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All Journal Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Edukasi dan Penelitian Informatika (JEPIN) Prosiding Semnastek REKAYASA Journal of Information Systems Engineering and Business Intelligence Network Engineering Research Operation [NERO] JURNAL INSTEK (Informatika Sains dan Teknologi) Berdikari: Jurnal Pengabdian Masyarakat Indonesia Jurnal Sistem Cerdas Dinasti International Journal of Education Management and Social Science JATI (Jurnal Mahasiswa Teknik Informatika) Teknika Journal of Information Technology and Cyber Security
Budi Dwi Satoto
Universitas Trunojoyo Madura
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Physics

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Empowerment of the Talango Islands Community Sumenep Regency through digital printing and screen printing business Budi Dwi Satoto; Bain Khusnul Khotimah
Berdikari: Jurnal Pengabdian Masyarakat Indonesia Vol. 1 No. 3 (2019): Berdikari: jurnal Pengabdian Masyarakat Indonesia
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (267.112 KB)

Abstract

The role of youth in development is very important because it is considered productive age to support various development activities in various sectors. Most youth can be absorbed in the labor market, and partly eliminated from the competition become static group. Not a few who engage in Small and Medium Enterprises such Silk Screen Printing. However, the form of efforts among youth most still use manual design and printing due to lack of capital and expertise. With this activity, try to solve them with IbM is working with partners Silk Screen Printing Industry centers in villages Talango, Talango islands, Sumenep, Disperindag and local cooperative activities such as application of digital printing printing techniques, the design theme of local wisdom Madura images with color or multicolor monocolor and entrepreneurship training and business management. IbM activity is done in the form of training, coaching and mentoring the youth group field of screen printing and printing for souvenirs and handicrafts which aims to: 1) increase the motivation of entrepreneurial partners; 2) improve the understanding of partner business planning and business management; 3) improve human resource capabilities in the production and marketing techniques; 4) develop a network to support youth entrepreneurship development of the creative economy. Youth empowerment group is expected to produce a model that can be used as a model youth entrepreneurial development youth empowerment-based society.
Classification of Corn Seed Quality Using Convolutional Neural Network with Region Proposal and Data Augmentation Budi Dwi Satoto; Rima Tri Wahyuningrum; Bain Khusnul Khotimah
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26222

Abstract

Corn is one of the essential commodities in agriculture. All components of corn can be utilized and accommodated for the benefit of humans. One of the supporting components is the quality of corn seeds, where a specific source has the physiological qualities to survive. The problem is how to get information on the quality of corn seeds at agricultural locations and get information through the physical image alone. This research tries to find a solution to obtain high accuracy in classifying corn kernels using a convolutional neural network because there is a profound training process. The problem with convolutional neural networks is the training process takes a long time, depending on the number of layers in the architecture. This research contributes to increasing the computing time with the proposed contribution by adding Region proposals with a convex hull to use on a custom layer. The method's purpose is a region proposal area with a convex hull to increase the focus on the convolution multiplication process. It affected reducing unnecessary objects in background images. A custom layer architecture by maintaining the priority layer is an option to get a shorter computational time in constructing a model. In addition, the architecture that is made still considers the stability of the training process. The results on the classification of corn seeds are obtained by a model with an average accuracy of 99.01%—the Computational training time to get the model is 2 minutes 30 seconds. The average error value for MSE is 0.0125, RMSE is 0.118, and MAE is 0.0108. The experimental data testing process has an accuracy ranging from 77% -99%. In conclusion, using region proposals can increase accuracy by around 0.3% because focused objects assist the convolution process
Klasifikasi Covid-19 menggunakan Arsitektur DarkCovidNet pada Citra Radiografi X-ray Dada Wahyuningrum, Rima Tri; Putra, Wahyu Zainur; Satoto, Budi Dwi; Sari, Amillia Kartika; Sensusiati, Anggraini Dwi
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 1 (2024): Volume 10 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i1.69817

