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All Journal Indonesian Journal of Electronics and Instrumentation Systems IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Penelitian dan Pengembangan Sains dan Humaniora (JPPSH) JURNAL MANAJEMEN AGRIBISNIS Sinkron : Jurnal dan Penelitian Teknik Informatika SINTECH (Science and Information Technology) Journal Jurnal Ilmiah Pendidikan dan Pembelajaran JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia)
PUTU SUGIARTAWAN
Institut Bisnis Dan Teknologi Indonesia (INSTIKI)
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Hyperparameter Optimization Techniques for CNN-Based Cyber Security Attack Classification Adnyana, I Gede; Sugiartawan, Putu; Hartawan, I Nyoman Buda
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 18, No 3 (2024): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.98427

Abstract

Abstract The proliferation of cyber security attacks necessitates advanced and efficient detection methods. This study explores the application of Convolutional Neural Networks (CNNs) for classifying cyber security attacks using a comprehensive dataset containing various attack types and network traffic features. Emphasizing the role of hyperparameter optimization (HPO) techniques, this research aims to enhance the CNN model's performance in accurately detecting and classifying cyber attacks. Traditional machine learning approaches often need to catch up in capturing the complex patterns in such data, whereas CNNs excel in automatically extracting hierarchical features. Using the provided dataset, which includes attributes such as packet length, source and destination ports, protocol, and traffic type, we implemented various (HPO) techniques, including Grid Search, Random Search, and Bayesian Optimization, to identify the optimal CNN configurations. Our optimized CNN model significantly improved classification result. to baseline models without hyperparameter tuning. The results underline the importance of HPO in developing robust CNN models for cybersecurity applications. This study provides a practical framework for leveraging deep learning and optimization techniques to enhance cyber defense mechanisms, paving the way for future advancements in the field.
Information System for Monitoring Production Process of Dried Kelor Leaf Dried Using the FAST Method Sudiarsa, I Wayan; Sudipa, I Gede Iwan; Sugiartawan, Putu; Maharianingsih, Ni Made; Pande, Ni Kadek Nita Noviani
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.13095

Abstract

Moringa or Kelor leaves, rich in nutrients and health benefits, are used in many culinary, supplement, and medicinal items. However, drying moringa leaves is a crucial step that impacts product quality. Companies must maintain product quality and production efficiency to meet rising demand. Since moringa leaf drying production management is difficult, this study uses the Framework for the Application System Thought (FAST) method. Its use in moringa drying allows thorough monitoring of temperature, humidity, drying duration, and other product quality factors. According to this research, using the FAST method in the moringa leaf drying production management monitoring application will help identify production issues, prevent product damage, and improve product quality. This research improves moringa production management and helps explain FAST method implementation in industrial process management. FAST is significant for monitoring applications because it can continually monitor all production conditions that affect drying moringa leaves. FAST can immediately detect dryer humidity issues. The FAST technique and moringa drying production management monitoring applications can be used to improve product quality, operational efficiency, and consumer safety in this research. Thus, this research gives tangible answers for the moringa processing business and can be applied to other industrial sectors facing comparable production process management issues.
Deteksi Tingkat Kematangan Tandan Buah Segar Kelapa Sawit dengan Algoritme K-Means Sari, Wahyuni Eka; Muslimin, Muslimin; Franz, Annafi; Sugiartawan, Putu
SINTECH (Science and Information Technology) Journal Vol. 5 No. 2 (2022): SINTECH Journal Edition Oktober 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v5i2.1146

Abstract

Oil extraction rate (OER) of fresh fruit bunches (FFB) of palm oil is depend on the stage of ripeness. The process of detecting the ripeness of oil palm FFB has difficult by manually. Farmers find it difficult to reach the fruit to detect ripeness with the eye, when the palm tree is tall. So farmers need a system that is able to detect the maturity level of oil palm FFB based on color. The K-Means method is capable of clustering based on the closest mean value to the centroid from a number of objects to cluster k. Data obtained from 2 oil palm plantations in East and North Kalimantan. In this study, the clustering of fresh fruit bunches of oil palm has four levels of maturity based on the calculation of the elbow method. The training data used in this study is 80 data. The test image data used in this study is 40 data. There are 36 appropriate data based on the classification method so the accuracy obtained in grouping using the k-means clustering segmentation method is 90%.
Media Pembelajaran Interaktif Klasifikasi Hewan di Sekolah Dasar Setiawan, I Made Dedy; Putra, Ryan Pratama; Sugiartawan, Putu
Jurnal Penelitian dan Pengembangan Sains dan Humaniora Vol. 6 No. 3 (2022): Oktober
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jppsh.v6i3.55129

