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PENERAPAN LMS-GOOGLE CLASSROOM DALAM PEMBELAJARAN DARING SELAMA PANDEMI COVID-19 Ommi Alfina
Majalah Ilmiah METHODA Vol. 10 No. 1 (2020): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (374.002 KB) | DOI: 10.46880/methoda.Vol10No1.pp38-46

Abstract

This research aims to (1) find out the results of the implementation of Learning Management System (LMS)-Google Classroom in the online learning process for Informatics Engineering students, Universitas Potensi Utama during the COVID-19 pandemic; (2) learn about students' responses to online learning using LMS-Google Classroom. This research is based on the transformation of the course process from face-to-face learning to remote learning (PJJ) by relying on technology as a substitute for learning media, known as distance learning and online learning. This research was conducted using case study methods. This research was conducted on informatics engineering students in multimedia courses. Sampling techniques using purposive sampling methods. The results showed that the application of LMS-Google Classroom to online learning for Informatics Engineering students during the COVID-19 pandemic had a positive effect, especially in terms of absorption related to understanding lecture materials. Based on the results of student questionnaire calculations, it was obtained that as many as 23% of students find it difficult to attend lectures using LMS-Google Classroom which is reviewed in terms of technological efficiency and material understanding level. Meanwhile, 77% of students are happy and enthusiastic about gaining a new learning experience after using LMS-Google Classroom to participate in multimedia lectures. It can be concluded that, the implementation of LMS-Google Classroom in online learning during the COVID-19 pandemic is one of the solutions that can be used so that the lecture process can continue. However, it is necessary to provide assistance and control over student activities to keep students motivated in following the lecture process in the context of online learning.
PENERAPAN METODE CERTAINTY FACTOR DALAM SISTEM PAKAR UNTUK MENENTUKAN VARIETAS BUAH RAMBUTAN YANG UNGGUL Deny Adhar; Ommi Alfina; Evri Ekadiansyah
Jurnal Informatika Kaputama (JIK) Vol 2 No 2 (2018): Volume 2, Nomor 2, Juli 2018
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v2i2.423

Abstract

Rambutan (Nephelium sp.) merupakan tanaman buah hortikultural yang tergolong ke dalam suku lerak-lerakan atau Sapindacaeae. Tanaman buah tropis ini dalam bahasa inggrisnya disebut Hairy Fruit berasal dari Indonesia. Hingga saat ini telah menyebar luas di daerah yang beriklim tropis seperti Filipina, Malaysia, Thailand, Kamboja, Sri Lanka, India, Karibia, Afrika, negara-negara Amerika Latin dan ditemukan pula di daratan yang mempunyai iklim sub-tropis. Tanaman buah rambutan sengaja dibudidayakan untuk dimanfaatkan buahnya yang mempunyai gizi, zat tepung, sejenis gula yang mudah terlarut dalam air, zat protein dan asam amino, zat lemak, zat enzim-enzim yang esensial dan nonesensial, vitamin dan zat mineral makro, mikro yang menyehatkan, tetapi ada pula masyarakat yang memanfaatkan sebagai pohon pelindung di pekarangan atau sebagai tanaman hias. Dari survey yang telah dilakukan terdapat 22 varietas rambutan baik yang berasal dari galur murni maupun hasil okulasi atau penggabungan dari dua varietas dengan galur yang berbeda. Ciri-ciri yang membedakan setiap varietas rambutan dilihat dari sifat buah (dari daging buah, kandungan air, bentuk, warna kulit, panjang rambut). Selain itu juga buah rambutan mempunyai nilai ekonomis yang tinggi, sehingga sekarang banyak dibudidaya, tetapi masyarakat umum masih banyak yang tidak mengetahui buah rambutan yang mempunyai nilai ekonomis yang tinggi, sehingga dibutuhkan suatu aplikasi sehingga dapat membantu masyarkat untuk mengetahui mana buah rambutan yang mempunyai nilai ekonomis yang tinggi.
PELATIHAN PENGGUNAAN APLIKASI HOTELOGIX MOBILE PMS UNTUK KEPERLUAN MANAJEMEN PADA RAZ HOTEL AND CONVENTION MEDAN Ommi Alfina; ElidaTuti Siregar; Renal Syadani; Frans Ikorasaki; M. Safii
Battuta-Jurnal Pemberdayaan Masyarakat Vol 1 No 3 (2024): Edisi September
Publisher : LPPM Universitas Battuta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Hotel menjadi salah satu jenis bisnis di dalam industri pariwisata yang memiliki potensi keuntungan yang besar. Namun, untuk mengelola bisnis hotel, dibutuhkan manajemen yang baik dan efektif agar bisnis tetap berjalan dengan lancar dan sukses. Penelitian ini difokuskan pada Raz Hotel and Convention yang merupakan hotel dengan kualitas yang baik setara bintang 3 di kota Medan. Tujuan Pelatihan yang akan dilaksanakan pada hotel tersebut adalah memberikan rekomendasi aplikasi manajemen hotel terbaik menggunakan Android yang dapat membantu pengelola hotel dalam mengelola bisnis mereka, salah satunya adalah aplikasi Hotelogix mobile PMS.  Dengan menggunakan aplikasi Hotelogix, pengelola hotel dapat mengelola reservasi, manajemen kamar, serta manajemen keuangan dengan lebih efektif dan efisien. Pelatihan ini juga akan membahas peran dari aplikasi manajemen hotel dan fitur-fitur apa saja yang tersedia di dalam aplikasi tersebut. Dengan adanya aplikasi manajemen hotel terbaik untuk Android, maka hal ini dapat meningkatkan efisiensi dan produktivitas kerja.
Penerapan Internet of Things (IoT) Dasar dalam Sistem Monitoring Lingkungan Sekolah Serta Smart Classroom di SMK PAB 8 Sampali Medan Ommi Alfina; Nita Syahputri; Ananda Pratama; Muhammad Taufiq Rustam; M. Safii; Jamaluddin Jamaluddin
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 2 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methabdi.Vol5No2.pp259-265

