
PENERAPAN DECISION TREE C4.5 SEBAGAI SELEKSI FITUR DAN SUPPORT VECTOR MACHINE (SVM) UNTUK DIAGNOSA KANKER PAYUDARA Pakarti Riswanto; RZ. Abdul Aziz; Sriyanto -
Jurnal Informatika Vol 19, No 1 (2019): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v19i1.1442

Abstract

In the field of medicine, the use of data mining has a quite important and evolutionary role that can change the perspective of doctors, practitioners and health researchers in the process of detecting breast cancer in a patient. There are 2 classification applications in it, namely the process of diagnosing (diagnosing) cancer cells that distinguishes between tumors (benign cancer) or malignant cancer and prognosis (prognosis) to determine the possibility of reappearance of cancer cells in patients who have been operated on in the future. Data mining aims to describe new findings in the dataset and explain a process that uses statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify useful information and related knowledge from the database.Classification with data mining can be done using several methods, namely Decision Tree, K-Nearest Neighbor, Naive Bayes, ID3, CART, Linear Discriminant Analysis, etc., which certainly have advantages and disadvantages of each. But in this study, the author focuses on the classification of data mining using the Support Vector Mechine and Deccision Tree algorithms.This study will analyze the Breast Cancer Wisconsin Original data set obtained from the UCI Machine Learning Repository (repository of research data) to classify breast cancer malignancies. This time the author correlates between the Decision Tree classifier algorithm which has good ability to process large databases as a feature selection, then with a proper and relevant SVM Method used in analyzing and diagnosing breast breast cancer patients because it has accurate results for existing problems and several bases . Keywords— Data Mining, diagnosis, Decision Tree, SVM Method
Identifikasi Penyakit Diabetes Millitus Menggunakan Jaringan Syaraf Tiruan Dengan Metode Perambatan-Balik (Backpropagation) Sriyanto Sriyanto; Sutedi Sutedi
Jurnal Informatika Vol 10, No 2 (2010): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v10i2.163

Abstract

Diabetes Melitus (DM) is dangerous disease that affect many of the various layer of work society. This disease is not easy to accurately recognized by the general society. So we need to develop a system that can identify accurately. System is built using neural networks with backpropagation methods and the function activation sigmoid. Neural network architecture using 8 input layer, 2 output layer and 5 hidden layer. The results show that this methods succesfully clasifies data diabetics and non diabetics with near 100% accuracy rate. Keyword : Neural Network, Backpropagation, diabets
IMPLEMENTASI SISTEM PAKAR UNTUK MENDIAGNOSA KERUSAKAN PRINTER JENIS CANON BJC-2100SP chairani chairani; Sriyanto Sriyanto; Fitria .
Jurnal Informatika Vol 12, No 1 (2012): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v12i1.135

Abstract

Printer as the printing tool is already dominate several field, such as office, shop, school, university, educational institution, etc. In certain time, there must be trouble in printer using, just like another machines, damages. So that, no matter how hi-tech the printing tool, it must need the expert to fix the damages.Expert system transform the knowledge of the expert(s) to be a computer system that help general people to do anything like an expert. In this case, expert system is built to diagnose the damage of printer type Canon BJC-2100SP. This expert system will increase time of effort to diagnose the damage of the printer type Canon BJC-2100SP for computer technician, specially for printer type Canon BJC-2100SP. Keyword : Production system, expert system, Rule, Knowledge, Inference Engineering.
MEMBANDINGKAN PERFORMA ANTARA HYPERLEDGER DAN MYSQL Riko Herwanto; Onno W. Purbo; Sriyanto Sriyanto
Jurnal Informatika Vol 20, No 1 (2020): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v20i1.1816

Abstract

In this paper, we report the benchmarking results of Hyperledger, a Distributed Ledger, which is the derivation Blockchain Technology. Method to evaluate Hyperledger in a limited infrastructure is developed. The measured infrastructure consists of 8 nodes with a load of up to 20000 transactions/second.. The benchmarking of Hyperledger shows better than a database system in a high workload scenario. We found that the maximum size data volume in one transaction on the Hyperledger network is around ten (10) times of MySQL. Also, the time spent on processing a single transaction in the blockchain network is 80-200 times faster than MySQL. This initial analysis can provide an overview for practitioners in making decisions about the adoption of blockchain technology in their IT systems.
NEURAL NETWORK OPTIMIZATION WITH GENETIC ALGORITHM FOR HEART DISEASE PREDICTION M Agus Badruzaman Al Khoir; Sriyanto Sriyanto
IJISCS (International Journal of Information System and Computer Science) Vol 6, No 2 (2022): IJISCS (International Journal of Information System and Computer Science)
Publisher : STMIK Pringsewu Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v6i2.1235

Abstract

Coronary Heart Disease (CHD) is a contributor to the number 1 cause of death in the world besides cardiovascular disease. The tendency of Indonesian people who do not know and ignore coronary heart disease is a factor that causes Indonesia to be high a contributor to deaths caused by coronary heart disease. This research is expected to produce new predictions of heart disease using genetic optimization of neural networks with better prediction results and can obtain algorithms with new percentage values in predicting coronary heart disease. Genetic optimization of the neural network is used because the algorithm follows the human nervous system which has the characteristics of parallel processing, processing elements in large quantities, and fault tolerance. The results of the research carried out are the accuracy obtained by 82.18% and increased to 83.50% after using genetic algorithm optimization, from these results it can be concluded that the neural network algorithm can be better if it is supported by genetic algorithm optimization
PENENTUAN KEPUTUSAN ALAT KONTRASEPSI YANG TEPAT MENGGUNAKAN ALGORITMA NAÏVE BAYES Ayu Brahdika Putri; Sriyanto Sriyanto; Firmansyah Yunialfi
IndraTech Vol 3, No 2 (2022): Oktober 2022
Publisher : STMIK Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56005/jit.v3i2.121

