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Konseptualisasi Awal Framework Literasi Etis KAA untuk Siswa SD: Analisis Perspektif Guru dan Orang Tua di SDN 023 Palembang Adelin, Adelin; Hartati, Eka; Everhard Riwurohi , Jan
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 2 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

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Abstract

The rapid development of Coding and Artificial Intelligence (AI) technology has brought new challenges to the world of education, especially related to the importance of instilling ethical literacy from an early age. This study aims to develop an initial framework for AI ethical literacy that is appropriate for elementary school students by analyzing the perspectives of teachers and parents at SDN 023 Palembang. Through an exploratory qualitative approach, this study collected data from in-depth interviews with 5 teachers (3 class teachers and 2 curriculum developers) and 10 parents/guardians of students, as well as a literature study of previous research related to ethical literacy in the use of AI. The research findings reveal several key needs, including: (1) integration of digital ethics materials into the existing curriculum, (2) practical and contextual teacher training, (3) creative learning methods based on stories and games, and (4) active involvement of parents in the learning process. Based on these findings, this study produces a draft framework of 4 pillars that cover aspects of curriculum, teacher training, teaching methods, and collaboration with parents. Although still hypothetical and requiring further validation testing, this framework provides an important foundation for the development of ethical KAA education at the elementary level. The implications of this study are not only relevant for the development of school policies, but also provide theoretical contributions to the discussion on digital literacy for early childhood.   Keywords: framework, artificial intelligence, coding, ethical literacy, elementary education.
Etika Digital dan Teknologi Kunci Kewirausahaan dalam Industri 4.0 Sriyeni, Yesi; Effendi, Hendra; Veronica, Maria; Everhard, Jan
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 2 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

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Abstract

The Fourth Industrial Revolution has transformed the labor market structure through digitalization, automation, and the integration of technologies such as AI, IoT, and big data. One of the most evident impacts is the emergence of the gig economy—a platform-based work model that offers high flexibility but is often accompanied by income uncertainty, limited job security, and minimal legal protection. These conditions give rise to serious ethical dilemmas, particularly regarding the power imbalance between workers and platform companies. This study aims to analyze the application of digital ethics principles in entrepreneurial practices within the gig economy and to identify the emerging ethical challenges. The method used is a literature review focusing on digital entrepreneurship, gig economy characteristics, and the principles of business ethics and algorithmic ethics. The results indicate that fairness, honesty, responsibility, and transparency are fundamental to ethical entrepreneurship in the digital context. Algorithmic transparency, fair compensation, human-centered management approaches, and strong regulatory interventions are essential to ensure worker well-being and protection. These findings highlight the crucial role of digital ethics as a balancing force in building an inclusive and sustainable platform-based work ecosystem.   Keywords— Digital Ethics, Industry 4.0, Gig Economy, Enterpreneurial Ethics
Performance Analysis of Intel Core i7-10610U and Intel Core i7-1265U CPUs Using Benchmarking Method: Analisis Performa CPU Intel Core i7-10610U dan Intel Core i7-1265U Menggunakan Metode Benchmarking Hastomo, Mursid Dwi; Presdianto, Eko; Riwurohi, Jan Everhard
RADIANT: Journal of Applied, Social, and Education Studies Vol. 6 No. 3 (2025): RADIANT: Journal of Applied, Social, and Education Studies
Publisher : Politeknik Assalaam Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52187/rdt.v6i3.336

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Since its introduction, technology that utilizes semiconductor chips to perform data processing and computing or commonly known as microprocessors has experienced various advances and improvements in every aspect. Various innovations have been produced by microprocessor manufacturing companies, namely Intel, to adjust the Central Processing Unit (CPU) to its function. Intel periodically recreates microprocessors that have previously been on the market. The purpose of this study is to determine how significant the difference in performance is between one generation and the next. The launch of CPU products with the same type, but from different generations, shows that each CPU launched at different times always has an increase in performance compared to its predecessor. So, what causes this increase in performance? This question will be answered through testing between the Intel Core i7-10610U and Intel Core i7-1265U Passmark software version. 11. 1 and CPU-Z version. 15. 0. The use of several test tools aims to ensure that the benchmarking results are not biased from only one source and provide a comprehensive picture of the performance of each processor. The benchmarking method is the main measuring tool, while performance comparison is the purpose of the analysis. The tests performed include integer math, compression, floating point math, extended instructions/Streaming SIMD Extensions (SSE), encryption, sorting, Frequency, Single-Thread and Multi-Thread. The results of this test show that the Intel Core i7-1265U has superior performance to the Intel Core i7-10610U. This is because the number of cores, threads, and bandwidth owned by the Intel Core i7-1265U is larger and more, namely 12 threads and 54.1 GB/s for bandwidth, while the Intel Core i7-10610U has 8 threads and 45.8 GB/s bandwidth.
Smart Gardening Berbasis IoT Menggunakan Pengendali Mikro ESP32 Serta Protokol Komunikasi Modbus Yani Prabowo; Tatang Wirawan Wisnuadji; Yan Everhard; Daffa Putra
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 09 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

