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All Journal International Journal of Electrical and Computer Engineering Techno.Com: Jurnal Teknologi Informasi Teika JSI: Jurnal Sistem Informasi (E-Journal) DINAMIKA DOTCOM TEKNOLOGI INFORMASI Jurnal Informatika Sisforma: Journal of Information Systems ANDHARUPA Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Ilmiah KOMPUTASI Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Petir QARDHUL HASAN: MEDIA PENGABDIAN KEPADA MASYARAKAT J-SAKTI (Jurnal Sains Komputer dan Informatika) Multitek Indonesia : Jurnal Ilmiah Jurnal Riset Informatika Jurnal Teknologi Terapan Antivirus : Jurnal Ilmiah Teknik Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Generation Journal Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Jurnal Abdimas Berdaya : Jurnal Pembelajaran, Pemberdayaan dan Pengabdian Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) International Conference on Industrial Revolution for Polytechnic Education Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Brilliance: Research of Artificial Intelligence MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Software Development Digital Business Intelligence and Computer Engineering Kohesi: Jurnal Sains dan Teknologi Jurnal Informatika Polinema (JIP) Pengabdian Pendidikan Indonesia (PPI) International Journal of English Language and Pedagogy Jurnal Pengabdian Kepada Masyarakat
Usman Nurhasan
Politeknik Negeri Malang
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Pengaruh Penggunaan Platform CodeEasy terhadap Tingkat Pemahaman Mahasiswa dalam Pembelajaran Data Science Python Lumintang, Galur Arasy; Nurhasan, Usman; Lestari, Vivin Ayu
Techno.Com Vol. 24 No. 4 (2025): November 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i4.14642

Abstract

Penelitian https://www.adenomyosisadviceassociation.org/hysterectomy ini bertujuan menguji hipotesis bahwa penggunaan platform pembelajaran mandiri CodeEasy dapat meningkatkan pemahaman mahasiswa pada mata kuliah Data Science Python. CodeEasy merupakan lingkungan belajar asinkron yang menyediakan latihan berbasis kode dengan penilaian otomatis melalui test case, serta umpan balik instan untuk mendorong keterlibatan aktif mahasiswa. Penelitian menggunakan desain one-group pretest–posttest dengan 28 mahasiswa Program Studi Sistem Informasi Bisnis, Politeknik Negeri Malang, semester genap 2024/2025. Analisis Paired Sample t-test menunjukkan peningkatan signifikan skor pemahaman mahasiswa (rata-rata pretest = 32,34%; posttest = 80,38%; ), dengan ukuran efek besar (Cohen’s ), yang mendukung hipotesis penelitian. Hasil ini bersifat indikatif, mengingat desain tanpa kelompok kontrol membatasi kesimpulan kausalitas dan generalisasi. Penelitian ini memberikan bukti awal mengenai efektivitas platform autograding dalam mendukung pembelajaran mandiri pemrograman, dan menyarankan penerapan lebih lanjut dengan desain kontrol serta integrasi Explainable AI (XAI) untuk meningkatkan transparansi evaluasi kode dan personalisasi umpan balik.   Kata Kunci - Autograding, CodeEasy, Data Science Python, Evaluasi Kode, Pembelajaran Mandiri
Analisis Efektivitas Algoritma K-Means Clustering dalam Pengelompokan Siswa Berdasarkan Kemampuan Multidimensi Rafandi, Hanif Naufal; Nurhasan, Usman; Sintiya, Endah Septa
Techno.Com Vol. 24 No. 4 (2025): November 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i4.14653