Abstract

The development of Internet of Things (IoT) technology has opened up significant opportunities for improving the efficiency and effectiveness of learning systems as well as school environmental management. This community service activity aims to provide basic IoT training and implement an environmental monitoring system and smart classroom at SMK PAB 8 Sampali Medan. The implementation method includes three main stages: (1) socialization of basic IoT concepts and their application in the educational field, (2) practical training for creating simple IoT devices based on temperature, humidity, and light sensors, and (3) implementation of a school environmental monitoring system integrated with a web-based platform and a real-time dashboard. In addition, participants were also introduced to the concept of a smart classroom, where classroom conditions can be monitored and controlled automatically through the developed IoT system. The results of the activity showed an 85% increase in participants' understanding of basic IoT concepts and their ability to independently design environmental monitoring system prototypes. This program has had a positive impact on enhancing digital literacy, technical skills, and school readiness for IoT-based educational digital transformation.
Penilaian Otomatis di SMK TI Budi Agung dengan Certainty Factor Ommi Alfina
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 1 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No1.pp27-34

Abstract

The assessment system at SMK TI Budiagung still relies on conventional methods but has gradually shifted towards AI-based automated assessment. This study aims to analyze the effectiveness of an automated assessment system using the Certainty Factor method in evaluating students objectively and accurately. The research methodology includes interviews with educators and an analysis of the implemented system. The findings indicate that automated assessment enhances efficiency in grading objective answers but faces challenges in evaluating subjective aspects such as creativity and problem-solving skills. Furthermore, the application of the Certainty Factor method allows the system to provide assessments based on calculated certainty levels from available data. The main challenge is ensuring valid and weighted data for more accurate evaluation results. With further development and integration into the learning system, automated assessment is expected to improve academic evaluation quality at SMK TI Budiagung.
Perancangan Aplikasi E-Rekrutmen dan Penempatan Karyawan Menggunakan Metode PSI pada PT. Mutiara Inti Persada Tedi Utomo; Ommi Alfina
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 2 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No2.pp149-158