The internet has now become part of human life both in villages and cities, as long as it is still accessible by cellular communication networks, the internet will be easily accessible, by anyone as long as they have a device, this internet will hereinafter be called the Internet of Things (IoT), this internet in addition to providing Various information can also be used for control systems or control systems. To utilize the Internet, you need a device that has access to the internet network, the ESP32 microcontroller is one of the microcontrollers that can be used to access the internet, with this microcontroller it can also be used as a controller which can receive data from the environment and then process the data according to the embedded program. . It is possible that the microcontroller can be applied in plantations, how to create a minimum system design based on an ESP32 microcontroller with communication capabilities via the internet to be applied in plantations. The method in this research is the design and minimum design of a microcontroller-based system and how to integrate between microcontroller-based IoT devices and how SCADA protocols and technology can be implemented as a reliable system.
Forecasting the Electricity Consumptions of PLN UP3 Cengkareng using Deep Learning Dewi, Novia; Riwurohi, Jan Everhard
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 13 No. 1 (2024): MARET
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i1.1849

Abstract

The consumption of electrical energy for the community every year has increased including the electricity consumption of PLN UP3 Cengkareng customers. Therefore, PLN UP3 Cengkareng must supply electricity to customers in all categories such as Social Category, Household Category, Business Category, Industry Category and Government Category. With customer needs that continue to increase, it is necessary to forecast future electricity needs, so that PLN UP3 Cengkareng can provide the required electrical power. For this reason, it is necessary to predict the electricity demand. This research was conducted to forecast the electricity demand of UP3 Cengkareng by using the Deep Learning Model Long Short-Term Memory (LSTM). The data set used in this study was taken from the PLN UP3 Cengkareng information system, for 10 years, the period from 2012 to 2021. The data used is divided into 2 categories, namely 70% training data and 30% testing data. The results obtained from this prediction are 96,689, with an average neuron value of 32 and an epoch value of 10.
Technical Comparison Between Classical and Quantum Architectures: Quantum Error Challenges and Qubit Stability Bonie Wijaya; Muhammad Fahrizal; Muhrodi; Dhamma Nagara; Yan Everhard
Jurnal Ilmu Komputer Vol 2 No 2 (2024): Jurnal Ilmu Komputer (Edisi Desember 2024)
Publisher : Universitas Pamulang

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Abstract

The age of evolving computational technologies, classical architecture (traditional digital computing) and quantum architecture have emerged as two prominent approaches, offering diverse computational solutions. Classical computing bases its operations on transistors and binary logic gates, while quantum computing leverages the principles of quantum mechanics to perform information processing. This article provides a technical comparison between the two architectures, encompassing essential characteristics, algorithms, processing models, problem-solving capabilities, and challenges faced. In particular, this article highlights the key challenges in quantum computing, namely quantum errors and qubit stability, which significantly impact its reliability and practical implementation. The method used in this research is a literature review study, analyzing various reference sources such as journals, articles, and research reports. With the growing influence of quantum computing in specific sectors, this study is expected to provide a clearer view of the potential and limitations of both architectures, as well as the steps needed to overcome these challenges. The main conclusion of this study is that quantum computing has the potential to revolutionize certain fields, but still faces challenges in terms of stability and error correction.
Implementasi Large Language Model dalam Multi-Domain Psikologi: Tinjauan Literatur Sistematis Ansor, Mohamad Zakaria; Ari Kusuma, Dyah Topan; Riwurohi, Jan Everhard
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 11 (2025): JPTI - November 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1105

