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All Journal Jurnal Simetris CCIT (Creative Communication and Innovative Technology) Journal Journal Sensi: Strategic of Education in Information System
Sunandar, Endang
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Credit Risk Prediction Model Using Support Vector Machine with Parameter Optimization in Banks Martono, Aris; Padeli, Padeli; Suhaepi, Muhamad Iip; Santoso, Sugeng; Sunandar, Endang
Journal Sensi: Strategic of Education in Information System Vol 10 No 2 (2024): Journal Sensi
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sensi.v10i2.3463

Abstract

Abstract This research aims to determine the Support Vector Machine (SVM) model with Parameter Optimization in predicting loan worthiness to avoid the risk of bad credit at the Bank. Every bank tries to market financial loan products with very strict requirements. One of the requirements is that the company's financial reports must be healthy if it borrows money from a bank to develop the company's business. In the credit analysis process, there are 19 financial factors that must be measured from dozens or even hundreds of companies proposing financial loans, making it difficult for credit analysts to make decisions about whether these companies are worthy of borrowing or not. Therefore, this research was carried out by comparing the two models, namely SVM with parameter optimization and SVM with parameter optimization and Particle Swarm Optimization (PSO) to select the best model. The research results show that the Area Under Curve (AUC) criteria with validation number of folds (nof) = 10 and nof = 5 are 98.80% and 98.80%, meaning good and stable in the SVM model with parameter optimization. Meanwhile, the SVM model with parameter optimization and PSO has better AUC for validation nof=5 (99%) but for AUC with validation nof=10 (98.30%) it is less good.
Interface Analysis of Bullying Monitoring Systems for Students in Avicena Rajeg School Sunandar, Endang; Fauzan, Jimmy; Sunarya, Po Abas; Rafika, Ageng Setiani
CCIT (Creative Communication and Innovative Technology) Journal Vol 18 No 1 (2025): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v17i1.2840

Abstract

The Emergency Panic Button tool has been developed to provide quick response and accessibility in emergency situations. In this research, we designed and developed an Emergency Panic Button tool using the Arduino ESP32 Devkit V1. This tool allows users to easily trigger emergency signals, send help messages to Telegram, and includes user location information and monitoring of the user's body temperature. The development method includes the integration of electronic components such as buttons, communication modules such as GSM or Wi-Fi, and body temperature sensors. We use Arduino ESP32 Devkit V1 as the main platform and utilize the Telegram API software to send help messages to specified contacts. In this research, we study the theoretical foundations related to emergency systems, Arduino technology, integration with the Telegram API, and user body temperature training. We design and implement tools by developing Arduino programs that allow training panic buttons, sending emergency messages to Telegram, acquiring locations using GPS modules or other methods, as well as training the user's body temperature using temperature sensors.
PERANCANGAN PURWARUPA BIRD REPELLENT DEVICE SEBAGAI OPTIMASI PANEN PADI DI BIDANG PERTANIAN BERBASIS INTERNET OF THINGS Roihan, Ahmad; Hasanudin, Muhaimin; Sunandar, Endang; Pratama, Saria Rizki
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 11, No 1 (2020): JURNAL SIMETRIS VOLUME 11 NO 1 TAHUN 2020
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (677.837 KB) | DOI: 10.24176/simet.v11i1.3752

Abstract

Burung adalah salah satu binatang dari beberapa hama atau hewan perusak yang terdapat pada area persawahan. Luasnya area menjadi perhatian khusus bagi petani. Oleh karena itu petani menggunakan peralatan-peralatan tradisional seperti tali plastik dan orang-orangan sawah untuk mengusir hama tersebut. Tentu saja cara pengusiran ini butuh dukungan dari teknologi terbaru, dikarenakan masih terlihat adanya hama burung yang mengganggu area persawahan, dan akhirnya mengakibatkan produktivitas hasil panen yang tidak optimal. Sebuah metode dengan automasi yang cerdas dibutuhkan sebagai jawaban dari kesulitan yang dialami selama ini oleh para petani. Penerapan sistem pengusir burung secara otomatis dengan cara mendeteksi keberadaan burung serta teknik pengusiran memanfaatkan frekuensi suara yang tidak disukai oleh burung, diharapkan dapat mengusir hama burung. Perancangan purwarupa Bird repellent device bekerja dengan cara memanfaatkan teknik computer vision melalui sensor kamera untuk menangkap objek burung dalam setiap frame, kemudian diproses oleh Raspberry Pi. Setelah objek tertangkap pada kamera maka Raspberry Pi mengaktifkan aktuator berupa frekuensi suara.
Co-Authors Ahmad Roihan, Ahmad Fauzan, Jimmy Jonas, Dendy Martono, Aris Padeli Padeli Po Abas Sunarya Pratama, Saria Rizki Rafika, Ageng Setiani Sohir, Satrio Pramudito Sugeng Santoso Suhaepi, Muhamad Iip