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Hindriyanto Dwi Purnomo

Universitas Kristen Satya Wacana

Author-ID : 349478

Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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The Strategic Role of Orange Technology in Cultivating Innovation and Well-Being Daniel Yeri Kristiyanto; Hindriyanto Dwi Purnomo; Galih Putra Cesna; Nyree Ani
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 1 (2025): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i1.707

This paper examines the integration of Orange Technology a human-centred paradigm advancing health, happiness, and care (H2O triad) within strategic management frameworks. While strategic management provides the processes of environmental scanning, formulation, implementation, and evaluation, Orange Technology introduces models that emphasize well-being as a strategic asset. Employing an exploratory conceptual design, this study synthesizes interdisciplinary literature across information technology, biomedical engineering, psychology, and cognitive sciences, and maps them against the established stages of strategic management. The analysis highlights the potential for Orange Technology to enrich strategic processes by embedding health and happiness indicators into value propositions, governance systems, and performance evaluation tools. A phenomenon-level gap persists, however, as empirical evidence on governance systems, interdisciplinary adoption, and performance measurement remains scarce. To bridge this divide, two propositions are advanced for embedding an Orange Index into Balanced Scorecard frameworks, and developing a Three-Dimensional Transformational Balanced Scorecard to evaluate human centred innovation. Finally, emerging applications such as TRAIVIS demonstrate how Orange Technology principles extend beyond healthcare into education, combining AI, blockchain, and human centred learning to foster innovation and societal well-being.

FUN LEARNING WITH COMPUTER BAGI SISWA TK KRISTEN 1 SATYA WACANA SALATIGA Hermawan, Anton; Nataliani, Yessica; Dwi Purnomo, Hindriyanto; Christianto, Erwien; Setyanti, Angela Atik; Yulia, Hanita; Krismiyati, Krismiyati; Juliastomo Gundo, Adriyanto; Bayangkariwati Tacoh, Yuliana Tien; Wellem, Theophilus; Hendry, Hendry; Chandra, Dian W.
Midang Vol 3 No 3 (2025): Midang, Oktober 2025
Publisher : Unpad Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/midang.v3i3.63906

ABSTRACT. The rapid development of information technology necessitates adjustments across various sectors, including education, particularly in early childhood education. Introducing technology at an early age is considered a strategic step in preparing children to face the challenges of the digital era. This community service program aimed to introduce technology, specifically computers, to kindergarten students. The program was in-person for students aged 4 to 5 years at TK Kristen 1 Satya Wacana, Salatiga. The training was conducted over multiple sessions, starting with an introduction to computer hardware, then developing mouse-handling skills, and engaging in interactive learning activities through educational games that addressed subjects like letters, numbers, geometric shapes, and different types of vehicles. Evaluation results revealed that the participants showed high enthusiasm throughout the sessions. The students also began to recognize computers as an alternative learning medium and other digital devices commonly used at home, such as smartphones and tablets. These findings suggest that a digital game-based learning approach can effectively enhance both students’ learning motivation and basic computer operation skills at an early age. Keywords: childhood education, computer training, education game, fun learning, gamebased learning.

IMPLEMENTASI Q-LEARNING PADA AGEN YANG MEMAINKAN PERMAINAN SOS Vinsensius Wijaya; Hindriyanto Dwi Purnomo
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.6497

Permainan SOS merupakan permainan kertas dan pensil sederhana yang dimainkan oleh dua pemain dengan tujuan membentuk sebanyak mungkin pola “S-O-S”. Meskipun sederhana, permainan SOS menawarkan tantangan strategis yang dapat dijadikan sebagai platform untuk menguji algoritma pembelajaran mesin. Penelitian ini berfokus pada implementasi algoritma Q-Learning dalam permainan SOS dan menganalisis efektivitas algoritma Q-Learning. Q-Learning, sebuah metode reinforcement learning, digunakan untuk mengajarkan agen melalui pengalaman bermain, dengan Q-table yang diperbarui secara dinamis berdasarkan aksi dan reward yang diterima. Implementasi dilakukan menggunakan bahasa pemrograman Python. Agen Q-Learning dilatih melalui self-play sebanyak 100.000 kali dengan parameter learning rate 0,5, discount factor 0,9, epsilon awal 1,0, epsilon minimum 0,01, dan decay rate epsilon 0,0000005.Eksperimen dilakukan dengan agen Q-Learning yang bermain melawan agen acak pada grid berukuran 3x3 dalam 1.000 permainan. Hasil penelitian menunjukkan bahwa agen Q-Learning secara signifikan mampu meningkatkan persentase kemenangannya seiring dengan bertambahnya episode pelatihan, mencapai rata-rata kemenangan 84,07%. Penelitian ini menyimpulkan bahwa algoritma Q-Learning efektif dalam mengajarkan agen untuk bermain permainan SOS. Temuan ini memperluas aplikasi Q-Learning dalam permainan yang lebih kompleks, meskipun ada beberapa keterbatasan seperti waktu pelatihan yang panjang. Studi lebih lanjut diperlukan untuk mengatasi keterbatasan ini, termasuk integrasi dengan teknik pembelajaran lain seperti deep learning.