Abstract

Pengelompokan siswa berbasis data sangat penting untuk mendukung evaluasi yang adil dan menyeluruh, mengingat penilaian potensi selama ini cenderung terfokus pada aspek akademik saja. Penelitian ini mengembangkan sistem rekomendasi regu inti lomba kepramukaan menggunakan algoritma K-Means Clustering, dengan dataset berisi 120 siswa SMP yang dinilai berdasarkan parameter akademik, non-akademik, serta pencapaian SKU dan SKK. Jumlah cluster ditentukan sebanyak 24, sesuai dengan kategori lomba berdasarkan aturan Kwarnas mengenai lomba pramuka tingkat penggalang. Proses pengolahan data meliputi normalisasi dan reduksi dimensi menggunakan Principal Component Analysis (PCA). Evaluasi kualitas clustering dilakukan menggunakan metrik Silhouette Score dan Davies–Bouldin Index (DBI). Hasil terbaik diperoleh pada konfigurasi random_state = 42, n_init = 20, dan max_iter = 300, dengan Silhouette Score sebesar 0,1238 dan DBI sebesar 1,4418. Meskipun kualitas pengelompokan tergolong rendah dengan hasil Silhoutte Score = 0.102 dan DBI = 1.362, sistem ini tetap memberikan solusi objektif bagi pembina dalam memilih siswa berpotensi secara adil dan menyeluruh. Sistem ini juga menjawab keluhan orang tua terkait ketidakterlibatan anak dalam lomba, karena pemilihan dilakukan berdasarkan potensi keseluruhan kategori lomba, bukan hanya satu kategori untuk membentuk tim regu inti pramuka.   Kata kunci: K-Means Clustering, Principal Component Analysis (PCA), Silhouette Score, Davies–Bouldin Index, Regu Inti Pramuka.
Programming Assessment in E-Learning through Rule-Based Automatic Question Generation with Large Language Models Saputro, Halim Teguh; Nurhasan, Usman; Nur Wijayaningrum, Vivi
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.10901

Abstract

This study develops an evaluation instrument for Python programming using a Rule-Based Automatic Question Generation (AQG) system integrated with Large Language Models (LLMs), designed based on the Revised Bloom’s Taxonomy. The urgency of this research stems from the limitations of conventional programming evaluations, which are often time-consuming, less objective, and insufficiently aligned with cognitive learning levels. The proposed method applies assessment terms as rule-based constraints to guide LLM-generated questions, ensuring both pedagogical validity and structural consistency in JSON format. A total of 91 questions were produced, consisting of multiple-choice and coding items, which were then validated by three programming experts and tested on 32 vocational students. The findings indicate that the instrument achieved an overall validity of 77.66% (valid category), with the highest accuracy at the Apply (96.30%) and Create (100%) levels. The reliability test using Cronbach’s Alpha yielded 0.721, showing acceptable internal consistency. Item difficulty analysis revealed a strong dominance of easy questions (97.78%), with only 2.22% classified as moderate and none as difficult. Student performance also showed a fluctuating pattern: high in Remember (94.79%), Understand (95.83%), and Create (95.60%), but lower in Apply (86.11%), Analyze (90.97%), and Evaluate (87.15%). These results confirm that integrating Rule-Based AQG with LLMs can produce valid, reliable, and adaptive evaluation instruments that not only capture basic programming competencies but also partially address higher-order cognitive skills. This research contributes both practically by providing educators with an efficient tool for generating evaluation items and academically by enriching the growing body of literature on AI-assisted assessment in programming education.
Abstract Syntax Tree Model for Minimizing False Negative in Semantic Evaluation of Python Fill-in-the-Blank Nurhasan, Usman; Prasetya, Didik Dwi; Patmanthara, Syaad
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11090

Abstract

This study develops and evaluates an automated assessment model using Abstract Syntax Trees (AST) with a view to overcoming the limitations of string-matching techniques in the assessment of Fill-in-the-Blank (FIB) programming answers. Traditional string-matching techniques have a relatively high False Negative Rate (FNR) of 21.5% within the context of detecting semantic equivalence. The current model uses semantic structural triangulation to ascertain the semantic similarity of student answers. Technical assessment shows that the AST approach markedly reduces the FNR to 4.5%. The model demonstrates high reliability (ϰ = 0.83) with high classification accuracy (F1 Score = 0.966) which attests to its inferential validity. From a pedagogical perspective, system implementation leads to substantial learning gains, evidenced by a large effect size (Cohen’s d = 1.82) and a high normalized gain (Normalized Gain = 0.90). Multiple regression analysis confirms that semantic accuracy is the primary causal factor driving improved student comprehension. Ontologically, while AST is valid as a partial representation, its limitations—particularly tree isomorphism in recursive structures—highlight the need for further exploration of graph isomorphism approaches. Control Flow Graphs (CFG) and Data Flow Graphs (DFG) offer more expressive relational models for capturing control and data dependencies. The model demonstrates functional feasibility with a System Usability Scale (SUS) score of 76.47. Overall, the AST Triangulation Model is validated as pedagogically effective, inferentially robust, and supportive of evaluative transparency. Future research recommends validating the model on more complex tasks and releasing it as open-source to support reproducibility.
Model Otomatisasi Cerdas Berbasis data Spasial untuk Prioritas Perbaikan Jalan Rusak Nurhasan, Usman; Pradibta, Hendra
Jurnal Informatika Polinema Vol. 12 No. 1 (2025): Vol. 12 No. 1 (2025)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i1.8654

