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Peat Soil Temperature Monitoring System With IoT Technology Hatta Zulkifli; Agus Urip Ari Wibowo; Memen Akbar
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1307.762 KB)

Abstract

Peat soil is a soil element that is very susceptible to burning if it is dry and when burned peat will be synonymous with giving rise to dense smoke and giving rise to embers. Prevention has been carried out so far by building a monitoring tower to see the condition of a peatland from a certain height, but because this is done by humans, there will certainly be limitations in monitoring quickly and precisely. By utilizing the development of Internet of Things technology, a solution that can be done by building a system called Silahan Gambut (SILAGA), where this system has been tested on peatlands using the DB18S20 sensor calibrated with a DHT 22 sensor Using Internet of Things technology, it has been successfully monitored in real time the condition of a peatland that has the potential to burn. The results of the sensor data are managed using MongoDB noSQL so that the data obtained is well managed on peat soils at a certain time, condition and region.
Diabetes Risk Prediction using Feature Importance Extreme Gradient Boosting (XGBoost) Kartina Diah Kusuma Wardani; Memen Akbar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 4 (2023): August 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i4.4651

Abstract

Diabetes results from impaired pancreatic function as a producer of insulin and glucagon hormones, which regulate glucose levels in the blood. People with diabetes today are not only experienced adults, but pre-diabetes has been identified since the age of children and adolescents. Early prediction of diabetes can make it easier for doctors and patients to intervene as soon as possible so that the risk of complications can be reduced. One of the uses of medical data from diabetes patients is to produce a model that medical personnel can use to predict and identify diabetes in patients. Various techniques are used to provide the earliest possible prediction of diabetes based on the symptoms experienced by diabetic patients, including the use of machine learning. People can use machine learning to generate models based on historical data from diabetic patients, and predictions are made with the model. In this study, extreme gradient boosting is the machine learning technique for predicting diabetes (xgboost) using XGBoost with importance features. The diabetes dataset used in this study comes from the early stage diabetes risk prediction dataset published by UCI Machine Learning, which has 520 records and 16 attributes. The diabetes prediction model using xgboost is displayed as a tree. The model precision result in this study was 98.71%, for the F1 score was 98.18%. The accuracy obtained based on the best 10 attributes using the importance of the XGBoost feature is 98.72%.
Ekstraksi Data pada Tabel dari Halaman Web Menggunakan Pohon Document Object Model Memen Akbar; Cici Patmala; Dini Nurmalasari
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 5 No 4: November 2016
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

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Abstract

Data on the web page can be available in various formats, such as table. With the growing of web pages, the need to extract data from tables is increasing. Results of the extraction can be used for integration with other web tables or stored in a database. This study discusses the extraction of data from a table on a web page using a Document Object Model (DOM) tree. The initial step of this extraction process is to transform the HTML document into a DOM tree. Then, by applying search methods Depth First Search (DFS), part of the data in the table is extracted and stored in a CSV file. An engine has been developed using Visual Basic. The results show that the engine can automatically extract data from the table that has the following characteristics: the number of rows and columns are not limited, able to handle all of the table orientation layout, and able to handle tables that are merged cells.
Studi Perbandingan Metode SAW, MAUT dan SMART dalam Pemilihan Telepon Seluler untuk Belajar Online : Comparative Study of SAW, MAUT and SMART Methods in Selecting Smartphones for Online Learning Memen Akbar; Elfa Zahara; Aufa Assariy; E. Andika Alfira D
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 1 (2024): MALCOM January 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i1.1073

Abstract

Telepon seluler merupakan perangkat yang sering digunakan untuk pembelajaran online pada masa pandemik covid-19. Banyak pilihan dengan beragam spesifikasi dan harga yang bervariasi membuat masyarakat bingung dalam memilih telepon seluler untuk pembelajaran online. Penerapan metode pendukung keputusan dapat memberikan rekomendasi telepon seluler yang baik untuk pembelajaran online. Pada penelitian ini, dilakukan studi perbandingan dan analisis penerapan metode SAW, MAUT, dan SMART dalam pemilihan telepon seluler untuk pembelajaran online. Kriteria telepon seluler yang digunakan pada penelitian ini dirangkum dari hasil wawancara dan studi literatur. Terdapat 8 kriteria yang digunakan, yakni ukuran kamera, ROM, RAM, processor, jenis layar, garansi, baterai, dan harga. Untuk simulasi perhitungan, diambil data 10 merk telepon seluler dan spesifikasinya berdasarkan kriteria yang telah ditentukan. Hasil simulasi perhitungan ketiga metode kemudian dibandingkan dan dianalisis tingkat kemiripan dan keragaman hasil perhitungan dan peringkat yang direkomendasikan. Berdasarkan hasil analisis yang telah dilakukan, metode SAW dan SMART memiliki tingkat kemiripan hasil perhitungan yang sangat tinggi, yakni 0,9579. Namun, nilai akhir hasil perhitungan metode SAW memiliki jarak yang sangat dekat, yakni 0,0281. Metode MAUT memiliki nilai akhir hasil perhitungan dengan jarak yang paling tinggi, yakni sebesar 0,0711. Peringkat yang direkomendasikan metode SAW dan SMART juga memiliki tingkat kemiripan yang sangat tinggi sebesar 0,9792.
Riau Youth Leader Club: Empowering the Youth of Riau to Implement Community Empowerment Programs: Riau Youth Leader Club: Pemberdayaan Generasi Muda Riau dalam Mengimplementasikan Program Pemberdayaan Masyarakat Putri Madona; M. Ihsan Zul; Hamid Azwar; Made Rahmawaty; Satria Perdana A; Tobi Arfan; Memen Akbar; Yuliska; Fifitri Ali; M. Suhairi
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 3 (2024): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v8i3.19732

Abstract

The data from Badan Pusat Statistik Provinsi Riau in 2020 indicates that Riau Province is poised to benefit from a demographic bonus, with its population predominantly composed of the younger, productive generation. The abundance of young individuals is anticipated to serve as a driving force in enhancing the quality of life for the surrounding communities. The Riau Youth Leader Club (RiyoLC) is an empowerment program aimed at organizing and implementing community empowerment initiatives within Riau. RiyoLC is envisioned as a platform for Riau's youth to exchange ideas, information, and best practices, empowering them to address local challenges and contribute to the advancement of Riau Province. PT Pertamina Hulu Rokan (PT. PHR) has collaborated with Politeknik Caltex Riau to conduct various capacity-building activities, program development support, and implementation assistance for 34 participants from different regencies and cities within PT. PHR WK Rokan's operational area. The program covered topics such as leadership, problem-solving, critical thinking, project management, communication techniques, and presentation skills. As a result, seven community program proposals have been generated, with three of them receiving implementation support from PT PHR