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All Journal Jurnal Informatika Jurnal Pekommas JURNAL PENGABDIAN KEPADA MASYARAKAT JOIV : International Journal on Informatics Visualization Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Realtech EPI International Journal of Engineering Jurnal Peduli Masyarakat Jurnal Restikom : Riset Teknik Informatika dan Komputer Journal of Electrical Engineering and Computer (JEECOM) JOINTER : Journal of Informatics Engineering Vivabio : Jurnal Pengabdian Multidisiplin Jurnal Pengabdian Kepada Masyarakat Abdi Putra Journal of Computing Theories and Applications Jurnal Pengabdian Masyarakat Tekno
Lanny Sitanayah
Department Of Informatics Engineering, Faculty Of Engineering, Universitas Katolik De La Salle, Manado
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health Social Sciences Other

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Pengembangan Aplikasi Online Logistik Internal Sentrum Agraris Lotta Lohonauman, Charlie A. P.; Sitanayah, Lanny; Sanger, Junaidy B.; Rahardiyan, Dino; Moko, Emma M.; Kawatak, Steven Y.
Jurnal Pengabdian kepada Masyarakat TEKNO (JAM-TEKNO) Vol 6 No 1 (2025): Juni 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/jamtekno.v6i1.6512

Abstract

Technological developments are currently felt in various fields, ranging from education to industry, and even agriculture. Logistics is a knowledge that is devoted to all activities in a place where all these activities are related to the process of selling, requisitioning goods, moving goods, transportation of goods, management, and storage of goods/products. Sentrum Agraris Lotta is a foundation operating in the agricultural sector, which currently has 5 groups of farmers, each consisting of 15 people. Increasing production results and demand for incoming and outgoing goods have led Sentrum Agraris Lotta, especially the warehouse department, to collect logistical data. Sentrum Agraris Lotta needs an application that can improve performance and make it easier for the warehouse to carry out the process of managing logistics data (management and storage of goods/products) made online with a web platform, so that it can be accessed from anywhere with different devices. The internal logistics online application was built and socialized to users through training. The training was conducted at Sentrum Agraris Lotta and attended by 10 people, including application users who act as admins, staff, and several people from Sentrum Agraris Lotta’s community. After the training, application users provided feedback in the form of the User Acceptance Test. Based on the results obtained, it can be concluded that the application built can overcome the problems faced by Sentrum Agraris Lotta, namely logistics data collection, reporting, and product data search.
IoT-Based Home Electricity Monitoring and Consumption Forecasting using k-NN Regression for Efficient Energy Management Angdresey, Apriandy; Sitanayah, Lanny; Rumpesak, Zefanya Marieke Philia; Ooi, Jing-Quan
Journal of Computing Theories and Applications Vol. 3 No. 1 (2025): JCTA 3(1) 2025 - in progress
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.13602

Abstract

Electricity has emerged as an essential requirement in modern life. As demand escalates, electricity costs rise, making wastefulness a drain on financial resources. Consequently, forecasting electricity usage can enhance our management of consumption. This study presents an IoT-based monitoring and forecasting system for electricity consumption. The system comprises two NodeMCU micro-controllers, a PZEM-004T sensor for collecting real-time power data, and three relays that regulate the current flow to three distinct electrical appliances. The data gathered is transmitted to a web application utilizing the k-Nearest Neighbor (k-NN) algorithm to forecast future electricity usage based on historical patterns. We evaluated the system's performance using four weeks of electricity consumption data. The results indicated that predictions were most accurate when the user’s daily consumption pattern remained stable, achieving a Mean Absolute Error (MAE) of approximately 1 watt and a Mean Absolute Percentage Error (MAPE) ranging from 1% to 1.7%. Additionally, predictions were notably precise during the early morning hours (3:00 AM to 8:00 AM) when k=6 was employed. This study demonstrates the effectiveness of integrating IoT-based systems with machine learning for real-time energy monitoring and forecasting. Furthermore, it emphasizes the application of data mining techniques within embedded IoT environments, providing valuable insights into the implementation of lightweight machine learning for smart energy systems.
Co-Authors Abraham Abast Aminuyati Anasthasya Banurea Anatje Lihiang Angelia Melani Adrian Anthoni Pulakiang Anthoni R. Pulakiang Apriandy Angdresey Billy Fernando Oentomo Dejan Kalengkongan Dino Rahardiyan Elisabeth Y. Yolasb Emma M Moko Evander Kristalino Fino C. Colling Immanuela Puspasari Saputro Indah Suryanto Jeri Wahyu Utama Johanna Zusye wa Joseph, Hizkia R.M. Junaidy Budi Sanger Junaidy Sanger Kalengkongan, Dejan A. Kawatak, Steven Y. Kumenap, Vivie Deyby Lahama, Artquito Beltsazar Livana Dethris Rawung Lohonauman, Charlie A. P. Micael Liem Michael George Sumampouw Noula J. Mokorimban Ooi, Jing-Quan Pether Romony Phang, Alvaro D. Rahardiyan, Dino Rampengan, Mercy Maggy Franky Rayuni A.F Kansil Romony, Pether V B Rumpesak, Zefanya Marieke Philia Steven Pandelaki Tangka, Ignatius Lucky Henokh Vandri Josua Abram Sampul Vivie D Kumenap Vivie D. Kumenap Vivie Kumenap Vivie Kumenap