Abstract

Kerusakan jalan berdampak signifikan terhadap keselamatan dan efisiensi sosial-ekonomi. Pendekatan manual dalam menentukan prioritas perbaikan seringkali tidak akurat, terutama di wilayah dengan karakteristik spasial kompleks seperti Kabupaten Pasuruan. Penelitian ini mengusulkan sistem rekomendasi cerdas berbasis data spasial menggunakan model hybrid, yang mengintegrasikan metode Simple Additive Weighting (SAW) untuk perankingan dan Random Forest (RF) untuk validasi klasifikasi. Dataset mencakup 100 segmen jalan dengan atribut spasial dan non-spasial. SAW berhasil mengklasifikasikan segmen ke dalam tiga kelas prioritas dengan tingkat konsistensi 92%, yang didukung oleh hasil RF. Model RF juga menunjukkan kinerja baik dengan precision, recall, dan F1-score rata-rata sebesar 0,87, serta mampu mengidentifikasi fitur penting. Integrasi SAW-RF dalam kerangka GIS terbukti efektif meningkatkan efisiensi dan transparansi. Prototipe ini berpotensi untuk direplikasi di daerah lain menggunakan platform open source
Perancangan Sistem Informasi Pengolahan Data Belanja Langsung Berbasis Website Nurhasan, Usman; Tresna, Esa Luh; Cahyana, Yuanita Hendra; Tresna, Tresna; Qori, Elsa Lusiana; Cahyana, Cahyana
Generation Journal Vol 3 No 2 (2019): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.686 KB) | DOI: 10.29407/gj.v3i2.12948

Abstract

Abstrak –Informasi mengenai data progres belanja langsung setiap Satuan Kerja Perangkat Daerah(SKPD) Kota Batu saat ini masih menggunakan sistem yang manual. Untuk setiap SKPD harus mengumpulkan data mengenai progressnya masing-masing kepada bagian monitoring yang nantinya akan dilakukan pemantauan. Sehingga, dalam proses input data dilakukan secara berulang untuk mengetahui sejauh mana progress yang telah dilakukan oleh setiap SKPD Kota Batu. Dari permasalahan tersebut maka dibuat aplikasi Sistem Informasi Data Progres Belanja Langsung berbasis website yang mampu menampilkan data progress setiap SKPD dalam bentuk progress bar. Hasil keluaran dari aplikasi Sistem Informasi Data Progres Belanja Langsung ini akan menampilkan nama SKPD, prosentase progress, waktu input data dan total pagu dalam bentuk progress bar yang memiliki warna berbeda dari setiap SKPD yang telah ditambahkan. Aplikasi ini hanya dapat diakses semua orang yang berada di Bagian Administrasi Perekonomian dan Pembangunan Sekretariat Daerah Kota Batu karena aplikasi ini berbasis website.
Application of Up-Event Applications in Multi Vendor Activity Management Nurhasan, Usman; Mentari, Mustika; Hartati, Kirana; Ningtyas, Noviana
Generation Journal Vol 4 No 2 (2020): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v4i2.14291

Abstract

Event organizer dapat didefinisikan sebagai pengorganisasian sebuah kegiatan yang dikelola secara profesional, sistematis, efisien dan efektif. Kegiatannya meliputi konsep (perencanaan), pelaksanaan hingga pengawasan. Saat ini sistem penyebaran informasi event dilakukan dengan cara mempromosikan eventmelalui website, social media dan juga masih banyak event organizer yang melakukan penjualan tiket event secara offline dengan membuka stand di event lain maupun di daerah tertentu. Pendistribusian tiket dengan cara ini menimbulkan beberapa masalah yaitu terjadinya antrian panjang yang akan menghabiskan banyak waktu dan adanya biaya tambahan untuk mendirikan stand tersebut. Peluang untuk penyebaran informasi event dan penjualan tiket secara online mulai dilirik oleh event organizer sebagai lahan yang menjanjikan karena menyediakan informasi yang akurat serta menghemat waktu dan juga biaya saat promosi. Dari permasalahan tersebut, kami merancang sebuah aplikasi “Up-Event” sistem ini berguna untuk membantu event organizer dalam penjualan tiket event. Sistem ini selain berbasis website juga berbasis android. Di sistem ini dilengkapi fitur absensi peserta event menggunakan teknologi QR Code. Selain untuk mengurangi penggunaan kertas yang terlalu banyak dan antrian yang panjang saat absensi peserta, QR Code juga menjamin keamanan event karena dapat diketahui keaslian tiket yang digunakan sebagai syarat masuk peserta kedalam tempat acara.
Hybrid project learning and peer teaching as learning strategies for learners with high activity Fakhris Khusnu Reza Mahfud; Zainal Abidin; Usman Nurhasan
Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Vol. 9 No. 2 (2024): May 2024
Publisher : University of Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/abdimas.v9i2.12261

