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Penentuan Rute Optimal Truk Peti Kemas dengan Algoritma Optimasi Koloni Semut Kambey, Feisy; Mahayana, Dimitri; Rusmin, Pranoto H. Rusmin
Jurnal Teknik Informatika Vol 4, No 1 (2014): Jurnal Teknik Informatika
Publisher : Universitas Sam Ratulangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35793/jti.4.1.2014.8637

Abstrak â€” Peningkatan arus peti kemas sampai saat ini menuntut adanya manajemen pelabuhan peti kemas yang baik. Truk peti kemas adalah bagian penting dari transportasi peti kemas yang perlu dioptimalkan. Makalah ini mengajukan salah satu bentuk optimasi transportasi peti kemas, yaitu dengan penentuan rute optimal truk peti kemas. Ant Colony Optimization merupakan salah satu metode optimasi dengan pendekatan stokastik yang terinspirasi dari proses biologis perilaku sekumpulan semut yang bekerja sama untuk mencari makan. Perjalanan sekumpulan semut yang menyebar mencari makan dari sarangnya menuju sumber makanan kemudian kembali lagi ke sarangnya dan pada akhirnya konvergen ke satu jalur terpendek menjadi inspirasi perancangan algoritma untuk penentuan rute optimal dari truk peti kemas ini. Beberapa algoritma ACO, yaitu Ant System, Elitist Ant System, Rank-Based Ant System, Max-Min Ant System, dan Ant Colony System dikenakan pada sistem penentuan rute truk peti kemas ini untuk menentukan algoritma yang memberikan hasil terbaik.

Kajian Ilmiah dan Deteksi Adiksi Internet dan Media Sosial di Indonesia Menggunakan XGBoost Rismala, Rita; Novamizanti, Ledya; Ramadhani, Kurniawan Nur; Rohmah, Yuyun Siti; Parjuangan, Sabam; Mahayana, Dimitri
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 7, No 1 (2021): Volume 7 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v7i1.43606

Internet dan media sosial telah menjadi kebutuhan pokok manusia untuk mengakses informasi, terutama di masa pandemi COVID-19 saat ini. Hal ini penting untuk dikaji karena berdampak pada perilaku dan kesehatan psikologi seseorang. Berdasarkan sudut pandang filsafat sains, adiksi internet dan media sosial di Indonesia merupakan kenyataan saintifik karena telah memenuhi kriteria falsifikasi dan bisa diuji (testable) secara empiris. Hasil survei terhadap 1980 responden, diperoleh 25,56% responden teradiksi internet dan 20,2% teradiksi media sosial. Penelitian ini juga berhasil membangun model untuk mendeteksi adiksi internet dan media sosial menggunakan XGBoost, dengan F-Measure sebesar 69,23% untuk adiksi internet dan 67,66% Â untuk adiksi media sosial. Oleh karena itu, fenomena adiksi internet dan media sosial ini perlu mendapatkan perhatian khusus agar dapat diantisipasi sejak dini.

Perkembangan Paradigma Metode Klasifikasi Citra Penginderaan Jauh dalam Perspektif Revolusi Sains Thomas Kuhn Ambarwari, Agus; Husni, Emir Mauludi; Mahayana, Dimitri
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.

Quantum Machine Learning Untuk Prediksi Emisi Gas Rumah Kaca dalam Perspektif Filsafat Sains : Quantum Machine Learning for Predicting Greenhouse Gas Emissions from a Philosophy of Science Perspective Hidayat, Wahyu; Surendro, Kridanto; Mahayana, Dimitri; Rosmansyah, Yusep
Jurnal Filsafat Indonesia Vol. 7 No. 2 (2024)
Publisher : Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jfi.v7i2.72236

