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All Journal TIN: TERAPAN INFORMATIKA NUSANTARA KLIK: Kajian Ilmiah Informatika dan Komputer
Joko Aryanto
Universitas Teknologi Yogyakarta, Yogyakarta
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Aplikasi Belajar Mengenal Rumah Adat Di Indonesia Menggunakan Teknologi Augmented Reality Berbasis Android Helmi Fikry Haikal; Joko Aryanto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1381

Abstract

A traditional house is a cultural heritage in Indonesia that we can get to know and learn about the meaning and function of a traditional house. Knowing or studying a traditional house is the same as studying the cultural heritage of a country, of course Indonesia. This research aims to help learning or introduction to culture or traditional houses in Indonesia by using Augmented Reality Technology and using the markerless method and using the markerbased method which can be used without certain media or objects for markerless, while the markerbased method can use media or image to show a three-dimensional image or plane. With this application, it is hoped that users will be able and easier to learn what is called a traditional house, where the traditional house comes from and the structure of the building and see it in 3 dimensions
Implementasi Metode Waterfall Pada Sistem Informasi Pencarian Lowongan Kerja Berbasis Web Praja Sendi Wardanu; Joko Aryanto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1478

Abstract

In the world of work that continues to develop, access to job vacancy information has become a very important aspect for society. Rapid technological advances have presented new challenges in terms of access to job vacancy information. Many people experience difficulties in finding work, especially due to limited access and costs associated with print media such as newspapers, brochures and magazines which were previously the main source of employment information. This website aims to make it easier for job seekers to get access to various job vacancies online. To achieve this goal, the research uses quantitative research methodology, including literature studies to understand concepts and user needs, observations to observe current job search methods, interviews with potential job seekers to collect relevant data and questionnaires to obtain relevant data from applicants and applicants. public. Meanwhile, in creating the system, the System Development Life Cycle (SDLC) methodology with a waterfall model approach was used, and Unified Modeling Language (UML) was used as a tool to describe the resulting system. The reason for using the waterfall method for developing a website-based information system is to facilitate job seekers' access to job vacancy information. This approach provides a structured framework, enables planning from analysis to implementation, and emphasizes strong documentation to ensure a comprehensive understanding of user needs and an end result that meets expectations. The research results obtained showed that of the 25 respondents, the percentage level of acceptance by the public or applicants for the system being developed was the highest in the first statement, namely 40% agreed, the second was 36% neutral and the third was 40% agreed. Through this website-based information system, research concludes that the reduction in costs and time for people looking for work is very significant and effective. Positive impacts include the potential to reduce unemployment rates and increase inclusivity, provide wider job access opportunities, and create a better world of work
Pemilihan Parameter Crossover Moving Average Adaptif pada BTC/USDT Menggunakan Proximal Policy Optimization Anandava Eka Buana Baskara; Joko Aryanto
TIN: Terapan Informatika Nusantara Vol 6 No 12 (2026): May 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i12.9968

Abstract

Cryptocurrency markets exhibit high volatility, making it challenging to determine the optimal combination of Moving Averages (MA Short and MA Long) for technical indicator-based trading strategies. This study aims to develop an adaptive crossover Moving Average strategy using the Proximal Policy Optimization (PPO) algorithm to evaluate and recommend the most effective MA combinations. Daily cryptocurrency price data from January 1, 2021, to May 15, 2026, comprising a total of 1960 candles, were obtained through an exchange platform API. The data were processed through preprocessing to form market states that include price, volume, and volatility indicators, which were then used as input for the PPO agent during training and strategy evaluation. Test results indicate that the MA 3/50 combination was most frequently selected by PPO based on average probability, while the MA 25/40 combination produced the best financial performance in terms of profit factor, net profit, and win rate. Visualizations of the equity curve, drawdown, and entry and exit points confirm the strategy’s ability to adaptively adjust decisions, capture market trends, and balance risk and profitability. These findings provide practical guidance for selecting adaptive crossover Moving Average parameters, enabling technical indicator-based trading strategies to navigate the complex and rapidly changing dynamics of cryptocurrency markets.
Rekomendasi Aktivitas Pembelajaran Anak Usia Dini Berbasis Q-Learning dan Profil Perkembangan Faiz Ahmad Fauzan; Joko Aryanto
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.9986

Abstract

This study designs a Q-Learning-based recommendation system for early childhood learning activities in a Raudhatul Athfal setting. The system supports teachers in selecting activities aligned with children's developmental profiles, especially physical-motor and cognitive aspects. The recommendation problem is formulated as a Markov Decision Process. The state consists of children's age in months, physical-motor level, cognitive level, previous activity, and previous participation score. The action space contains twelve learning activities, while the reward combines participation, developmental fit, and activity variation. Testing was conducted using scenario-based learning data with five experimental seeds. The results show that Q-Learning achieved an average evaluation reward of 24.667 with a standard deviation of 0.222 from a theoretical scenario bound of 30 points. Ranking evaluation produced Precision@1 of 0.645, Recall@5 of 0.448, and NDCG@5 of 0.641. These results support Q-Learning as a transparent tabular baseline, but they do not prove pedagogical impact. Q-Learning was selected because the state is discrete, the action space is limited, and Q-values are traceable. Since operational data have not been used, the claims are limited to system design, recommendation traceability, and computational evaluation.
Co-Authors Anandava Eka Buana Baskara Faiz Ahmad Fauzan Helmi Fikry Haikal Praja Sendi Wardanu