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All Journal Jurnal Informatika Techno.Com: Jurnal Teknologi Informasi Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Journal of Information Systems Engineering and Business Intelligence Riau Journal of Computer Science Jurnal Teknologi dan Sistem Komputer JUTEI (Jurnal Terapan Teknologi Informasi) Jurnal ULTIMA InfoSys Jurnal ULTIMATICS Jurnal Informatika Jurnal Informatika dan Sistem Informasi Prima Abdika: Jurnal Pengabdian Masyarakat COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Prosiding Seminar Nasional Program Pengabdian Masyarakat Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat Jurnal Algoritma Jurnal Atma Inovasia GIAT: Teknologi untuk Masyarakat International Journal of Information Technology and Computer Science Applications (IJITCSA) SmartComp International Journal of Information Technology and Business JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komtika (Komputasi dan Informatika)
Yuan Lukito
Universitas Kristen Duta Wacana
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Social Sciences Other

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Pelatihan Persiapan Olimpiade Sains Nasional Bidang Komputer Untuk Siswa SMA Pangudi Luhur Yogyakarta Lukito, Yuan; Chrismanto, Antonius Rachmat; Wibowo, Argo; Delima, Rosa; Santosa, Raden Gunawan; Haryono, Nugroho Agus; Wijana, Katon
GIAT : Jurnal Teknologi untuk Masyarakat Vol. 3 No. 1 (2024): Mei 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/giat.v3i1.9166

Abstract

Kompetisi Olimpiade Sains Nasional (OSN) yang rutin diselenggarakan setiap tahunnya membutuhkan persiapan dari siswa-siswa sekolah yang ingin mengikuti kompetisi tersebut.  SMA Pangudi Luhur Yogyakarta ingin mengikuti kompetisi tersebut dengan mengirimkan beberapa siswanya, sehingga membutuhkan pelatihan OSN untuk siswa-siswanya. Tim PKM dari Fakultas Teknologi Informasi bersedia untuk mengadakan pelatihan OSN dengan menyiapkan materi-materi dengan topik algoritma, logika dan aritmatika sesuai dengan silabus OSN.  Pelatihan dilaksanakan selama 14 pertemuan di kampus Universitas Kristen Duta Wacana.  Pelatihan tersebut telah berhasil dilaksanakan dengan baik dan berhasil memenuhi kebutuhan dari pihak sekolah. Pada materi algoritma didapatkan peningkatan rata-rata nilai post-test terhadap rata-rata nilai pre-test, yaitu meningkat dari 57,14 menjadi 97,14. Hasil evaluasi dari pelaksanaan pelatihan ini secara umum sudah baik dan sesuai kebutuhan, walaupun ada beberapa permasalahan seperti jadwal pelatihan yang terpaksa mundur dan tingkat partisipasi siswa yang makin menurun pada beberapa pertemuan akhir.
Building a Mobile Reporting Dashboard System Based on Android Using Web Service Restful for Congregation Data Dody Ivana; Budi Susanto; Yuan Lukito
International Journal of Information Technology and Business Vol. 4 No. 2 (2022): April: International Journal of Information Technology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/ijiteb.422022.01-15

Abstract

The development of the Church is increasingly growing marked by the increasing number of people who attend the church. The church needs to utilize technology in paying attention to spiritual growth in existing congregations. But to do that, there needs to be a system that can see data that is well visualized and can be used by the church. It is not easy to visualize data manually so a practical and portable system is needed. The purpose of this study is as a material consideration in seeing the development of the Church in the Church and improve efficiency without having to use a computer. The process of gathering congregational data comes from the data warehouse of the Indonesian Christian Church Synod in the Central Java Region which is obtained from the Church Information System called SISWA which is local in every church. The interface design process is also carried out using User Centered Design which is centered on the user. This system will be designed using Resrful web Service which has better capabilities than other web services. By building this system, it can facilitate the church in seeing the development of the church and can be taken into consideration in making decisions by the church.
Analisis Kinerja Support Vector Machine dan Moving Averages Convergence Divergence Untuk Saham-Saham Perbankan Indonesia Purnama, Andreas Anditya; Lukito, Yuan; Haryono, Nugroho Agus
Jurnal Komtika (Komputasi dan Informatika) Vol 9 No 1 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v9i1.13459

