Garuda - Garba Rujukan Digital

Kajian Adiksi Internet dan Adiksi Media Sosial dari Sisi Filsafat Sains Ade Chandra; Ayu Latifah; Hasta Pratama; Okyza Maherdy; Radiant Victor Imbar; Dimitri Mahayana
Jurnal Algoritma Vol 17 No 2 (2020): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.17-2.409

Perkembangan internet sangat mempengaruhi seluruh aspek kehidupan manusia dan sebagian pengguna internet adalah generasi muda. Dengan pengguna internet yang semakin banyak maka masalah adiksi internet dan sosial media menjadi hal yang diangkat oleh Dr. Kimberly Young. Penelitian ini akan meneliti adiksi internet dan sosial media yang akan dianalisis dengan metode deskriptif dan inferensial menggunakan analisis regresi logistik biner. Apakah usia sekolah, jenis pekerjaan dan waktu akses website mempengaruhi kecenderungan seseorang mengalami adiksi internet dan sosial media. Berdasarkan hasil uji statistik dapat disimpulkan bahwa variabel usia sekolah, jenis pekerjaan dan waktu akses website mempengaruhi kecenderungan seseorang mengalami adiksi internet. Sedangkan variabel jenis kelamin dan domisili tidak mempengaruhi kecenderungan seseorang mengalami adiksi internet. Kajian ini membuktikan bahwa adiksi pada internet maupun media sosial itu nyata di Indonesia dan dapat digolongkan sebagai science, bukan pseudo-science. Oleh karenanya perlu adanya perhatian khusus terhadap kasus ini, karena dampak yang ditimbulkan selain memiliki pengaruh buruk pada kesehatan secara fisik, juga dapat menimbulkan gangguan secara psikologis.

Kajian Adiksi Internet dan Adiksi Media Sosial dari Sisi Filsafat Sains Ade Chandra; Ayu Latifah; Hasta Pratama; Okyza Maherdy; Radiant Victor Imbar; Dimitri Mahayana
Jurnal Algoritma Vol 17 No 2 (2020): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.17-2.409

Perkembangan internet sangat mempengaruhi seluruh aspek kehidupan manusia dan sebagian pengguna internet adalah generasi muda. Dengan pengguna internet yang semakin banyak maka masalah adiksi internet dan sosial media menjadi hal yang diangkat oleh Dr. Kimberly Young. Penelitian ini akan meneliti adiksi internet dan sosial media yang akan dianalisis dengan metode deskriptif dan inferensial menggunakan analisis regresi logistik biner. Apakah usia sekolah, jenis pekerjaan dan waktu akses website mempengaruhi kecenderungan seseorang mengalami adiksi internet dan sosial media. Berdasarkan hasil uji statistik dapat disimpulkan bahwa variabel usia sekolah, jenis pekerjaan dan waktu akses website mempengaruhi kecenderungan seseorang mengalami adiksi internet. Sedangkan variabel jenis kelamin dan domisili tidak mempengaruhi kecenderungan seseorang mengalami adiksi internet. Kajian ini membuktikan bahwa adiksi pada internet maupun media sosial itu nyata di Indonesia dan dapat digolongkan sebagai science, bukan pseudo-science. Oleh karenanya perlu adanya perhatian khusus terhadap kasus ini, karena dampak yang ditimbulkan selain memiliki pengaruh buruk pada kesehatan secara fisik, juga dapat menimbulkan gangguan secara psikologis.

Model Penentuan Urgensi Perbaikan Tower Menggunakan Metode MOORA Abdurrasyid Abdurrasyid; Teguh Aryo Nugroho; Didik Fauzi Dakhlan; Arry Akhmad Arman; Dimitri Mahayana
Jurnal Informatika Vol 6, No 1 (2022): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v6i1.5496

Quality control can suppress or reduce the volume of errors and repairs in the future where it can also minimize costs incurred by the company if later there is damage. These activities must be carried out carefully and effectively so that the results obtained are in accordance with the initial objectives. In fact, the implementation of equipment quality control activities in the field at PT. Indonesia Comnets Plus SBU Regional Sumbagsel is still done manually so it is not practical and takes a lot of time. This research is a design science research (DSR) by making a decision support system to help determine the quality of equipment in the field and determine the level of urgency for repairs to the tower that suffered the most damage using the Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) Method. The accuracy results obtained in the implementation of this method are 100%

Kebenaran dalam Perspektif Filsafat Ilmu Pengetahuan dan Implementasi dalam Data Science dan Machine Leaning Mohamad Idris; Riza Ibnu Adam; Yulrio Brianorman; Rinaldi Munir; Dimitri Mahayana
Jurnal Filsafat Indonesia Vol. 5 No. 2 (2022)
Publisher : Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jfi.v5i2.42207

The development of data science or machine learning is experiencing swift growth. This development can become a pseudoscience due to the process of collecting, using algorithms, and processing data that are not per research standards. Machine learning is one of numerous artificial intelligence (AI) techniques that allow a machine to learn independently. Several machine learning implementations include consulting robots, process optimization, credit scoring, security, and services. Data science often uses supervised learning algorithms, which can be trapped intopseudoscience due to errors in the use and processing of data in research. The solution to avoid this is to apply the epistemological concept of Karl Popper, which is related to the falsification ofscience to solve the problem of demarcation. To enhance it, you can also use the principles of the Four Theory of Truth, namely coherence, correspondence, pragmatism, and consensus.

