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Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : -     EISSN : 25973584     DOI : -
Core Subject : Science,
Computer Science & IT
Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK) merupakan ajang pertemuan ilmiah, sarana diskusi dan publikasi hasil penelitian maupun penerapan teknologi terkini dari para praktisi, peneliti, akademisi dan umum di bidang sistem informasi dan teknologi dalam artian luas.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 472 Documents
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Penerapan Algoritma C4.5 , SVM Dan KNN Untuk Menentukan Rata-Rata Kredit Macet Koperasi Siswanto, Siswanto; Riefky Sungkar; Basuki Hari Prasetyo; M.Anif; Subandi, Subandi; Gunawan Pria Utama; Raden Sutiadi; Buana Suhurdin Putra
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

problem that often occurs is the difficulty in determining the average bad credit spread across 7,823 savings and loan cooperatives in Indonesia. The main problem faced by savings and loan cooperatives is the difficulty in identifying and mitigating credit risks that can cause bad credit. Bad credit not only harms cooperatives, but can also disrupt the financial stability of cooperative members. The lack of effective tools to measure and predict credit risk makes cooperatives potentially face unnecessary losses. The aim of this research is to apply the C4.5, SVM, and KNN algorithms in determining the average non-performing loans of savings and loan cooperatives, comparing the results and performance of the three such algorithms in the context of credit risk management, and improve understanding of the use of machine learning techniques in identifying credit risk patterns that may be difficult to detect manually. The application of the C4.5 Algorithm, SVM (Support Vector Machine), and KNN (K-Nearest Neighbors) models in determining the average bad credit in the context of savings and credit cooperatives is carried out by considering the appropriate configuration. This research first collects and preprocesses data which includes credit history, income, length of membership, and other related factors from savings and loan cooperatives. Next, factor analysis and feature selection are carried out to identify the factors that most influence credit risk. The results of the three models are evaluated using various evaluation metrics, such as accuracy, precision, recall, F1-score, and AUC-ROC. The results of this research The results show that the SVM model has the highest performance in predicting credit risk, followed by the C4.5 and KNN algorithms. Careful feature selection and robust model validation are also key components in accurate credit risk assessment. Thus, the results of this research can help cooperatives better manage credit risk and make more informed decisions regarding loan approvals.
STIMATA Rule Adviser: Sistem Rekomendasi Produk e-Commerce Tubagus Mohammad Akhriza; Dwi Safiroh Utsalina
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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A product recommendation system is a necessity for e-commerce applications in order to recommend a series of products related to a product being viewed or previously purchased by the user of the e-commerce application. This article introduces STIMATA Rule Adviser, an interactive recommendation system developed using an association rule mining approach on data streams so that the recommended products are popularity-aware, meaning they are products that are always trending, currently popular, or products that are at risk because they are no longer selling well. This system is equipped with features that allow users to interact with the recommendation list. Users can choose the level of similarity and popularity of products in the recommendation list with the product they are currently viewing. User interactions with the provided recommendations can be visually monitored through the administrator's dashboard.
Klasifikasi Kesegaran Buah Apel Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Android Respaty Namruddin; Mirfan, Mirfan; Irfandi, Irfandi
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Apple fruit is one of the important agricultural commodities in the farming industry. The maturity level of apple fruit is a key factor that affects its quality and shelf life. Manual determination of apple fruit maturity levels is often time-consuming and subjective. Therefore, this research aims to develop an automation system that can classify the maturity levels of apple fruit using the Convolutional Neural Network (CNN) method on the Android platform.Image data of apple fruit at various maturity levels were collected and processed in this study. A CNN model was designed, trained, and optimized using this data to identify the maturity levels of apple fruit from images. The final outcome of this research is a user-friendly Android application that can assist apple farmers in quickly and accurately classifying the maturity levels of apple fruit.The research results indicate that the CNN model can recognize the maturity levels of apple fruit with high accuracy, and the generated Android application provides easy access for users to support apple farming by enhancing efficiency in harvest management and apple processing
Uji Kinerja K-Means Clustering Menggunakan Davies-Bouldin Index Pada Pengelompokan Data Prestasi Siswa Imam T. Umagapi; Basirung Umaternate; Hazriani, Hazriani; Yuyun, Yuyun
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