Abstract

This study discusses the Machine Learning algorithm with technical indicator features in predicting the movement of Indonesian banking sector stocks. Many people seek profit in Indonesian banking stocks because most of them have good fundamentals but have high volatility. The strategy that can be used is the Support Vector Machine (SVM) algorithm with the Moving Averages Convergence Divergence (MACD) technical indicator feature. The SVM algorithm is used because it can process stock price movement data and technical indicators which tend to be complex. This research was conducted with the aim of contributing to the development of a machine learning-based stock prediction model that can be used by academics and financial practitioners. The research stages are collecting historical data on Infobank15 stock movements, data cleaning, training and testing the SVM model, then backtesting. The research methodology includes data processing using Python, training and testing the SVM model, then trading simulation with an initial capital of IDR 100 million. The kernels tested include RBF, Polynomial, and Sigmoid. Model performance is evaluated based on return, win rate, profit ratio, Sharpe ratio, maximum drawdown, risk-reward ratio, and accuracy rate. Historical data of Infobank15 stock is used in this study where the dataset is historical data from 2019-2024 for training and testing the model and historical data from 2024 for backtesting. Based on the experimental results obtained, it can be concluded that the combination of the SVM model and the MACD indicator yields favourable outcomes. The kernel that provides the best overall results is the Polynomial kernel. Penelitian ini membahas penerapan Machine Learning dengan fitur indikator teknikal dalam memprediksi pergerakan saham sektor perbankan Indonesia. Banyak masyarakat mencari keuntungan di saham perbankan Indonesia karena sebagian besar memiliki fundamental yang baik, namun memiliki volatilitas yang tinggi. Strategi yang dapat digunakan yaitu algoritma Support Vector Machine (SVM) dengan fitur indikator teknikal Moving Averages Convergence Divergence (MACD). Algoritma SVM dipakai karena dapat mengolah data-data pergerakan harga saham dan indikator teknikal yang di mana cenderung kompleks. Riset ini dilakukan dengan tujuan berkontribusi pada pengembangan model prediksi saham berbasis Machine Learning yang dapat digunakan oleh akademisi dan praktisi keuangan. Tahapan risetnya yaitu pengumpulan data historis pergerakan saham Infobank15, pembersihan data, pelatihan dan pengujian model SVM, kemudian backtesting. Metodologi risetnya meliputi pengolahan data menggunakan Python, pelatihan dan pengujian model SVM, kemudian simulasi trading. Kernel yang diuji antara lain Radial Basis Function, Polynomial, dan Sigmoid. Kinerja model dievaluasi berdasarkan return, win-rate, profit ratio, sharpe ratio, maximum drawdown, risk-reward ratio, dan accuracy rate. Data historis saham Infobank15 digunakan dalam penelitian ini adalah tahun 2019-2024 untuk pelatihan dan pengujian model serta data historis 2024 untuk backtesting. Dari hasil percobaan yang telah dilakukan, dapat disimpulkan bahwa kombinasi model SVM dan indikator MACD memberikan hasil yang baik. Kernel yang memberikan hasil terbaik secara keseluruhan adalah Polynomial.
Analisis indikator Bollinger Bands, Stochastics dan Relative-Strength Index Untuk Prediksi Pergerakan Gold Futures Berbasis Deep Learning Gabriel, Evander; Lukito, Yuan; Haryono, Nugroho
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2264