PENGENALAN GAME EDUKASI BAGI SISWA TK KRISTEN 1 SATYA WACANA SALATIGA USIA 5-6 TAHUN Anton Hermawan; Yessica Nataliani; Hindriyanto Dwi Purnomo; Erwien Christianto; Angela Atik Setyanti; Hanita Yulia; Krismiyati; Adriyanto Juliastomo Gundo; Theophilus Wellem; Hendry
Jurnal DIMASTIK Vol. 3 No. 2 (2025): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v3i2.12302

Kemajuan teknologi informasi dan komunikasi menuntut adanya adaptasi dalam dunia pendidikan, termasuk pada jenjang pendidikan anak usia dini. Pengenalan teknologi sejak dini menjadi langkah strategis dalam membentuk kesiapan anak menghadapi era digital. Kegiatan pengabdian ini bertujuan untuk mengenalkan teknologi, khususnya komputer, kepada siswa Taman Kanak-kanak (TK) melalui game edukasi berbasis online. Kegiatan dilaksanakan secara luring di TK Kristen 1 Satya Wacana, Salatiga, dengan melibatkan siswa berusia 5–6 tahun. Metode pelatihan dilakukan dalam beberapa sesi, mencakup pengenalan bagian-bagian komputer, penggunaan mouse, serta pelatihan melalui game edukasi seperti pengenalan huruf, angka, bentuk geometri, dan jenis-jenis kendaraan. Hasil evaluasi menunjukkan bahwa siswa menunjukkan antusiasme tinggi selama pelatihan, serta mulai mengenal komputer sebagai media pembelajaran alternatif selain perangkat yang biasa digunakan di rumah seperti handphone dan tablet. Kegiatan ini membuktikan bahwa pendekatan belajar sambil bermain dengan teknologi dapat meningkatkan minat belajar dan keterampilan dasar siswa dalam menggunakan komputer.

Pengembangan Sistem Antrian Web Real-Time Menggunakan CodeIgniter 3 dan WebSocket pada Layanan Kasir Perusahaan Manufaktur Eugene Tanuwijaya; Hindriyanto Dwi Purnomo
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 11 No 1 (2026): JANUARY
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v11i1.7882

Development of a Real-Time Web-Based Queuing System Using CodeIgniter 3 and WebSocket for Cashier Services in a Manufacturing Company. In manufacturing companies, manual queuing systems for administrative services lead to disorder, queue congestion, verbal calls that often go unheard, and the absence of digital records for service evaluation. These problems are particularly evident in the cashier process, which serves many suppliers daily. This study aims to develop a web-based digital queuing system using CodeIgniter 3, WebSocket for real-time updates, and SQL Server integrated with the company's internal systems. Development followed a Hybrid Waterfall–RAD method, combining structured stages with prototyping flexibility. The application consists of three main modules, namely a QR Code-based supplier registration form, an admin dashboard for queue management and monitoring, and a public display. The system was implemented as a case study at a manufacturing company. Testing results show that the system replaced the undocumented manual process with an automated, digitally recorded queuing service, improving cashier service effectiveness, particularly in orderly calling and service accountability toward suppliers.

Analisis faktor penerimaan pengguna terhadap adopsi Artificial Intelligence di Perguruan Tinggi melalui Extended UTAUT2 Jessica Nathania Kho; Hindriyanto Dwi Purnomo; Yessica Nataliani
AITI Vol 23 No 3 (2026)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v23i3.449-464

Artificial Intelligence (AI) has increasingly been used to support scientific writing, offering various benefits while simultaneously raising ethical challenges for higher education institutions. This situation highlights the need for targeted AI integration based on a comprehensive understanding of students’ acceptance and actual use. This study investigates the factors influencing users’ acceptance and actual use of AI in research and scientific writing using the Extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework and Partial Least Squares Structural Equation Modeling (PLS-SEM). Data were collected through a survey of 129 respondents from the Faculty of Information Technology, Satya Wacana Christian University (SWCU). The results indicate that Trust has the strongest influence on Behavioral Intention, followed by Habit and Social Influence. Meanwhile, Habit is the strongest predictor of Use Behavior, whereas Facilitating Conditions and Behavioral Intention do not significantly influence actual use. These findings provide evidence of an Intention–Behavior Gap, suggesting that actual AI use in scientific writing is influenced more strongly by established usage habits than by conscious behavioral intentions alone.