This research investigates how the values of clustered datasets, both normalized and non-normalized, influence the computation of Euclidean distance in the K-means algorithm. Additionally, it examines the impact of varying cluster quantities, identified through the elbow method, on the evaluation of the Davies-Bouldin Index (DBI). A dataset comprising 174 records undergoes mining using the CRISP-DM (Cross-Industry Standard Process for Data Mining) approach. In the data preparation phase, the min-max algorithm is applied to ensure that attribute values within the dataset are not diminished relative to each other. Concerning the selection of an optimal K value, the elbow method is employed. In this investigation, two K values exhibit significant mean reduction: the fourth and third cluster quantities. The DBI results for 3 clusters show a smaller value of 0.9250 compared to the DBI result for 4 clusters, which is 1.1584. The fundamental principle of evaluating the Davies-Bouldin Index is that a smaller DBI value (approaching zero but not reaching the minimum) indicates a better cluster. These findings contribute to a better understanding of the evaluation techniques involving the elbow method and Davies-Bouldin Index in clustering analysis and offer insights into the relationship between determining cluster quantities and clustering performance.
Penerapan Algoritma C4.5 dalam Mengidentifikasi Karakteristik Pasien Beresiko Diabetes Nuradha, Nuradha; Andi riski ramadani; Hazriani, Hazriani; Yuyun, Yuyun
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Diabetes Mellitus is a disease characterized by an increase in glucose as well as an abnormal rise in blood sugar concentration due to insulin deficiency. The International Diabetes Federation (IDF) reports that in 2021, approximately 540 million people worldwide were affected by diabetes, and this number is expected to increase further if the general public's lack of awareness about symptoms that can trigger the diabetes disease continues. This research aims to implement the C4.5 algorithm in predicting diabetes mellitus based on acquired data. The amount of data used is 300 records, where 90% of the data serves as training data and the remaining 10% is test data. The data consists of 6 attributes: age, gender, hypertension, glucose, heart disease, and BMI (Body Mass Index). Based on Gain calculations, the Glucose attribute becomes the root of the decision tree. The tested data in this study achieved an accuracy rate of 77%, precision of 82%, and recall of 64%.
Penerapan Algoritme Kriptografi RC6 Untuk Mengamankan File Penjualan Dan Gambar Produk Alisan Siswanto, Siswanto; Basuki Hari Prasetyo; M. Anif; Ari Saputro; Subandi; Djati Kusdiarto; Izzah Fadhilah Akmaliah
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Problems that commonly occurred in this period were that the sales data for Alisan products in several stores was falsified and there were quite large differences that did not match the reported data, as well as the large number of fake product images which could damage the image of the original Alisan products. One of the main problems faced in developing e-commerce web applications is the vulnerability of sales data and product images to security threats, such as hacking and data theft. The aim of this research is to create an application that implements the RC6 encryption algorithm to protect web-based Alisan product sales files and product images. This research aims to fill this gap by focusing on the effectiveness of the Rivest Code 6 (RC6) algorithm in protecting critical transactional and visual data in an e-commerce context. In addition, this research examines the impact of RC6 implementation on system performance and compares it with other encryption methods commonly used in web applications. Therefore, this research is expected to provide valuable insights for stakeholders in developing better data security solutions for web-based businesses. Applications are evaluated and planned with user acceptance testing (UAT). The results of application testing showed that the average size of the encryption process was 146,878.6 bytes and the processing time was 3.576291 MS and the average size of the decryption process was 146,854.6 bytes and the processing time was 2.8220591 MS. Test results from 26 UAT respondents, 89.1% agreed that the entire implementation of the RC6 algorithm can be used by Alisan employees to protect sales report files and Alisan product image files easily and safely.
Game Karapan Sapi Nanda Aditya Widhisyah Putra; Andiani, Andiani; Adi Wahyu Pribadi
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Nowadays, many children use Android via mobile phone devices that are played relatively quickly. In fact, it is not uncommon for the activity of playing this game to cause an addiction to continue playing the game, therefore educational alphabet games are beneficial to develop, especially for children. who is already addicted to Android. On the other hand, games function as a means of education. Android addiction often makes players forget many things and focus on the devices that support them in playing the game. One of the things they forget is culture, some of them who are familiar with games using modern technology tend to ignore games that have domestic cultural values.
Optimalisasi Data Rambu Transportasi Darat Berbasis Web Maps Khairil Hamdi; Yuhefizar, Yuhefizar
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Traffic road equipment is an important component in supporting safety and smooth traffic. However, in reality, there is still a lot of road traffic equipment that is damaged and not maintained. This can endanger road users and potentially cause traffic accidents. Web maps are hosted maps usually used to display spatial information visually. Web maps can be created using various technologies, map APIs: Map APIs are a collection of functions that can be used to add maps to a website or application. online mapping software. The method chosen in this research is waterfall because each research step carried out must be sequential and structured to avoid the risk of errors in each sequence of processes carried out, maintenance of road traffic equipment needs to be carried out routinely and periodically to ensure its condition remains good and works fine. Maintenance can be done manually or using technology. Google Maps can be used to create traffic road equipment maps. These maps can be used to monitor the condition of traffic road equipment and to plan maintenance.
Perancangan Aplikasi Media Pembelajaran Seni Tari bagi Siswa Tunarungu berbasis Android Sri Wahyuni; M. Fadhil Muhaimin; A. Muhammad Syafar
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

In its implementation, teaching dance for deaf students at SLB-B YPPLB Makassar, still has obstacles, namely a complicated control process and teaching dance consistency which still uses conventional methods, namely hand clapping. So, in this research, the author makes an application as a forum for learning dance that will be used by students where there is dance introduction material, learning dance consistency exercises through visual media, and receiving feedback from the teacher. Based on questionnaires that have been filled out by students, it can be concluded that the application made is in accordance with the dance learning method and makes it easier for them in the process of learning dance tempo.
Smart Gorden Menggunakan Arduino dan Telegram Rian Sultan Asizan; Akmal Hidayah A; Muhammad Risal; Abdul Latief Arda
Prosiding SISFOTEK Vol 7 No 1 (2023): SISFOTEK VII 2023
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Curtains or curtains are a part of household appliances used to block light and visibility into the house, usually placed on windows and bedroom doors. However, we often forget to open and close windows when traveling, causing the air in the house to become damp and at night visibility can penetrate the glass, attracting thieves. Therefore, this research aims to create smart curtains that can open and close automatically and be controlled remotely via smartphones. This system implementation uses a real-time clock (RTC), button limit switches, and telegrams as inputs, Arduino Uno as processor, and LCD, telegrams, and stepper motors as outputs. With three control systems: manual with buttons, using RTC timer and using Telegram application. Research results show that smart curtain systems based on the Internet of Things (IoT) can work well when the average curtain opening and closing time is 32 seconds. To check timing accuracy based on timer input, there is no delay between input timing. and time on transient system Testing with Telegram input messages showed delivery latency with an average latency of 3.5 seconds.

Page 26 of 48 | Total Record : 472

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