Abstract

Covid-19 adalah penyakit severe acute respiratory syndrome. Coronavirus menjadi penyebab gangguan pernapasan dan infeksi paru paru, sehingga dapat menyebabkan kematian. Penyakit Covid-19 sudah tersebar ke seluruh negara termasuk negara Indonesia. Meskipun saat ini, Covid-19 telah mereda namun pencegahan maupun penanganannya tetap dibutuhkan. Oleh karena itu sangat diperlukan alat untuk mendiagnosis penyakit Covid-19 pada X-ray dada. Penggunaan klasifikasi citra berfungsi untuk memproses penggabungan piksel pada suatu citra ke dalam kelompok untuk diinterpretasikan sebagai bentuk properti yang spesifik. Dengan klasifikasi citra, mampu mempermudah pengelompokan individu untuk mewakili fitur kelas citra. Pada penelitian citra radiografi X-ray dada ini, menggunakan multiclass-classification yang terdiri dari 3 kelas yaitu: Covid-19, Normal (No-Findings), dan Pneumonia. Dataset yang diperoleh berjumlah 4.945 citra X-ray.  Pertama, dilakukan proses input citra dan resize image. Setelah itu dilakukan pembagian data yaitu 80% sebagai data train dan 20% sebagai data test. Pada proses pelatihan (train) akan menggunakan model DarkCovidNet. Arsitektur yang diusulkan terdiri dari 19 convolutional layer dan 5 maxpooling. Model ini terdapat proses DarkNet (DN). DN terdiri dari proses convolutional, batch normalization dan LeakyReLU. Pada skenario uji coba menggunakan optimasi Adam, reduce learning rate, dan menambahkan 3 hidden layer. Hasil uji coba terbaik terdapat pada uji coba keempat dengan hasil akurasi sebesar 95,85%, F1-score 95,89%, AUC 99,48%. Dengan demikian model DarkCovidNet tersebut sangat bagus dalam melakukan klasifikasi citra X-ray dada.
Identifying Dominant Actors of Ferdy Sambo's Case Network on Social Media X/Twitter Using Social Network Analysis for Public Relations Strategy Prastiti, Novi; Satoto, Budi Dwi; Efendi, Moch Rizal
Journal of Information Technology and Cyber Security Vol. 2 No. 1 (2024): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.10852

Abstract

The Indonesian National Police (Polri) has experienced ups and downs in building a positive image in interacting with the public. This decline in trust is caused by the emergence of various issues that show the low performance of the police. In the Ferdy Sambo case study, the performance and integrity of the police is at stake and the sensitivity of the police to meet public expectations. One solution to im-prove the image is through an effective public relations strategy. However, to develop it, a deep un-derstanding of the characteristics and interaction patterns between social media through social net-work analysis is required. This research aims to identify influential X/Twitter actors in the case study of Inspector General Ferdy Sambo by applying the centrality method in Social Network User Analysis. The results of centrality analysis on the network show a wide variety of centrality levels. The @Zaindamai account dominates with the highest Degree Centrality value of 0.426829, indicating the number of connections in the network. The main role in disseminating information is held by @Zaindamai with the highest Betweenness Centrality value of 0.325748, indicating its role in connect-ing various networks. @Rizkynu46127931 stands out in Closeness Centrality with a high value of 0.497791, signifying quick and efficient access to all parts of the social network. In addition, @Rizkynu46127931 has significant influence in the network based on the highest Eigenvector Cen-trality of 0.245625. This centrality value forms the basis for formulating a more focused public relations strategy, improving the efficiency of communication with stakeholders, and designing a more concrete public relations plan.
Application of the DBSCAN Algorithm in MSME Clustering using the Silhouette Coefficient Method Abidin, Mochammad Syahrul; Kustiyahningsih, Yeni; Rahmanita, Eza; Satoto, Budi Dwi; Firmansyah, Muhammad Iqbal
Jurnal Sistem Cerdas Vol. 7 No. 3 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i3.472

Abstract

MSMEs participate in the very important contribution of developing Indonesia's economy, where this industry contributes to GDP and also to the absorption of labor. Most MSMEs in Sidoarjo Regency are still constrained by financial management and the utilization of technology. This research will apply the DBSCAN method to clustering MSMEs in Sidoarjo for the purpose of finding patterns in characteristics related to capital, turnover, and workforce. The analysis will involve 1,479 MSMEs, while the research methodology applies the CRISP-DM method to guide the process from business understanding up to the implementation phase. Normalization using Simple Feature Scaling was applied before clustering. The results of this analysis provide insight that the best possible combination of the parameters in DBSCAN is epsilon (ε) 0.10 and MinPts 16, which gives the optimal value of Silhouette Score as 0.4304. It creates seven clusters, in which the third has the highest Silhouette value of 0.9326, indicating that there are high similarities recorded within that cluster. These results provide essential lessons to develop more targeted policy strategies and interventions for MSMEs in Sidoarjo and explore the capabilities of DBSCAN as an effective analytical tool in determining the characteristics of businesses in the region.
Optimasi Klasifikasi Sentimen Menggunakan Random Forest dengan Preprocessing K-Means Clustering dan SMOTE Angkoso, Cucun Very; Thrisna, Mochamad Adrian Nuradha; Satoto, Budi Dwi; Kusumaningsih, Ari
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 3 (2024): Volume 10 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i3.84514

