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All Journal UG Journal CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Jurnal Info Sains : Informatika dan Sains Journal International of Lingua and Technology Journal International Journal of Teaching and Learning (INJOTEL) TECHNOVATE Journal of Computer Science Advancements
Alfiah, Agry
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Languange, Linguistic, Communication & Media Mathematics Other

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ANALISIS SIKAP KONSUMEN MARKETPLACE INDONESIA DENGAN MODEL TAM (TECHNOLOGY ACCEPTANCE MODEL) DI KECAMATAN JAYAMEKAR KABUPATEN BANDUNG BARAT SEPANJANG PANDEMI COVID-19 (CASE STUDY TOKOPEDIA) Alfiah, Agry
UG Journal Vol 15, No 10 (2021)
Publisher : Universitas Gunadarma

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Abstract

Tujuan dari riset ini adalah menganalisa sikap konsumen sepanjang pandemi covid-19 yang mempengaruhi pemakaian marketplace Tokopedia dengan Technology Acceptance Model (TAM). Riset ini melakukan survei mengolah informasi. Responden pada riset ini sebanyak 200 ibu rumah tangga di Kecamatan Jayamekar Kabupaten Bandung Barat, yang mengetahui serta pernah melakukan transaksi belanja online marketplace Tokopedia. Untuk menguji informasi Riset, peneliti memakai Partial Least Square (PLS) versi 3.2.3. Hasil riset menunjukkan kalau minat pemakaian marketplace Tokopedia pada saat transaksi online dipengaruhi oleh lima variable. Hal ini dilakukan untuk menjelaskan sikap para pengguna teknologi informasi padapemakaian aplikasi Tokopedia (actual use), kemudahan aplikasi Tokopedia (perceived easy of used), manfaat aplikasi Tokopedia (perceived usefulness), resiko aplikasi Tokopedia (perceived risk), kepercayaan para pengguna aplikasi Tokopedia (trust) yang memiliki pengaruh terhadap marketplace Tokopedia untuk pembelian online
Benefits of Big Data in Supporting Better Educational Decision Making Efendi, Efendi; Alfiah, Agry; Qorib, Fathul; Firdaus, Fadli; Sabri, Sabri
Journal International of Lingua and Technology Vol. 3 No. 2 (2024)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jiltech.v3i2.676

Abstract

Big data plays an increasingly important role in education, offering great potential to improve educational decision making. Big Data collects, stores, and analyzes large amounts of and diverse data at very high speeds. In the educational context, big data collects data from various sources, including school management systems, student academic records, student satisfaction surveys, and online data. Analysis of this data can provide valuable information to decision makers in the education sector to identify relevant trends, patterns and opportunities. This research discusses the great benefits that can be gained from using Big Data in an educational context to support better decision making. Through research on the educational benefits of big data in supporting better decision making, it is hoped that this will provide an excellent opportunity to improve decision making in education. Through careful data analysis, education can become more effective, efficient and relevant to better meet the needs of students and society. The method used in this research is a quantitative method. Researchers conducted a survey using a Google form consisting of 15 statements related to the title of the research. Researchers found that using big data in education provides great opportunities to improve better educational decision making. And supported by careful selection as material for consideration. The limitation of this research is that the researcher only conducted research in schools and the researcher did not conduct research directly in schools but shared a survey link on a Google form containing a statement about the benefits of big data in supporting better educational decision making.
INCREASING STUDENT INTEREST AND MOTIVATION IN LEARNING WITH AUGMENTED REALITY TECHNOLOGY Andy Rachman; Alfiah, Agry; Cindhana Brilliananda, Cindy
International Journal of Teaching and Learning Vol. 2 No. 8 (2024): AUGUST
Publisher : Adisam Publisher

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Abstract

Augmented reality has opened a new window in the digital learning paradigm. Its presence in the realm of education has brought about a number of impressive benefits. In many educational domains, research and development are now centered on the use of augmented reality to boost students' motivation to learn. It has been demonstrated that integrating augmented reality (AR) into the classroom improves student engagement, enriches the educational process, and raises students' interest in learning. Students can have more efficient learning experiences with AR technology, interactive, and realistic learning. For example, the development of a virus learning application using AR technology has helped students learn microorganisms such as viruses better, as well as increasing students' interest in learning in studying human blood circulation. Thus, Students' interest and drive to learn can be heightened by the use of augmented reality (AR) technology in the classroom, which can offer an engaging, dynamic, and realistic learning environment. This shows the great potential of AR technology in creating a more interesting and effective learning environment for students.
Predicted demand for 3 kg LPG gas in each provinces area in Indonesia Novaria, Rachmawati; Alfiah, Agry; Khaddafi, Muammar; Tukino, Tukino; Sudipa, I Gede Iwan
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 01 (2024): Informatika dan Sains , Edition March 2024
Publisher : SEAN Institute