Abstract

Indonesia merupakan negara berkembang yang memiliki jumlah penduduk yang cukup padat. Pertumbuhan penduduk Indonesia yang semakin meningkat mendorong pemerintah untuk mengembangkan upaya-upaya pengendalian kelahiran, memperkecil angka kematian dan peningkatan kualitas penduduk, salah satunya dengan program Keluarga Berencana. Program Keluarga Berencana (KB) merupakan salah satu upaya pemerintah untuk mengendalikan laju pertumbuhan penduduk serta membentuk keluarga yang berkualitas. Alat kontrasepsi terdiri dari metode operasi wanita (MOW) atau sterilisasi wanita, metode operasi pria (MOP) atau sterilisasi pria, pil, IUD, suntik KB, kondom, metode amenore laktasi (MAL), Imlpant, Senggama Terputus dan Kalender. Pemilihan alat kontrasepsi yang sesuai penting dilakukan oleh pasangan mengingat kehamilan haruslah direncanakan. Perencanaan kehamilan penting dilakukan agar pasangan siap secara mental, fisik, maupun kondisi ekonominya. Akurasi yang dihasilkan oleh algoritma Naïve Bayes sedikit lebih baik dibandingkan dengan DT. C45 dengan Naïve Byes mendapat akurasi sebesar 91,91% dan DT.C45 sebesar 91,18%. Precision yang dihasilkan oleh algoritma Naïve Byes lebih baik dibandingkan dengan DT. C45 dengan Naïve Byes mendapat akurasi sebesar 79,82% dan DT.C45 sebesar 70,73%. Recall yang dihasilkan oleh algoritma Naïve Byes lebih baik dibandingkan dengan DT. C45 dengan Naïve Byes mendapat akurasi sebesar 77,71% dan DT.C45 sebesar 65,59%.Kata Kunci : Algoritma C4.5, Naïve Bayes, Alat Kontrasepsi, Rapidminer
XSS Attack Detection and Mitigation Using Multi-Layer Security Mechanism (MLSM) Hartono; Sriyanto
Sienna Vol 3 No 2 (2022): Sienna Volume 3 Nomor 2 Desember 2022
Publisher : LPPM Universitas Muhammadiyah Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

BSSN stated that there were 12.9 million cyber threats in Indonesia during 2018. In January - April 2020, the number of cyber-attacks increased. In those four months, the number of cyberattacks reached 88 million. The methods, applications, and attack techniques used cannot be identified easily. However, according to data from the OWASP Top Ten in 2017 and 2021 (statistics-based proposal), there are 10 website security vulnerabilities that are most often exploited. XSS is one of the security holes included in the list. In addition to being a loophole that is often found, the impact of XSS is very fatal, because it allows attackers to do account takeovers, theft of personal data, and so on. There are several studies that have implemented mechanisms to detect and mitigate XSS attacks. However, the implementation has not yet obtained effective and holistic results. The mechanism tested by previous research still leaves a security problem that allows attackers to execute XSS attacks. One of the things that cause this problem is the use of a single-layer security mechanism. Therefore, the purpose of this study is to test the effectiveness of the multi-layer security (MLSM) mechanism in detecting and mitigating XSS attacks. MLSM consists of five layers, namely OWASP ModSecurity, Framework/CMS Security Feature, HTTP Middleware, Templating Engine, and Data Sanitizer. To test the security level of MLSM, the researchers conducted a simulation of attacks using the Arachni and ZAP applications on a sample website that had 170 XSS security vulnerabilities. Based on test attacks on non-MLSM websites, Arachni successfully executed 168 of 170 (98.82%), and ZAP executed 103 of 170 (60.58%) XSS attacks. However, after implementing the MLSM feature on the website, Arachni and ZAP attacks failed to perform XSS attacks, both stored, reflected, and DOM-based XSS. There is no single type of XSS attack that can be carried out on MLSM websites
PREDIKSI PENYAKIT MALARIA MENGGUNAKAN PRE-TRAINED MODEL ALGORITMA DENSE CONVOLUTIONAL NETWORK (DENSENET) Asep Eryana; Sriyanto Sriyanto; Nursiyanto Nursiyanto
IndraTech Vol 3, No 2 (2022): Oktober 2022
Publisher : STMIK Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56005/jit.v3i2.127

Abstract

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Co-Authors A. Toding Adhi Tristiyanto Ahmed Jamal Abdullah Al-Gburi Asep Eryana Ayu Brahdika Putri Aziz, RZ. Abdul Chairani Chairani Firmansyah Yunialfi Fitria . Hartono Hartono Herwanto, Riko Khodijah Khodijah Kurniawan Saputra M Agus Badruzaman Al Khoir M. Abu Mohammed Yousif Zeain Nursiyanto Onno W. Purbo Onno W. Purbo Pakarti Riswanto R. Syahputri Sutedi Sutedi Y. Suhendro Z. Zakaria Zuriati Zuriati