Abstract

Kegiatan pembelajaran peserta didik kurang mampu memahami materi pelajaran tentang klasifikasi hewan. Sementara guru masih menggunakan metode pembelajaran konvensional dalam menyampaikan materi ajar kepada peserta didik menggunakan buku ajar dengan metode ceramah, tanpa memanfaatkan media pembelajaran yang relevan, sehingga pembelajaran menjadi kurang menarik. Tujuan penelitian ini adalah untuk menciptakan media pembelajaran interaktif klasifikasi hewan di SD. Jenis penelitian ini merupakan penelitian pengembangan menggunakan model pengembangan ADDIE dengan subjek penelitian sebanyak 2 ahli pakar dan 32 orang. Metode pengumpulan data dengan observasi, wawancara, dan kuisioner. Data selanjutnya dianalisis secara kualitatif dan kuantitatif. Berdasarkan hasil uji ahli konten diperoleh persentase skor 80,25% dengan kualifikasi baik, hasil uji ahli media dan desain diperoleh persentase skor 88,75% dengan kualifikasi baik, serta hasil uji coba kelompok diperoleh persentase skor 85, 83% dengan kualifikasi baik. Berdasarkan hasil penelitian, media pembelajaran interaktif tentang klasifikasi hewan dinyatakan valid dan layak digunakan dalam kegiatan pembelajaran di kelas 3 SD. Implikasi penelitian ini diharapkan dapat membantu guru dan siswa dalam proses pembelajaran, sehingga tujuan pembelajaran dapat tercapai.
Media Pembelajaran Interaktif Pada Materi Klasifikasi Hewan untuk Siswa Sekolah Dasar I Made Dedy Setiawan; Ryan Pratama Putra; Putu Sugiartawan
Jurnal Ilmiah Pendidikan dan Pembelajaran Vol. 6 No. 3 (2022): Oktober 2022
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jipp.v6i3.56641

Abstract

Dalam kegiatan pembelajaran di kelas, peserta didik kurang mampu memahami materi pelajaran tentang klasifikasi hewan. Sementara guru masih menggunakan metode pembelajaran konvensional dalam menyampaikan materi ajar kepada peserta didik menggunakan buku ajar dengan metode ceramah, tanpa memanfaatkan media pembelajaran yang relevan, sehingga pembelajaran menjadi kurang menarik. Tujuan penelitian ini adalah untuk merancang sebuah media pembelajaran interaktif yang layak diimplementasikan. Pengembangan media pembelajaran interaktif menggunakan model pengembangan ADDIE dengan subjek penelitian sebanyak 32 orang. Metode pengumpulan data dengan observasi, wawancara, dan kuisioner. Data selanjutnya dianalisis secara kualitatif dan kuantitatif. Berdasarkan hasil uji ahli konten diperoleh persentase skor 80,25% dengan kualifikasi baik, hasil uji ahli media dan desain diperoleh persentase skor 88,75% dengan kualifikasi baik, serta hasil uji coba kelompok diperoleh persentase skor 85, 83% dengan kualifikasi baik. Berdasarkan hasil penelitian dapat disimpulkan media pembelajaran interaktif tentang klasifikasi hewan dinyatakan valid dan layak digunakan dalam kegiatan pembelajaran di kelas 3 sekolah dasar.  
Analisis Customer Relationship Management (CRM) dengan Menggunakan Aplikasi Power Business Intelligence (BI) Pada Pt. Terang Abadi Raya ariani, alda; Sugiartawan, Putu
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 4 No 3 (2022): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.151