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Implementasi large language models (LLM) dalam bidang psikologi menyajikan peluang signifikan untuk meningkatkan diagnosis, pengambilan keputusan klinis, dan penelitian medis. Studi ini melakukan tinjauan literatur sistematis untuk mengeksplorasi penelitian-penelitian terkini mengenai aplikasi LLM dalam bidang psikologi. Dengan mengikuti panduan PRISMA, pencarian literatur dilakukan pada database ScienceDirect. Kriteria inklusi dan eksklusi diterapkan untuk mengidentifikasi studi-studi yang relevan. Data yang diekstraksi mencakup tujuan penelitian, metodologi, bidang aplikasi, jenis data yang digunakan, key findings, dan hasil. Sebanyak 20 studi dimasukkan setelah proses seleksi. Review ini memberikan gambaran komprehensif mengenai aplikasi LLM dalam bidang psikologi, mengidentifikasi peluang, tantangan, dan arah penelitian masa depan yang bermanfaat bagi peneliti, praktisi, dan pembuat kebijakan. Temuan ini menunjukkan bahwa integrasi LLMs dalam praktik psikologi memiliki potensi transformatif untuk meningkatkan kualitas dan aksesibilitas layanan kesehatan mental, namun memerlukan pengembangan framework etis dan regulasi yang komprehensif untuk memastikan implementasi yang aman dan efektif.
ANALISIS KOMPARATIF EFISIENSI DAN KINERJA PROSESOR INTEL XEON 6 DAN AMD EPYC 9004 PADA LINGKUNGAN SERVER VIRTUALISASI Oktora, Andre; K, Irvan; K, Johanes H; Ridwan, Mohamad; Riwurohi, Jan Everhard
Jurnal TIMES Vol 14 No 2 (2025): Jurnal TIMES
Publisher : STMIK TIME

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Abstract

Peningkatan konsumsi daya pada pusat data global menempatkan efisiensi energi (performance-per-watt) sebagai metrik krusial dalam pemilihan prosesor server modern, terutama dalam lingkungan komputasi awan dan virtualisasi berbasis container. Penelitian ini bertujuan untuk menganalisis komparatif kinerja (throughput relatif) dan efisiensi energi () antara prosesor Intel Xeon 6 (arsitektur hybrid) dan AMD EPYC 9004 (arsitektur Zen 4 dengan 96 core) di bawah skenario peningkatan beban kerja container. Studi ini menggunakan pendekatan kuantitatif simulatif berbasis data sekunder, mengimplementasikan model matematis yang mereplikasi degradasi kinerja dan peningkatan konsumsi daya seiring penambahan jumlah container (10 hingga 100). Hasil simulasi menunjukkan bahwa AMD EPYC 9004 unggul secara signifikan. Prosesor ini tidak hanya mempertahankan throughput absolut yang lebih tinggi di seluruh beban kerja ( hingga 463.30 pada 100 container), tetapi juga menunjukkan skalabilitas yang lebih baik (degradasi minimal dari ). Keunggulan kinerja ini menghasilkan Efisiensi Energi () yang superior (mencapai 2.47), yang membuktikan bahwa arsitektur berdensitas inti tinggi mampu mengkompensasi TDP yang sedikit lebih tinggi, memberikan rasio performance-per-watt yang lebih ekonomis. Disimpulkan bahwa AMD EPYC 9004 merupakan pilihan yang lebih optimal bagi pengelola data center yang mencari solusi kinerja tinggi yang stabil dan efisien energi untuk beban kerja virtualisasi yang intensif.
Hybrid Relevance and Sentiment Classification of Indonesian Gold Tweets Using Machine Learning for Market Risk Signal Extraction Kamalia, Antika Zahrotul; Indra, Indra; Wibowo, Arief; Riwurohi, Jan Everhard; Hassan, Shiza
International Journal of Advances in Data and Information Systems Vol. 7 No. 1 (2026): April 2026 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v7i1.1517

Abstract

This study proposes a hybrid relevance–sentiment classification framework to analyze public opinion on physical Antam gold from Indonesian Twitter data and to support exploratory market-risk signal extraction. Tweets were collected during February–November 2025, after preprocessing and text-normalized deduplication, 1,271 unique tweets were retained. The approach combines weak supervision (rule-/lexicon-based silver labels) with TF-IDF-based machine learning in two stages: (1) relevance classification to separate tweets genuinely discussing physical Antam gold from non-relevant contexts (e.g., ANTM stock/capital-market discussions), and (2) two-class sentiment classification (positive vs negative) applied to relevance-filtered tweets. Random Forest achieved the strongest relevance performance (Accuracy = 0.984; macro-F1 = 0.943; 5-fold CV macro-F1 = 0.928 ± 0.033). For sentiment classification, performance was moderate and close across models; the most stable model under cross-validation (Logistic Regression/Naive Bayes) was used for downstream aggregation. Sentiment outputs were aggregated into a monthly sentiment index for descriptive comparison with gold prices; the observed association was weak, indicating that the index is better interpreted as a risk-perception proxy rather than a direct price predictor.
Tinjauan Literatur Sistematis dan Analisis Bibliometrik tentang Isu Etika dan Tata Kelola Kecerdasan Buatan dalam Aplikasi Militer dan Peperangan Bambang Suharjo; Dendi Sunardi; Jan Everhard
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 9 No. 1 (2026): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v9i1.58508