Abstract

Prediksi harga Gold Futures menantang karena volatilitas tinggi dan perannya sebagai aset safe-haven yang dipengaruhi kondisi politik serta ekonomi global. Strategi trading yang tepat diperlukan untuk memanfaatkan fluktuasi harga, salah satunya melalui analisis teknikal, fundamental, sentimen, maupun machine learning. Penelitian ini menganalisis efektivitas indikator teknikal Bollinger Bands (BB), Stochastic Oscillator (STOCH), dan Relative Strength Index (RSI) dalam memprediksi harga Gold Futures menggunakan model Deep Learning Long Short-Term Memory (LSTM). Data penelitian berupa ±40.000 harga Gold Futures dari Yahoo Finance, yang dibagi ke dalam data latih, validasi, dan uji dengan metode sliding window (pergeseran 20% dari 0%–60%). Kinerja model dievaluasi melalui Return, Real, Trade, Win-rate, dan Profit-factor menggunakan back testing di Metatrader 5 (leverage 100). Hasil menunjukkan model LSTM dengan fitur BB (periode 20, deviasi 2) menghasilkan return tertinggi rata-rata $100.48, Win-rate 32.53%, dan Profit-factor 2.30. Model terbaik kedua menggunakan kombinasi ketiga indikator dengan return rata-rata $98.033, Win-rate 30.96%, dan Profit-factor 2.12.
Pelatihan Algoritma Pemrograman Untuk Persiapan OSN Informatika Siswa SMA Kolose de Britto Yogyakarta Siang, Jong Jek; Krisnawati, Lucia Dwi; Lukito, Yuan; Chrisantyo , Lukas; Santoso, Raden Gunawan
Prima Abdika: Jurnal Pengabdian Masyarakat Vol. 5 No. 4 (2025): Volume 5 Nomor 4 Tahun 2025 (Desember 2025)
Publisher : Program Studi Pendidikan Guru Sekolah Dasar Universitas Flores Ende

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/abdika.v5i4.6897

Abstract

The Olimpiade Sains Nasional (OSN) in Informatics is a prestigious competition that demands mastery of programming and problem-solving. SMA Kolese de Britto, located in Yogyakarta, faced a challenge in preparing its students for this event due to a limited number of qualified teachers. To address this problem, a community service program in the form of intensive training was implemented through a collaboration with the Fakultas Teknologi Informasi (FTI) UKDW. The program's execution involved five key stages: partner application, coordination and planning, material preparation, training implementation, and evaluation. The training was conducted in 12 sessions, both online and offline, for five students who were pre-selected by the school. The material focused on algorithms, logic, and C++ programming, all highly relevant to past OSN questions. The results showed that one student successfully advanced to the provincial level of the Olimpiade Sains Nasional. Evaluations from both the school and the participating students revealed very high satisfaction, with an average score of 4.5 to 5 on a 5-point scale. This outcome underscores the training's relevance and effectiveness. The students' initial lack of programming knowledge was also successfully overcome. Both the school and the students highly recommend that a similar training program be held again in the following year.
Co-Authors Aditya Wikan Mahastama Antonius R. Chrismanto, Antonius R. Antonius Rachmat Chrismanto Argo Wibowo Astuti, Laksmita Widya Budi Susanto Budi Susanto Chrisantyo , Lukas Daniel Felix Setiawan Dody Ivana Erinda Resha Astanti F. Yogiswara Adinugraha P Gabriel, Evander Ginting Pebrindanov Gloria Virginia Halim Budi Santoso Hartono, Arfiananda Dhede Hizkia Juan Suryanto Hizkia Juan Suryanto, Hizkia Juan Jong Jek Siang Katon Wijana Katon Wijana Katon Wijana Kevin Valiant Kristian Hartono, Renaldi Laurentius Kuncoro Probo Saputra Laurentius Kuncoro Probo Saputra, Laurentius Kuncoro Probo Lucia Dwi Krisnawati Lukas Chrisantyo Lukas Chrisantyo Naibaho, Yosep Parlindungan Nugroho Agus Haryono Nugroho Haryono Pranatantri, Shalommita Purnama, Andreas Anditya Purwadi, Joko Raden Gunawan Santosa Raden Gunawan Santoso Ragil Yoga Irawan Restyandito Rosa Delima Sagara Mahardika Sunaryo Setiawan, Daniel Felix Susilo, Anton Valonia Inge Santoso Verianto, Eko Wahju Satria Wibowo Widi Hapsari Willy Sudiarto Raharjo