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All Journal JUTIS : Jurnal Teknik Informatika Multidiciplinary Output Research for Actual and International Issue (Morfai Journal)
Danendra, Danica Recca
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Rancang Bangun Alat Pemberi Makan Hewan Peliharaan Pintar Menggunakan Mikrokontroler ESP32 Berbasis Internet Of Things (IoT) dengan Platform Blynk Canady, Richwen; Danendra, Danica Recca; Indrawan, Vincenzo Matalino; Rochadiani, Theresia Herlina
Jutis (Jurnal Teknik Informatika) Vol. 11 No. 2 (2023): Jutis (Jurnal Teknik Informatika)
Publisher : Universitas Islam Syekh Yusuf

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33592/jutis.v11i2.3460

Abstract

Internet of Things (IoT) dapat digunakan untuk menangani berbagai masalah dalam kehidupan sehari-hari manusia, terutama dalam hal-hal yang memerlukan pengawasan konstan. Salah satu contohnya adalah pemberian makan hewan peliharaan. Penelitian ini bertujuan untuk merancang alat pemberi makan hewan peliharaan pintar berbasis Internet of Things menggunakan mikrokontroler ESP32 dan platform Blynk. Perangkat ini menawarkan fitur pemberian makan otomatis dan manual jarak jauh, serta pemantauan real-time makanan yang tersedia melalui platform dan aplikasi mobile Blynk. Studi sebelumnya tentang pemberi makan hewan peliharaan otomatis telah ditinjau dan menjadi dasar untuk penelitian ini. Perangkat yang diusulkan mencakup komponen seperti sensor ultrasonik, load cell, modul Real Time Clock, dan mikrokontroler ESP32. Arsitektur tiga lapisan, termasuk lapisan persepsi, lapisan jaringan dan gateway, dan lapisan aplikasi, diimplementasikan dalam desain sistem. Diagram Fritzing memberikan representasi visual dari hubungan komponen. Metodologi penelitian melibatkan identifikasi masalah, tinjauan literatur, desain perangkat, implementasi, dan pengujian sistem IoT. Pengujian sensor dan komponen dilakukan untuk memastikan akurasi dan efisiensi. Antarmuka aplikasi mobile dikembangkan menggunakan platform Blynk, memungkinkan pengguna memantau dan mengontrol pemberi makan pintar secara jarak jauh. Secara keseluruhan, perangkat pemberi makan hewan peliharaan pintar menunjukkan kinerja yang dapat diandalkan dan berhasil mengatasi tantangan yang terkait dengan pemberian makan hewan peliharaan.
ANALYSIS AND PREDICTION OF HEALTH INSURANCE PREMIUM VALUE USING MACHINE LEARNING ALGORITHM Danendra, Danica Recca; Firizqi, Januponsa Dio
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 5 No. 2 (2025): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/morfai.v5i2.2775

Abstract

Rising healthcare costs and administrative complexity in the health insurance sector underscore the need for an efficient predictive model to anticipate insurance premium prices. The study explores Machine Learning (ML) techniques to predict the value of health insurance premiums. Also, it aims to provide further insights to stakeholders to create strategies in premium pricing and risk management. This study uses the Kaggle.com datasets and a boosting regression algorithm to compare the accuracy and metric evaluation results in predicting the value of insurance premiums. Feature engineering techniques are applied to improve model performance, reduce over-fitting, and interpret the model to ensure the inclusion of relevant predictors by studying the strengths and limitations of each technique. They overcome this through feature selection, model interpret-ability, scalability, and generalization. Through this comprehensive review, the results of this study aim to provide valuable insights for practitioners, researchers, and policymakers, as well as facilitate informed decision-making in the context of determining the value of health insurance premiums through the use of ML methodologies.
Co-Authors Canady, Richwen Firizqi, Januponsa Dio Indrawan, Vincenzo Matalino Rochadiani, Theresia Herlina