Abstract

Service is something that must be done in a management, in order to increase and maintain sales results. PT. Terang Abadi Raya is a company that distributes a product in the form of electrical equipment. PT. Terang Abadi Raya adheres to the loyalty of its customers. This company does not yet have a system that can assist the company in retaining its customers. With the technology, the company must have a close relationship with its customers, so that the company's relationship with its customers begins to become a major problem that must continue to be considered. Therefore, Customer Relationship Management (CRM) has become an important concept or thing in the business world. Using the Power BI application, which is very simple and fast, can be one of the solutions to problems in processing and visualizing data into a more attractive and interactive graphic form. The system created displays 6 graphs according to company needs, namely customer purchasing trends, top 10 purchases based on customers, top 10 purchases based on goods, top 10 purchases based on sales, the highest purchases based on customer area and customer purchases during the pandemic. In practice, Power Business Intelligence (BI) and Customer Relationship Management (CRM) applications can be integrated so as to produce an analysis and consideration that is relevant to what strategy the company will undertake in competitive competition..
Rancang Bangun Sistem Informasi Keuangan Pada CV.Tiga Mestika Berbasis Website Setiawan, Adam; Sugiartawan, Putu
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 4 No 3 (2022): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.152

Abstract

Tiga Mestika was established on October 18, 2007, CV Tiga Mestika is located on Jl Pulau Komodo No 21 Denpasar. Based on the results of interviews, there are problems that occur in the company's operations, in particular, the financial statements produced are not accurate, the impact is that there are often errors in writing financial data by admins. In addition, the archiving of records of sales and purchase notes is recorded manually causing an incorrect cash book. properly archived, so that checking reports on the cash book is difficult to do every year. Based on the description of the problems contained in CV. Tiga Mestika, a computerized financial reporting system is needed to facilitate the work on CV. Three Jewels. This information system will be able to minimize the risk of errors in managing financial statements, bookkeeping records will also become more accurate and make it easier to find data quickly when needed so as to be able to provide better service to customers or consumers. Based on the problems that occur in the company, the authors create a system, namely "Designing the Financial System at CV Tiga Mestika based on a website" from the results of tests carried out with the Blackbox lissing method, this information system can run according to the analysis and design carried out.
Prediksi Penjualan Produk Menggunakan Data Mining Dengan Metode K-Nearest Neighbor Pada PT. Terang Abadi Raya Supandi, Endang; sugiartawan, putu
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 4 No 3 (2022): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.153

Abstract

Terang Abadi Raya is a lighting and cable distributor company that has various types of goods, with the many types of products to be sold the company has difficulty in determining which products are the most sold in the market. This makes it difficult for the marketing department to offer products to be sold. PT. Terang Abadi Raya has various types of products based on sales data for the last 5 years, using the K-Nearest Neighbor prediction can make it easier for companies to plan sales. To find out the best-selling sales using the maining data classification and the K-Nearest Neighbor method. The results of this study are predictions of sales of the best-selling electric tools as many as 5 items. Based on the accuracy value of the best selling product sales classification of 99,50074%.
Support Vector Machine for Accurate Classification of Diabetes Risk Levels Sugiartawan, Putu; Wardani, Ni Wayan; Pradhana, Anak Agung Surya; Batubulan, Kadek Suarjuna; Kotama, I Nyoman Darma
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 3 (2025): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.107740

Abstract

This research explores the application of Support Vector Machines (SVM) for accurately classifying diabetes risk levels based on a publicly available dataset containing 768 instances and 9 attributes, including glucose levels, BMI, blood pressure, and insulin levels. The model's systematic development process involved data preprocessing, feature selection, and hyperparameter optimization to ensure robust performance. Results indicate an overall accuracy of 76%, with high precision and recall for the non-diabetic risk class, but relatively lower performance for the diabetic risk class, highlighting the challenges posed by class imbalance and overlapping data features. To address these issues, future research should incorporate advanced resampling techniques, refined feature engineering, and alternative machine learning models like Random Forest or XGBoost. This research underscores the potential of SVM as a valuable tool for early diabetes detection, offering healthcare professionals a reliable means to identify at-risk individuals and personalize intervention strategies. By bridging theoretical advancements and practical applications, the research contributes to enhancing predictive analytics in medical diagnostics, paving the way for improved patient outcomes and efficient public health management
Adaptive Operator and Scaling Factor Selection in Differential Evolution using Parametrized Reinforcement Learning Santiyuda, Kadek Gemilang; Sugiartawan, Putu; Santiago, Gede Agus; Ardriani, Ni Nengah Dita; Kafiyanna, Moch Ilham Nur
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 7 No 3 (2025): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.206