Kajian Adiksi Internet dan Adiksi Media Sosial dari Sisi Filsafat Sains Ade Chandra; Ayu Latifah; Hasta Pratama; Okyza Maherdy; Radiant Victor Imbar; Dimitri Mahayana
Jurnal Algoritma Vol 17 No 2 (2020): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Perkembangan internet sangat mempengaruhi seluruh aspek kehidupan manusia dan sebagian pengguna internet adalah generasi muda. Dengan pengguna internet yang semakin banyak maka masalah adiksi internet dan sosial media menjadi hal yang diangkat oleh Dr. Kimberly Young. Penelitian ini akan meneliti adiksi internet dan sosial media yang akan dianalisis dengan metode deskriptif dan inferensial menggunakan analisis regresi logistik biner. Apakah usia sekolah, jenis pekerjaan dan waktu akses website mempengaruhi kecenderungan seseorang mengalami adiksi internet dan sosial media. Berdasarkan hasil uji statistik dapat disimpulkan bahwa variabel usia sekolah, jenis pekerjaan dan waktu akses website mempengaruhi kecenderungan seseorang mengalami adiksi internet. Sedangkan variabel jenis kelamin dan domisili tidak mempengaruhi kecenderungan seseorang mengalami adiksi internet. Kajian ini membuktikan bahwa adiksi pada internet maupun media sosial itu nyata di Indonesia dan dapat digolongkan sebagai science, bukan pseudo-science. Oleh karenanya perlu adanya perhatian khusus terhadap kasus ini, karena dampak yang ditimbulkan selain memiliki pengaruh buruk pada kesehatan secara fisik, juga dapat menimbulkan gangguan secara psikologis.

Avoiding Machine Learning Becoming Pseudoscience in Biomedical Research Meredita Susanty; Ira Puspasari; Nilam Fitriah; Dimitri Mahayana; Tati Erawati Latifah Rajab; Hasballah Zakaria; Agung Wahyu Setiawan; Rukman Hertadi
Jurnal Informatika Vol 10, No 1 (2023): April 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v10i1.12787

The use of machine learning harbours the promise of more accurate, unbiased future predictions than human beings on their own can ever be capable of. However, because existing data sets are always utilized, these calculations are extrapolations of the past and serve to reproduce prejudices embedded in the data. In turn, machine learning prediction result raises ethical and moral dilemmas. As mirrors of society, algorithms show the status quo, reinforce errors, and are subject to targeted influences – for good and the bad. This phenomenon makes machine learning viewed as pseudoscience. Besides the limitations, injustices, and oracle-like nature of these technologies, there are also questions about the nature of the opportunities and possibilities they offer. This article aims to discuss whether machine learning in biomedical research falls into pseudoscience based on Popper and Kuhn's perspective and four theories of truth using three study cases. The discussion result explains several conditions that must be fulfilled so that machine learning in biomedical does not fall into pseudoscience

Perkembangan Paradigma Metode Klasifikasi Citra Penginderaan Jauh dalam Perspektif Revolusi Sains Thomas Kuhn Agus Ambarwari; Emir Mauludi Husni; Dimitri Mahayana
Jurnal Filsafat Indonesia Vol. 6 No. 3 (2023)
Publisher : Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jfi.v6i3.53865

The rapid improvement of remote sensing technology has given rise to three paradigms of remote sensing image classification methods, namely pixel-based, object-based, and scene-based. This article aims to explain or reveal the development of remote sensing image classification methods and their relationship with Thomas Kuhn's scientific revolution process (pre-paradigm, normal science, anomaly, crisis, and scientific revolution) that occurs in the development of these classification methods. The preparation of this article uses a descriptive qualitative method. Reference sources are journal articles collected from the Scopus database with topics related to classification and remote sensing. Other reference sources are data extracted from review articles. From all the references collected, a literature study is then carried out by analyzing the article's title, abstract, and overall content. After that, the stages of the scientific revolution related to the development of classification methods in remote sensing images were described. Based on the review of the articles, it can be explained that the development of classification methods for remote sensing imagery began in the 1970s when the Landsat satellite was first launched. In this early period, the classification method used was based on pixels or sub-pixels, because the spatial resolution of remote sensing imagery was shallow. As remote sensing technology developed, in the 2000s a new approach was discovered that was more efficient than the pixel-based approach for classifying high-resolution imagery, namely object-based classification methods. Then, with the release of the land use dataset (UC-Merced) in the 2010s, scene-based remote sensing image interpretation began to be used, as pixel- and object-based methods were insufficient to classify correctly.

Title

Found 7 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 7 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 7 Documents
Search