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Abstract

Predicted the demand for 3 kilograms of LPG gas in different provinces of Indonesia is crucial for assuring the provision of energy to households. By employing the Exponential Triple Smoothing (ETS) technique, this study examines demand-influencing factors and consumption patterns. By integrating historical data's levels, trends, and seasonality, ETS enables accurate and timely forecasts. The findings illustrate the predicted outcomes for the ten provinces in Indonesia that have the highest demand for 3 kilograms of LPG gas, as well as the ten provinces that have the lowest demand across all regions. All provinces' MAPE forecasting error testing results utilizing the ETS method are incorporated with an exceptionally high degree of precision, given that the error rate is 5.27%.
Arima Modeling for High-Frequency Channel Response in Equatorial Region Jaya, Indra; Nawawi, Muhammad; Handoko, Lukman; Alfiah, Agry
Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro Vol. 9 No. 2 (2025)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/5yvm4332

Abstract

Indonesia, an archipelagic country located along the equator, is highly vulnerable to natural disasters. At the same time, its geographical conditions require reliable telecommunications to strengthen connectivity across its many islands. One effective solution is the utilization of High-Frequency (HF) communication technology, which enables long-distance communication and supports broadcasting-based telecommunications. This approach can expand available frequency channels, making HF radio communication an important tool for disaster-prone regions like Indonesia. To optimize HF communication, researchers have developed various models of HF channel radio systems, often represented statistically and implemented through channel simulators. Among these approaches, the Auto Regressive Integrated Moving Average (ARIMA) model has been identified as particularly suitable. This is because ARIMA can handle the non-stationary characteristics of time-series data, such as those found in HF channel attenuation measurements. In the modeling process, several ARIMA configurations were tested, including ARIMA (0,1,1), (0,0,5), (1,0,0), (1,0,1), (1,0,2), and (0,0,4). From these options, two models—ARIMA (1,0,0) and ARIMA (1,0,2)—showed the closest fit to the observed data. The final selection was made using the Akaike Information Criterion (AIC), where the ARIMA (1,0,2) model emerged as the best. This model provides the most accurate representation for predicting HF channel attenuation, supporting more reliable telecommunications systems for Indonesia.
Strategic Evaluation of Financial Information Systems through Information Technology Auditing Bakri, Asri Ady; Alfiah, Agry
TECHNOVATE: Journal of Information Technology and Strategic Innovation Management Vol. 1 No. 1 (2024): January 2024
Publisher : PT.KARYA GEMAH RIPAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52432/technovate.1.1.2024.45-55

Abstract

People-based cooperatives encounter digital hurdles to providing effective services. Wiguna Mertha Cooperative needs IT audits to ensure good operations, security, and corporate goals. Enterprise information technology audits are conducted using qualitative and quantitative methodologies in this research. IT audit goal mapping helps firms align business goals with corporate goals, vision, purpose, and IT procedures. PEG aligns IT investments and activities with company strategy, evaluates IT maturity, and prioritizes improvements. Interviews, questionnaires, observations, and documentation were used to analyze 5 cooperative employees' responses. Objective mapping for five corporate goals and maturity level analysis for four COBIT domains: EDM, APO, BAI, and DSS. The results revealed good maturity, with EDM averaging 3.85, APO 3.87, BAI 3.88, and DSS 3.53. Risk management, business resource optimization, IT data up keep, and IT service availability and capacity management are recommended improvements.
Impact of Using Big Data Analisys in Increasing Personalization of Learning Rahmawati, Rahmawati; Nursalim, Nursalim; Alfiah, Agry; Hasyim, Andi; Fawait, Aldi Bastiatul
Journal of Computer Science Advancements Vol. 2 No. 2 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i2.906

Abstract

In today’s digital era, big data analytics has become a very relevant topic to improve learning personalisation as it can collect and analyse very large and complex data. Big data analytics can lead to a more efficient learning system by collecting and analysing huge and complex data. In education, big data analytics can be used to understand students’ learning behaviour, their needs and preferences, so that learning and learning outcomes can be improved. This research is conducted with the aim of using big data analytics to improve learning personalisation. It also aims to find out the challenges of using big data analytics to improve learning personalisation. The method used in this research is quantitative method. This method is a way of collecting numerical data that can be tested. Data is collected through the distribution of questionnaires addressed to students. Furthermore, the data that has been collected from the distribution of the questionnaire, will be accessible in Excel format which can then be processed with SPSS. From the research results, it can be seen that the big data analysis has shown that the use of more detailed and accurate data can help teachers find students’ special needs and improve learning effectiveness. As a result, teachers can create learning strategies that are better suited to students’ needs and improve their learning outcomes. From this study, we can conclude that the use of big data analytics in improving personalisation allows teachers to understand better the individual needs and preferences of students, so that more suitable learning plans can be developed and student engagement can be improved.
Co-Authors Aldi Bastiatul Fawait Fawait Andy Rachman Bakri, Asri Ady Cindhana Brilliananda, Cindy Efendi Efendi Fathul Qorib Firdaus, Fadli Hasyim, Andi I Gede Iwan Sudipa Indra Jaya Lukman Handoko Muammar Khaddafi Muhammad Nawawi Novaria, Rachmawati Nuri Aslami Nursalim Rahmawati, Rahmawati Tukino, Tukino