Abstract

The rapid advancement of Artificial Intelligence (AI) in military applications has raised a range of ethical and governance concerns, particularly regarding the use of Autonomous Weapon Systems (AWS) in making lethal decisions without direct human involvement. While these developments offer strategic advantages, they also introduce significant challenges in ensuring accountability, transparency, and compliance with international humanitarian law. This study aims to systematically examine and map the knowledge structure and global research trends related to ethical and governance issues of AI in the military domain. The research adopts a Systematic Literature Review (SLR) approach based on the PRISMA protocol, combined with bibliometric analysis of 469 articles published between 2020 and 2025. The analysis is conducted using VOSviewer to identify thematic clusters, relationships among research topics, and the overall density of scholarly discourse. The findings reveal seven major thematic clusters, including ethical foundations and human-centric approaches, operational systems and decision-making, robotics and autonomous systems, military applications and strategy, governance and regulatory frameworks, ethical principles and accountability, and technical foundations based on machine learning. Network visualization indicates that ethical issues are closely interconnected with governance as the central focus of the discourse, while density analysis shows that the terms “artificial intelligence,” “ethics,” and “application” dominate the research landscape. The study also highlights a gap between normative ethical frameworks and practical implementation in the development and deployment of AI in military contexts. Therefore, stronger governance frameworks are required to ensure accountability and compliance with international regulations. This research contributes by mapping current research directions and identifying future research opportunities, particularly in developing more adaptive and context-aware AI governance approaches.
Co-Authors A. Adriansyah Adelin, Adelin Adi Rizky Pratama Adjie Nugroho Ady Wisma Putra Wardana Agnes Aryasanti Agung Permana Agung Pramono Ajar Rohmanu Angga Rizki Pratama Anindya Putri Pradiptha Ansor, Mohamad Zakaria Antika Zahrotul Kamalia Antika Zahrotul Kamalia Anwar Rifai Ari Kusuma, Dyah Topan Arief Wibowo Arimaya Setyorini Arsanto Narendro Aryasanti, Agnes Ayu Ratna Juwita Bagus T Prabawa Bambang Suharjo Bima Cahya Putra Bonie Wijaya Daffa Putra David Jefri Aruan Dendi Sunardi Despiyan Dwi Budiarto Devit Setiono Dhamma Nagara Dian Anubhakti Diana Juwi Megatarini Dion Setiawan Eka Hartati Farhani Ayu Amalina Fathan Nur Muhtadi Fuad Hasan Hardjianto, Mardi Hari Soetanto Hassan, Shiza Hastomo, Mursid Dwi Hendarin Hendarin Hendra Effendi Hendry Gunawan, Hendry Hidayat Ramadhani I Ketut Sudaryana Ija Sudija Indra Indra Indra Nurman Intan Oka Herdanis Jeremy Jonathan Joko Christian K, Irvan K, Johanes H Kusumaningsih, Dewi Lalang Gumirang M. Anif Maria Veronica Maulana Malik Ibrahim Miftahudin Miftahudin Mohamad Ridwan Mohammad Syafrullah Muh. Syahrir Muhamad Masruin Masad Muhammad Baso Adrian Ibrahim Muhammad Fahrizal Muhammad Faiz Burhanuddin Muhammad Farid Muslich Muhrodi Namin Namin Namora Novia Dewi Nugraha Abdullah, Indra nurhanudin nurhanudin Oktora, Andre Painem Prasasti Alam, Raden Gesit Presdianto, Eko Pudoli, Ahmad Purwanto Purwanto Putri Hayati Raden Bagus Dhana Pradana Adi Ramadhan, Ferry Muhamad Ratna Kusumawardani, Ratna Reza Pahlevi Riyanto Riyanto Roeswidiah, Ririt Rohmanu, Ajar Rusdah Rusdah Ruth Hanseliani Samidi Samidi Samsinar Samsinar Setyo Arief Arachman Siswanto, Siswanto Sriyeni, Yesi Sucipto Basuki Sujono Sujono Sunu Ilham Pradika Suwasti Broto Tatang Wirawan Wisjhnuadji Tatang Wirawan Wisnuadji Tety Sapriani Tobias Duha Triana Anggraini Triana Anggraini Tutik Sri Susilowati Victor Akbar Wahyudin Wahyudin Wisjnuadji TW Wiwin Windihastuti Yani Prabowo Yulianawati Yusuf Hambali