Abstract

Salah satu topik penelitian terkini dalam bidang pengolahan informasi adalah opinion mining atau analisis sentimen dimana didalamnya terdapat pekerjaan utama yaitu klasifikasi sentimen pada data teks. Penelitian ini bertujuan mengoptimalkan proses klasifikasi sentimen dengan mengatasi tantangan-tantangan umum seperti ketidakseimbangan kelas dan kualitas data input dengan mengusulkan metode baru untuk meningkatkan kinerja mesin klasifikasi yang digunakan. Data yang digunakan untuk mengevaluasi metode yang diusulkan adalah satu topik yang diperbincangkan di media sosial Twitter yaitu terkait kebijakan peralihan mobil listrik di Indonesia. Jumlah data yang dikumpulkan adalah tweet berbahasa Indonesia dimulai pada tanggal 01 Januari 2019 hingga 27 Februari 2023 dengan jumlah data yang diperoleh adalah 7.745 data tweet. Penelitian ini mengikuti model penelitian data science CRISP-DM, dimulai dengan observasi topik, pengumpulan data, pelabelan, dan preprocessing data. Data yang telah diberi label dibagi menjadi data train dan data test, kemudian melalui tahap ekstraksi fitur menggunakan TF-IDF (Term Frequency-Inverse Document Frequency). Model Random Forest diterapkan untuk klasifikasi sentimen, dan teknik SMOTE (Synthetic Minority Over-sampling Technique) digunakan untuk menangani ketidakseimbangan kelas. Hasil eksperimen menunjukkan bahwa kombinasi preprocessing K-Means Clustering dan SMOTE secara signifikan meningkatkan kinerja model klasifikasi sentimen. Model Random Forest menghasilkan akurasi sebesar 98,47% dengan 5-fold cross validation, dan setelah penambahan teknik SMOTE, akurasi meningkat menjadi 99,55%.
Optimization of MSMEs Clustering in Sampang District Using K-Medoids Method and Silhouette Coefficient Method Firmansyah, Muhammad Iqbal; Kustiyahningsih, Yeni; Rahmanita, Eza; Abidin, Mochammad Syahrul; Satoto, Budi Dwi
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1116

Abstract

Micro, Small, and Medium Enterprises (MSMEs) are an important sector in the economy, playing a significant role in creating jobs and driving local economic growth. This study aims to identify the business development patterns of MSMEs in Sampang District using the K-Medoids method. The background issue raised is the lack of appropriate segmentation for MSMEs, which complicates the efforts of the government and business actors in designing suitable development strategies. The dataset used consists of 1,276 MSME data points with six variables: Type of Business, Number of Workers, Production Capacity, Revenue, Assets, and Business License. The data processing steps include data conversion, one-hot encoding, and normalization to ensure uniformity. Clustering is performed using the Elbow method to determine the optimal number of clusters, with K=4 chosen as the optimal cluster number based on the highest Silhouette Coefficient value of 0.5662 compared to other K values. The Silhouette Coefficient values for K=2 are 0.3711, K=5 is 0.5389, K=7 is 0.5201, and K=9 is 0.4737. The clustering results show that this cluster encompasses various types of services, trade, to food and beverages sectors. This segmentation can support data-driven decision-making at the village level. Although this research shows promising results, it is recommended to expand the quantity and variety of data and consider external factors affecting MSME performance. Thus, this study makes a valuable contribution to understanding the business characteristics of MSMEs in Sampang District.
IMPLEMENTASI TEKNIK WEB SCRAPING UNTUK PENGUMPULAN DATA LAPORAN KEUANGAN PERUSAHAAN DI BURSA EFEK INDONESIA (IDX) Javier, Najamuddin; Dwi Satoto, Budi; Dwi Putra Negara, Yudha
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.13070

Abstract

Dalam era digital, pengumpulan data laporan keuangan perusahaan sangat penting bagi analis dan investor, khususnya para investor saham Indonesia. Sebab Investasi saham di Indonesia selalu mengalami peningkatan pada jumlah investornya. Namun, pengumpulan data secara manual seringkali memakan waktu, tenaga, dan berisiko kesalahan. Penelitian ini bertujuan untuk menggunakan metode Web Scraping untuk mengotomatisasi pengumpulan data laporan keuangan perusahaan yang terdaftar di Bursa Efek Indonesia (IDX). Dengan menggunakan bahasa pemrograman Python dan pustaka Selenium, penelitian ini mengembangkan metode scraping untuk mengekstrak data secara efisien, menyimpannya dalam format terstruktur, dan memastikan akurasi data. Dalam 10 kali pengujian dari 2 jaringan yang berbeda, hasilnya menunjukkan bahwa scraping web dapat meningkatkan efisiensi pengumpulan data, memungkinkan akses data yang lebih besar dalam waktu singkat, serta menghasilkan data yang akurat diangka rata-rata 97% akurasi data yang berhasil dikumpulkan untuk analisis lebih lanjut. Dan juga waktu yang dibutuhkan untuk proses pengumpulan data ini kurang lebih diangka 17 menit, baik dari jaringan via hotspot maupun via ethernet. Penelitian ini juga memberikan kontribusi pada perkembangan teknik pengumpulan data di bidang keuangan.
Decision Support System For Food Menu Selection For Boarding Students Using The Fuzzy AHP Method Faisal Dzikri, Mohammad; Soesilo, Budi; Dwi Satoto, Budi
Dinasti International Journal of Education Management And Social Science Vol. 6 No. 1 (2024): Dinasti International Journal of Education Management and Social Science (Octob
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v6i1.3471

