Article Per Year (5 Year)
p-Index From 2020 - 2025
2.392
P-Index
This Author published in this journals
All Journal Jurnal Pekommas Journal of Sustainable Engineering: Proceedings Series Jurnal Ilmiah Realtech Journal of Electrical Engineering and Computer (JEECOM)
Steven Pandelaki
Program Studi Teknik Informatika, Universitas Katolik De La Salle Manado
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Prediksi Tingkat Kesejahteraan Masyarakat Di Kelurahan North Wangurer Menggunakan Regresi Linear Berganda Wikarsa, Liza; Pandelaki, Steven; Sumajouw, Karen
Jurnal Pekommas Vol 8 No 2 (2023): December 2023
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jpkm.v8i2.5094

Abstract

The level of social welfare in a country can determine the quality and condition of the country itself. North Wangurer sub-district is in Madidir District, Bitung City, with a population of around 750 households. The level of community welfare in this sub-district is solely based on the monthly income obtained from each community which is regarded to be ineffective. Thus, this research aimed to predict the level of community welfare at this sub-district using the multiple linear regression method. It was hoped that this research could provide insights for the North Wangurer sub-district office to make more effective policies/decisions to increase the level of welfare in hope of eradicating poverty and equitably distributing social assistance to the targetted households. There were four independent variables employed in this research such as income, education, occupation, and the number of family members. Meanwhile, the dependent variable was the level of community welfare consisting of Pra-KS, KS-I, KS-II, KS-III, and KS-III Plus as acknowledged by BKKBN. The results revealed that the level of community welfare for the North Wangurer sub-district was in Prosperous Family III Plus (Level 5). Most of the families (98,7%) in this sub-district can meet all basic needs, social psychology and its development, and self-accountability (self-esteem).
Implementasi Algoritma Boyer-Moore Majority Vote pada Sistem Manajemen Inventory Berbasis Internet of Things Lahama, Artquito Beltsazar; Sitanayah, Lanny; Pandelaki, Steven
Jurnal Pekommas Vol 9 No 1 (2024): Juni 2024
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jpkm.v9i1.5105

Abstract

Gold jewelry stores have to deal with various problems involving inventory control and inventory analytics in their day-to-day operations. Many Indonesian gold retailers tackle these problems by using a paperbased recording method. This method is not time efficient and adds more workload into the inventory management processes, such as stocktaking and popular item category classification. Stocktaking gets more difficult as more items are added to the inventory. These added workload and time increase the risk for items to go missing without being immediately documented. This paper proposes an Internet of Things solution that makes inventory stocktake more streamlined by introducing an RFID system with a web application that allows an operator to identify items during a stocktake instantly. In addition, store managers can also find trends in item categories using the Boyer-Moore majority vote algorithm. Our evaluation show that this system can effectively record data items in one scan with an average accuracy of 93.16% for a tray of 5 up to 25 items.
Pengembangan Aplikasi berbasis Android untuk Mengenali Jenis Lesi Kulit Menggunakan Convolutional Neural Network Sengkey, Blessynta Christesa; Pandelaki, Steven; Paseru, Debby
Jurnal Pekommas Vol 9 No 1 (2024): Juni 2024
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jpkm.v9i1.5557

Abstract

Skin lesions are skin abnormalities or disorders in the form of changes, damage, abnormal growth of the skin, such as changes in texture, color, appearance of lumps and spots on the skin. This disease certainly disrupts people's activities and behavior every day because of the reactions it causes, such as sensations of itching, pain, stinging and excessive heat. However, knowledge of the types of skin lesions by the lay public is still lacking and a system is needed that can provide information regarding primary skin lesions. Image processing as part of machine learning can recognize types of primary skin lesions through applications that use Convolutional Neural Network (CNN). This method can perform good feature extraction and classification, so it is very suitable for image detection. Research was carried out on 4 classes of lesions, namely macular, urticarial, popular and vesicular. Based on the test results with the CNN model, it was found that the average accuracy value was 95% with the calculation of values in the macular class with precision 91%, recall 100%, f-1 score 95%, urticaria class with precision 100%, recall 91%, f-1 score 95%, papule class with precision 98%, recall 93%, f-1 score 96% and vesicular class with precision 93%, recall 99%, f-1 score 96%.
Analysis of The Effectiveness of Covid-19 Prevention Measures in Manado City Using the K-means Method Wikarsa, Liza; Pandelaki, Steven; Kurnia, Henrico
Jurnal Pekommas Vol 7 No 1 (2022): June 2022
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jpkm.v7i1.4390

Abstract

Covid-19 is an infectious disease caused by the Coronavirus, spreading quickly and resulting in death. Thus, the government of Manado city recommends all the residents always comply with the   Covid-19 health protocols. The study aimed to investigate the public's response to the effectiveness of the Covid-19 prevention measures imposed by the local government. The prevention measures include using masks, healthy lifestyles, clean lifestyles, and social distancing. K-means clustering was used to determine the level of effectiveness of prevention measures into four clusters, namely very effective (C1), moderately effective (C2), ineffective (C3), and very ineffective (C4). This algorithm yields consistent results despite the difficulty of predicting the K-values or the number of clusters at the beginning of the algorithm. As a result, 58% of respondents consider the prevention measures very effective. They have a high level of Covid-19 awareness and the consequences of violating the health protocols, even though about 10% of the respondents doubted the health protocols in Manado were effective due to the high number of death cases daily. The results can be used as insights for the local government to stop the spread of the Coronavirus in Manado city.
Co-Authors Anthoni Pulakian Dame, Kristian Debby Paseru Hendri Hermawan Adinugraha Henrico Kurnia Kondo, Kristian Y. Kristian Dame Kristian Dame Kristian Kondo Kurnia, Henrico Lahama, Artquito Beltsazar Lanny Sitanayah Micael Liem Michael George Sumampouw Polly, Victori Sengkey, Blessynta Christesa Steven Koloay Sumajouw, Karen Verna Y.P. Bokau Victory Polly Victory Polly Wikarsa, Liza