Abstract

Mutation strategy selection along with parameter settings are well known challenges in enhancing the performance of differential evolution (DE). In this paper, we propose to solve these problems as a parametrized action Markov decision process. A multi-pass deep Q-network (MP-DQN) is used as the reinforcement learning method in the parametrized action space. The architecture of MP-DQN comprises an actor network and a Q-network, both trained offline. The networks’ weights are trained based on the samples of states, actions and rewards collected on every DE iterations. We use 99 features to describe a state of DE and experiment on 4 reward definitions. A benchmark study is carried out with functions from CEC2005 to compare the performance of the proposed method to baseline DE methods without any parameter control, with random scaling factor, and to other DEs with adaptive operator selection methods, as well as to the two winners of CEC2005. The results show that DE with MP-DQN parameter control performs better than the baseline DE methods and obtains competitive results compared to the other methods.
Co-Authors Adam Setiawan, Adam Adriani, Ni Nengah Dita Agung Mahadewa, I Putu Agus Aan Jiwa Permana Aniek Suryanti Kusuma, Aniek Suryanti annafi franz, annafi Ardriani, Ni Nengah Dita ariani, alda Arimawarni, Rafika Aryawan, I Made Gitra Batubulan, Kadek Suarjuna Cintya Dewi, Ni Putu Senantri Darma Wandika, I Made Pranadata Desak Made Dwi Utami Putra Dewa, Hari Putra Maha Dewi, Ni Made Gusnia Didit Suprihanto, Didit Dinata, I Gede Surya Dirgayusari, Ayu Manik Erawati, Kadek Nonik Febyanti, Putu Ayu Frasetya, I Gusti Ngurah Hendra Gebo, Alexander Hartama, I Dewa Agung Bayu Mega I Dewa Made Krishna Muku I Gede Adnyana I Gede Andika I Gede Iwan Sudipa I Gede Made Yudi Antara I Gede Totok Suryawan I Gusti Made Ngurah Desnanjaya I Komang Arya Ganda Wiguna I MADE DEDY SETIAWAN . I Made Yudiana I Nyoman Agus Suarya Putra I Nyoman Buda Hartawan I Wayan Dharma Suryawan I Wayan Ramantha I WAYAN SUDIARSA Indawan, I Gusti Agung Indra Pratistha Jumariana, I Putu Candra Junaidi, Muh. Lutfi Kafiyanna, Moch Ilham Nur KETUT BUDI SUSRUSA Kotama, I Nyoman Darma Kumara, I Dewa Made Putra Kusuma, I Made Wijaya Maharianingsih, Ni Made Mahendra, I Gede Orka Mauko, Arfan Murdhani, I Dewa Ayu Sri Murpratiwi, Santi Ika Muslimin B, Muslimin Muslimin Muslimin Negara, I Gede Sunia Ni Ketut Kertiasih Novitadewi, Ni Made Ary Ntihung, Maria Ephifania Ntihung Nurul Hidayat Paholo Iman Prakoso Palus, Petrus Pande, Ni Kadek Nita Noviani Pradhana, Anak Agung Surya Prakoso, Paholo Iman Prastika, I Kadek Aris Putra, I Wayan Kintara Anggara Putra, Putu Gede Weda Pramana Rachmat Wahid Saleh Insani radho, alpolinaris edius Riska, Putu Rizky, Muhammad Alfa Rowa, Heruzulkifli Rustina, I Dewa Ketut Rai Ryan Pratama Putra Ryan Pratama Putra, Ryan Pratama Ryanta, Made Santiago, Gede Agus Santiyuda, Kadek Gemilang Saputra, Komang Yodi Andira Sariayu, Vilomena Satya, I Putu Adnya Sindu, I Gede Partha Suardana, I Made Eka Supandi, Endang Trisnayanti, Ni Made Ratih Wadi, Faska Aris Y K Wahyuni Eka Sari Wardani, Ni Wayan Wibawa, Gusti Putu Sutrisna Widya Dharma, I Gusti Ngurah Adi Willdahlia, Ayu Gede willdalia, ayu Wiratama, Ichsan wirayanti, Ni Putu Eka Wisnawa, Komang Surya Wiwahana Prasetya, I Made Irfan Yudara, I Gede Yudiana, I Made Yuri Prima Fittryani, Yuri Prima