Advancing Startup Ecosystems Through AI-Driven Matchmaking: A Comprehensive Bibliometric Analysis Ninda Lutfiani; Sutarto Wijono; Untung Rahardja; Hindriyanto Dwi Purnomo
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1095

This study investigates the integration of AI in streamlining the alignment process between startups and potential collaborators and partners, particularly in the Indonesian startup ecosystem. The motivation behind this research lies in the gaps and challenges startups face in efficiently connecting with suitable partners or investors. We employed a bibliometric analysis approach. This study sourced data from Scopus, analysing 515 articles and 59,412 citations published from 2018 to 2023. Key findings provide insights into the predominant role of AI technologies, notably machine learning methods like deep learning and data mining, and the significance of recommendation systems that incorporate collaborative filtering. Furthermore, the results underscore the increasing importance of AI as an indispensable tool in the startup landscape, enhancing the efficiency and productivity of collaborations. We assessed publications from several countries, authors, and citations through the bibliometric measures to comprehensively understand the current trends and trajectories. The study concludes by recognising the transformative potential of AI in fostering tighter and more efficient alliances within the startup ecosystem, laying the groundwork for future research into refining AI-driven collaborative processes.

Assessing Employee Performance in the Information Technology Department Using K-Means Clustering: A Case Study Approach Afelia Jozalin Elisa Sakalessy; Hindriyanto Dwi Purnomo
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.653

This research explores the utilization of the K-Means method for evaluating the performance of employees within the Information Technology Department at PT Nusa Halmahera Minerals. The research leverages data from Manage Engine to analyze diverse parameters of employee performance. By employing the K-Means method, employees are categorized based on specific characteristics, facilitating a deeper understanding of each individual's contribution and potential in attaining company objectives. The implementation of the K-Means method aims to offer a more objective perspective on employee performance, empowering companies to make informed decisions in the enhancement and development of their human resources.

Analyzing the Distribution of Health Workers in Semarang City Using K-Means Clustering Method Akhfan Setiyaji; Hindriyanto Dwi Purnomo
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.663

This research employed the K-Means Clustering method to examine the distribution of health workers in Semarang City, emphasizing their pivotal role in the public health infrastructure. Leveraging current data encompassing health worker locations and quantities, the clustering analysis discerned areas exhibiting similar distribution characteristics through the application of the K-Means technique. Quantitative analysis revealed distinct clusters, shedding light on the spatial patterns of health workforce dispersion within Semarang City. The study's quantitative findings furnish valuable insights crucial for formulating more efficacious health policies. By delineating the utility of the K-Means Clustering method in public health planning and providing quantitative evidence of health worker distribution, this research substantially augments geographical comprehension in the examined region.

Air Quality Prediction Using the Support Vector Machine Algorithm Liza Widyarini; Hindriyanto Dwi Purnomo
Journal of Information System and Informatics Vol 6 No 2 (2024): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i2.705

Air quality is an important factor in maintaining the health and well-being of humans and the environment. To anticipate and manage air pollution, air quality prediction has become an important research topic. In this research, researchers propose using the Support Vector Machine (SVM) algorithm to predict air quality. SVM has proven to be an effective method in classification and regression, especially in the context of complex and non-linear data such as air quality data. Researchers utilized historical air quality datasets that include various parameters such as particulates, ozone, nitrogen dioxide and carbon monoxide. Experiments were conducted to compare the performance of SVM with other prediction methods, and the results show that SVM provides accurate and reliable predictions in modeling air quality.

Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Ade Iriani Adi Nugroho Adimas Tristan Nagara Hartono Adriyanto Juliastomo Gundo Afelia Jozalin Elisa Sakalessy Agung Rizky Agung Wibowo Agus Priyadi Ahmad Bayu Yadila Akhfan Setiyaji Andre Kurniawan Andreas A. Sukmana Andrew Aquila Chrisanto Pabendon Andry Ananda Putra Tanggu Mara Andry Tanggu Mara Angela Atik Setiyanti Angela Atik Setyanti Anton Hermawan Anton Hermawan Anwar, Muchamad Taufiq April Firman Daru April Lia Hananto Aris Puji Widodo Aris Tri Joko Harjanto Arseta, Gama Astawa, I Wayan Aswin Dew Atmoko Nugroho Aziz Jihadian Barid Azzahra Nurwanda Bandung Pernama Baun, Sindy Cristine Budhi Kristianto Budi Kristianto Budi Kristianto, Budi C. Leuwol, Sylvie Cahyaningtyas, Christyan Cahyo Dimas K Chandra Halim Chandra, Dian W. Charitas Fibriani Christyan Cahyaningtyas Daniel Kurniawan Daniel Kurniawan Danny Manongga Danu Satria Wiratama Deden Rustiana Dedy Prasetya Kristiadi Dewita Karema Sarajar Didit Budi Nugroho Dody Agung Saputro Dwi Hosanna Bangkalang Edwin Zusrony Eka Purnama Harahap Eko Sediyono Eliansion Ivan Elizabeth Betty Elok Kristiani eremia Silvester Sutoyo Erwien Christianto Eugene Tanuwijaya Evang Mailoa Evangs Mailoa Fajar Rahmat Faudisyah, Alfendio Alif Fauzi Ahmad Muda Feibe Lawalata Florentina Tatrin Kurniati Galih Putra Cesna Giner Maslebu Gladis Tri Enggiel Griya Jitri Pabutungan Gudiato, Candra Hanita Yulia Hanna Arini Parhusip Hari Purwanto Hendra Kusumah Hendra Waskita Hendradito Dwi Aprillian Hendro Steven Tampake Hendry Hendry Hendry Heni Pujiastuti Heru Riza Chakim Hery Santono Hery Santono HR. Wibi Bagas N Hsin Rau Huda, Baenil Hui-Ming Wee Indra Wisnu Wibisono Irdha Yunianto Irwan Sembiring Istiarsi Saptuti Sri Kawuryan Istiarsih Saputri Sri Kawuryan Iwan Setiawan Iwan Setyawan Janinda Puspita Anidya Jessica Nathania Kho Jihot Lumban Gaol Joanito Agili Lopo Jonas, Dendy Joseph Teguh Santoso Kainama, Marchel Devid Kho, Delvian Christoper Krismiyati Kristoko Dwi Hartomo Lea Klarisa Liza Widyarini Lumban Gaol, Jihot Markus Permadi Mau, Stevanus Dwi Istiavan Maya Sari Mellyuga Errol Wicaksono Merryana Lestari Mira Mira Mira Mochamad Heru Riza Chakim Muhammad Aufal Muhammad Rizky Pribadi Nadya Octavianna Lompoliuw Nahak, Yosef Jeffri Silvanus Nahusona, Ferry Nanle, Zeze Nina Rahayu Nina Setiyawati Ninda Lutfiani Ninda Lutfiani Novriest Umbu Walangara Nau Nurrokhman, Nurrokhman Nyree Ani Oliver Sauntos Permadi, Markus Picauly, Irma Amy Pratyaksa Ocsa Nugraha Saian Priatna , Wowon Purwanto Putri, Violita Eka Radius Tanone Ramos Somya Raynaldo Raynaldo Raynaldo Raynaldo, Raynaldo Rendy Hermanto Abraham Richard William Kho Riko Yudistira Robert William Ruhulessin Rufina Rahma Ajeng Setyaningsih Safitri, Adila Sampoerno Santoso, Fian Julio Santoso, Fian Yulio Setyanti, Angela Atik Sri Kasmiyati Sri Kawuryan, Istiarsi Saptuti Sri Sri Yulianto Joko Prasetyo Sugiman, Marcelino Maxwell Sutarto Wijono Syahrul Mu’Arif Wahid Syamsul Arifin Tad Gonsalves Tad Gonsalves Teguh Indra Bayu Teguh Wahyono Theophilus Wellem Tio Nurtino Tirsa Ninia Lina Tri Wahyuningsih Trivena Andriani Tukino, Tukino Tumbade, Marcho Oknivan Tungady, Cornelius Arvel Pratama Untung Rahardja Utama, Deffa Ferdian Alif Valentino Kevin Sitanayah Que Vinsensius Wijaya Wibowo, Mars Caroline Wilujeng Ayu Nawang Sari Winny purbaratri Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yos Richard Beeh Yudistira, Riko Yuli Agung Suprabowo, Gunawan Yuliana Tien Bayangkhariwati Tacoh Yusuf, Natasya Aprila Zakaria, Noor Azura

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