The climate change issues due to greenhouse gas emissions and the emergence of Quantum Machine Learning technology have sparked various studies in utilizing quantum machine learning (QML) to predict greenhouse gas emissions (GHG). This article aims to illustrate research related to the implementation of QML for GHG emission prediction from the perspective of the philosophy of science, particularly in terms of the scientific revolution from Thomas Kuhn's perspective, research program analysis from Imre Lakatos' perspective, pseudoscience pitfalls, potential biases of injustice, ethical and moral aspects, and their impact on society. The article is structured using a qualitative descriptive method. Reference sources include original articles and review articles from journals collected from the Scopus database with topics related to GHG emission prediction. Based on the review of the articles, it can be outlined that research on QML for GHG emission prediction is a progressive science currently in the phase of intensive exploration and development, where the research paradigm in this area is dominated by logical positivism and pragmatism. However, over time and with the development of the research context, new paradigms may emerge as additions or even replace existing research paradigms. The article also identifies the potential biases of injustice, ethical and moral aspects, and the impact of research in this field on society, recommending five strategies to avoid pseudoscience pitfalls related to research on QML for GHG emission prediction.

Keamanan Data Internet of Things dalam Perspektif Pseudosains Mario Bunge: Internet of Things Data Security in Mario Bunge's Pseudoscience Perspective Pradana, Aditya; Bandung, Yoanes; Mahayana, Dimitri; Rosmansyah, Yusep
Jurnal Filsafat Indonesia Vol. 7 No. 2 (2024)
Publisher : Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jfi.v7i2.72435

Data security is a major concern in the rapidly growing Internet of Things (IoT). This paper investigates the data security aspects of IoT with a pseudoscience perspective inspired by Mario Bunge. The purpose of this research is to understand and address data security challenges in IoT environments. First, researcher identify and evaluate potential vulnerabilities and threats to data, hacking risks, and data encryption needs. Then, researcher analyze commonly used security methods and strategies, including blockchain, fog computing, edge computing, and machine learning. Bunge's pseudoscience approach helps in comprehensively understanding and analyzing IoT data security. The results show a deeper understanding of the data security challenges in IoT, as well as detailed recommendations for risk mitigation. This research highlights the importance of a holistic approach that blends technical and philosophical aspects to address data security issues in IoT. The pseudoscience perspective helps in developing a solid conceptual framework and encourages critical thinking in formulating effective security strategies. In conclusion, this paper makes an important contribution in understanding and addressing the complexities of data security in IoT.

Research on Online Hate Speech Detection from Popper and Kuhn's Philosophical Perspective Cahyana, Rinda; Fitriani, Leni; Setiawan, Yudi; Mahayana, Dimitri
Journal of Digital Literacy and Volunteering Vol. 2 No. 2 (2024): July
Publisher : Puslitbang Akademi Relawan TIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57119/litdig.v2i2.96

The negative impact of spreading hate speech on social media has prompted various parties to intervene. Computer science researchers have conducted experiments to find solutions for automated intervention by applying artificial intelligence, such as machine learning and deep learning. The fulfillment of the theory of truth makes the machine learning paradigm considered by scientists to solve problems. However, the increasing size of social media data has shifted its paradigm to deep learning. Deep learning becomes a new normal science after completing the task of classifying hate speech well on a large amount of data. However, any approach will be an anomaly when it cannot complete the task. The accessibility of research resources makes it easier for researchers to determine the nature of their experiments, whether scientific or pseudo-science.

Kajian Saintifik Fenomena Adiksi Gadget dan Media Sosial di Indonesia Nursikuwagus, Agus; Hikmawati, Erna; Wisesty, Untari Novia; Munggana, Wira; Mahayana, Dimitri
Jurnal Teknologi dan Informasi (JATI) Vol 10 No 1 (2020): Jurnal Teknologi dan Informasi (JATI)
Publisher : Program Studi Sistem Informasi, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

The use of Gadgets and Social Media at this time can not be separated from everyday life. This can lead to gadget and social media addiction. This study aims to answer whether the phenomenon of gadget addiction and social media is a scientific reality or not in Indonesia. Data was collected by a survei of 1601 respondents. Before the questionnaire was distributed, pearson product moment validity and reliability tests were performed with Cronbachâ€™s alpha and the results showed that all questions on the questionnaire were valid and reliable. Based on the survei results, 42.45% of respondents experienced mild addiction, 10.82% of respondents experienced moderate level of addiction, and 0.38% of respondents experienced a very strong addiction to gadget. While the results for social media addiction, 37.50% of respondents experienced mild addiction, 7.85% of respondents experienced moderate level of addiction, and 0.38% of respondents experienced a very strong addiction to social media. In terms of the philosophy of science, Gadgets and Social Media Addiction is said to be science and not pseudo science because it has fulfilled the characteristics of science that is logical, empirical, and falsifiable. So it needs special attention from the community on the existence of gadget and media sosial addiction, so that this addiction can be anticipated and the symptoms can be minimized.