Abstract

This research aims to develop a decision support system specifically designed to help boarding school students choose a balanced food menu by considering nutritional aspects such as carbohydrates, protein and fat. The method used in this research is the Fuzzy Analytical Hierarchy Process (Fuzzy AHP), which aims to give weight to predetermined criteria and determine limits or thresholds for nutritional needs according to the condition of each student. This system is implemented in the form of a web-based application that makes it easier for students to determine food choices that suit their daily calorie and nutritional needs. The research results show that the system developed is able to provide optimal food menu recommendations, based on calculations of nutritional needs processed using the Fuzzy AHP method. Thus, it is hoped that this system can help boarding house students maintain a balanced nutritional intake and improve the quality of their health during the study period. Further implementation of this system is expected to be able to be integrated with users' food preferences to provide more personalized recommendations.
RANCANG BANGUN SISTEM COMPUTER SECURITY INCIDENT RESPONSE TEAM (CSIRT) DISKOMINFO KABUPATEN BANGKALAN MENGGUNAKAN METODE WATERFALL Amin Abdillah; Yasid, Achmad; Soesilo, Budi; Satoto, Budi Dwi
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 10 No 1 (2025): APRIL
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v10i1.54532

Abstract

Pesatnya perkembangan teknologi informasi membawa tantangan baru dalam menjaga keamanan siber, khususnya di sektor pemerintahan. Pemerintah Kabupaten Bangkalan melalui Dinas Komunikasi dan Informatika menghadapi kebutuhan mendesak dalam membentuk tim Computer Security Incident Response Team (CSIRT) sebagai langkah strategis menangani ancaman siber. Sistem CSIRT berbasis website dirancang menggunakan metode Waterfall yang terdiri dari lima tahapan: analisis kebutuhan, desain sistem, implementasi, pengujian, dan pemeliharaan. Pada tahap analisis kebutuhan, dikumpulkan informasi mengenai kebutuhan fungsional dan non-fungsional sistem. Desain dilakukan menggunakan Unified Modeling Language (UML) untuk merancang arsitektur sistem. Implementasi memanfaatkan Framework Laravel untuk aplikasi web dan MySQL sebagai basis data guna mengelola informasi insiden secara efisien. Pengujian dilakukan melalui User Acceptance Testing (UAT) yang mengacu pada standar ISO/IEC 9126 untuk mengukur kualitas sistem, pengujian yang dilakukan mencakup aspek functionality, reliability, efficiency, usability, maintainability, dan portability. Hasil UAT menunjukkan aplikasi mendapatkan penilaian sangat baik pada seluruh aspek. Functionality memperoleh nilai sebesar 91,3%, reliability 90,3%, usability 93,0%, efficiency 91,4%, maintainability 89,1%, dan portability 90,9%. Seluruh aspek masuk ke dalam rentang 80% sampai 100% sehingga termasuk dalam kategori 'Sangat Baik', menunjukkan aplikasi mampu memenuhi kebutuhan pengguna dengan tingkat kepuasan tinggi.
Co-Authors Abidin, Mochammad Syahrul Achmad Yasid Amillia Kartika Sari Amin Abdillah Angkoso, Cucun Very Ari Kusumaningsih Bain Khusnul Khotimah Bain Khusnul Khotimah Bain Khusnul Khotimah Bain Khusnul Khotimah Bain Khusnul Khotimah Bain Khusnul Khotimah Efendi, Moch Rizal Eko Budi Khoendori Eza Rahmanita Faisal Dzikri, Mohammad Fika Hastarita Rachman, Fika Hastarita Firli Irhamni Firmansyah, Muhammad Iqbal Imam Utoyo Iswati Iswati Iswati Iswati, Iswati Javier, Najamuddin Khotimah, Bain Khusnul Khotimah, Bain Khusnul Laili, Moh Linda Rimala Dewi Moh Laili Mukhamad Khoironi Novi Prastiti, Novi Putra, Wahyu Zainur Rima Tri Wahyuningrum Riries Rulaningtyas Sensusiati, Anggraini Dwi Soesilo, Budi Thrisna, Mochamad Adrian Nuradha Yeni Kustiyahningsih Yudha Dwi Putra Negara, Yudha