Abstract

PT. Mutiara Inti Persada is a company operating in the field of labor distribution services with the vision of providing and managing human resources professionally. However, employee recruitment and placement processes that are still carried out manually are often inefficient, lack objectivity, and face challenges in matching applicant profiles with the needs of partner companies. To overcome this problem, this research aims to design a web-based e-recruitment and employee placement application using the Preference Selection Index (PSI) method. The PSI method is applied to provide an objective assessment of applicants based on predetermined criteria, such as work experience, education and skills. The system developed is also equipped with an employee placement feature designed to optimally match applicant profiles with the needs of partner companies. This research uses data collection methods through observation, interviews and documentation to understand company needs, as well as a system development method using the Waterfall model. The research results show that the designed application is able to increase the efficiency of the recruitment process, reduce bias in applicant assessment, and ensure more appropriate employee placement.
Pengembangan Aplikasi Penjualan Kopi dengan Metode FIFO pada CV. Mandiri Kopi Berbasis Android Dwindah Ramadhania; Ommi Alfina
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 2 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No2.pp236-243

Abstract

CV. Mandiri Kopi is a coffee company with a variety of product variants. The company faces a challenge in accurately managing its inventory, particularly ensuring that incoming and outgoing products comply with their expiration dates and arrival dates. This can potentially lead to losses if older products are not promptly sold. To address this issue, this study aims to develop an Android-based coffee sales application that implements the FIFO method in inventory management. The application's main features include recording sales transactions, managing inventory using the FIFO method, recording sales reports, and notification of products approaching expiration. Test results show that the application can help the company manage product inventory more efficiently, reduce the risk of stockpiling, and make it easier for admins to monitor sales reports. Thus, the Android-based coffee sales application using the FIFO method can improve the effectiveness and accuracy of inventory management at CV. Mandiri Kopi.
Klasifikasi Pola Konsumsi Energi Rumah Tangga Menggunakan Algoritma Machine Learning untuk Mendukung Implementasi Smart City Ommi Alfina; M. Safii
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 2 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No2.pp300-306

Abstract

Population growth in urban areas drives a significant increase in household energy consumption. This condition poses a major challenge for the implementation of the smart city concept, particularly in achieving energy efficiency and sustainability. This study aims to classify household energy consumption patterns based on household power consumption data to support intelligent decision-making in urban energy management. The research method includes data preprocessing, data cleaning, and aggregation of daily energy consumption by utilizing key attributes such as Global Active Power, Voltage, Global Intensity, and three sub-metering variables. Consumption pattern categories are formed using the tertile method into three classes: Low, Medium, and High. Several machine learning algorithms are applied to build the classification model, including Logistic Regression, K-Nearest Neighbors (KNN), Random Forest, and Gradient Boosting. The test results show that the Random Forest model with hyperparameter adjustments produces the best performance with an accuracy value of 0.98 and an F1-macro value of 0.98, surpassing other models. These findings indicate that the ensemble learning approach is able to capture the complexity of household energy consumption patterns more effectively than conventional linear models. The contribution of this research lies in the development of a machine learning-based predictive model to support adaptive energy consumption monitoring and control systems in smart city implementations.
Prediksi Jumlah Produksi Kelapa Sawit di Indonesia Menggunakan Algoritma Backpropagation M. Safii; Ommi Alfina
Majalah Ilmiah METHODA Vol. 14 No. 2 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol14No2.pp166-174

Abstract

Indonesia is a country that has advantages in the agricultural sector which has the largest plantation and agricultural areas in ASEAN, one of which is oil palm plantations. Indonesia is one of the largest crude palm oil (CPO) business players in the world. More and more palm oil mills and oil palm land are being converted to oil palm cultivation, because oil palm plantations are more beneficial for farmers and palm oil processors. Palm oil plantations are still trying in several ways to maintain stable market demand, one of which is by increasing palm oil production, because palm oil is the main source of other product derivatives. Palm oil production fluctuates every month, but the ups and downs are caused by many factors, namely climate, rainfall, soil fertility, selling prices, and others. Reduced production has a direct impact on the income of farmers and workers in the sector, which in turn can cause economic instability. Actions are needed to ensure the continuity of this industry, one of which is by making predictions. One prediction technique is the Backpropagation artificial neural network. The prediction model can provide very accurate estimates of palm oil production at the provincial level. By analyzing historical data, this research can identify patterns that can help predict future palm oil production. The urgency lies in the strategic role of palm oil in the Indonesian economy.