Research on Online Hate Speech Detection from Popper and Kuhn's Philosophical Perspective Cahyana, Rinda; Fitriani, Leni; Setiawan, Yudi; Mahayana, Dimitri
Journal of Digital Literacy and Volunteering Vol. 2 No. 2 (2024): July
Publisher : Puslitbang Akademi Relawan TIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57119/litdig.v2i2.96

The negative impact of spreading hate speech on social media has prompted various parties to intervene. Computer science researchers have conducted experiments to find solutions for automated intervention by applying artificial intelligence, such as machine learning and deep learning. The fulfillment of the theory of truth makes the machine learning paradigm considered by scientists to solve problems. However, the increasing size of social media data has shifted its paradigm to deep learning. Deep learning becomes a new normal science after completing the task of classifying hate speech well on a large amount of data. However, any approach will be an anomaly when it cannot complete the task. The accessibility of research resources makes it easier for researchers to determine the nature of their experiments, whether scientific or pseudo-science.

Analisis Filsafat Ilmu Pengetahuan dalam Transformasi Digital Tridharma Perguruan Tinggi Menuju Smart Campus: An Analysis of the Philosophy of Science in Digital Transformation The Tridharma of Higher Education Towards a Smart Campus Johan, Meliana Christianti; Langi, Armein Z. R.; Mahayana, Dimitri; Abbas, Muhammad Fadhl
Jurnal Filsafat Indonesia Vol. 8 No. 3 (2025)
Publisher : Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jfi.v8i3.96905

The technological revolution has driven the digital transformation of higher education institutions towards a Smart Campus. This process often focuses on technical aspects and neglects philosophical foundations, risking unsustainable implementation. This study analyzes digital transformation in the Tridharma of Higher Education using a philosophy of science approach. It applies interpretive qualitative content analysis to 10 Q1 journal articles from 2021 to 2024. The analysis reveals three fundamental findings. Ontologically, technology is not a neutral tool, but an active agent that shapes academic reality. Epistemologically, there is a dilemma between personalization and standardization of knowledge and the challenge of academic integrity due to Generative AI. Axiologically, operational efficiency can conflict with the humanization of education, as well as innovation and data privacy. This research produces a value-based strategic framework of eight pillars: human-centered design, ethics from the outset, pedagogical accuracy, equity and inclusion, cultural responsiveness, sustainability, governance, and capacity building. This framework guides the implementation of an ethical and sustainable Smart Campus in Indonesia, aligning with the values of Tridharma.

Membangun Kepercayaan terhadap Sistem Pendukung Pendidikan berbasis Kecerdasan Buatan: Sebuah Review Naratif Herdiani, Anisa; Mahayana, Dimitri; Rosmansyah, Yusep
Jurnal Sosioteknologi Vol. 23 No. 1 (2024): MARCH 2024
Publisher : Fakultas Seni Rupa dan Desain ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/sostek.itbj.2024.23.1.6

A primary challenge associated with the implementation of educational support systems is the establishment of student trust in the systems themselves. Trust is a critical factor in the acceptance and use of AI-enabled systems, as it reduces uncertainty and the perception of risk associated with new technology adoption. A literature review of existing studies on trust in AI-based systems is needed to provide a solid foundation for future studies. This research aims to identify gaps in the literature regarding the establishment of user trust in AI-based educational systems by exploring the criteria of trust and the challenges of building trust in AI systems. A narrative review of the literature is conducted to synthesize the findings of selected articles, covering (1) fundamental principles of trust and the process of establishing trust in non-human entities; (2) technical issues relating to explainable AI; (3) the utilization of explainable AI to facilitate decision-making; and (4) the use of AI systems in facilitating educational activities and its influence. This article summarizes trust criteria, including reliance, transparency, affectiveness, integrity, consistency, fairness, accountability, security, and usability. Building trust in AI systems involves addressing technical, ethical, and societal challenges to ensure the responsible and beneficial use of AI for individuals and society.

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