Abstract

The mosque is the Muslim community's place of worship and education. Regular worship occurs according to a timetable. However, educational activities require quite a long time, so the mosque management schedules learning activities periodically. In addition, mosque congregations have a very high diversity and density of activities, especially mosque congregations in urban areas. The management of urban mosques has difficulty organizing learning consistently because the congregation has difficulty meeting at the same time periodically. This paper offers a solution by teaching with a hybrid learning method between project learning and peer teaching. Projects are created based on the needs of the environment and the congregation. The project development team is formed from worshipers who can work on projects. Other congregants receive knowledge through the project development team when the project is in the process of being created and run. This hybrid learning was experimented with by creating an aquaponics project. Aquaponics is operated with solar electricity. The project development team consists of a congregation of children to parents. The project has successfully transferred knowledge to the project development team members. The project operation attracts non-team worshippers to discuss independently with team members. Some non-team members have developed fish farming independently.
Clustering-Based Identification of Governance Risks in Campus Environments Sumiadji Sumiadji; Usman Nurhasan; Zainal Abdul Haris
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7205

Abstract

The growing implementation of governance models in higher education institutions has raised new challenges in accountability and performance. Although risk management and analysis in governance has received some attention in the literature, there is a lack of studies focusing on the use data-driven clustering algorithms. The current research focuses on the development and assessment of a web-based risk management information system that incorporates clustering principles to identify and map non-academic governance risks. The study followed the CRISP-DM framework and analyzed 678 risks from the Internal Audit Unit (SPI) of Politeknik Negeri Malang. The system employs K-Means clustering analysis to classify the risks into tiers based on performance indicators, budget, and risk severity. The system is equipped with data upload, preprocessing, logging, and cluster visualization modules. A comparative analysis of K-Means, DBSCAN, and Hierarchical Clustering showed that K-Means yields the best cluster quality with a Silhouette Score of 0.48, in comparison to DBSCAN (-0.705) and Hierarchical clustering (-0.395) . The developed system generated five distinct clusters corresponding to risks of varying settlement priority viz. very high, high, medium, low, and very low. The functional and usability assessments of the system confirmed that it provides automated and actionable insights on risks in a user-centric manner. The study has demonstrated the clustering of governance risks in higher education using K-Means is feasible. The incorporation of predictive analytics and real-time data would best support the research in active risk avoidance.
PEMANFAATAN YOGURTSALESPRO SEBAGAI UPAYA PENINGKATAN TATA KELOLA PENJULAAN UMKM BARK FRUITY Retno Damayanti; Usman Nurhasan; Anugrah Nur Rahmanto
Jurnal Pengabdian kepada Masyarakat Vol. 12 No. 2 (2025): JURNAL PENGABDIAN KEPADA MASYARAKAT 2025
Publisher : P3M Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/abdimas.v12i2.8027

Abstract

In the digital era, the transformation of information systems has become a crucial element in enhancing the competitiveness of micro, small, and medium enterprises (MSMEs). This community service initiative focuses on the digitalization of sales operations at Yogurt Bark Fruity, a student-run culinary business offering healthy yogurt-based products. Previously, sales activities were conducted manually via WhatsApp and Instagram, which posed risks of recording errors and limited market reach. The proposed solution involves the development and implementation of the yogurtSalesPro application, based on the PPEPP method. This system is designed to integrate the management of transactions, inventory, customer data, and sales reporting. Evaluation using the System Usability Scale (SUS) resulted in a score of 71.5, indicating a good level of usability. Additionally, assessment through the Technology Acceptance Model (TAM) revealed high scores across all indicators, with Perceived Usefulness and Perceived Ease of Use each achieving 100% positive responses. The application’s effectiveness is reflected in improved recording efficiency, a reduction in transaction errors from 15% to 2%, and an increase in both daily transactions and new customers. Beyond operational efficiency, the application also supports digital literacy and student entrepreneurship. Thus, yogurtSalesPro proves to be an effective solution in fostering innovation and sustainability for technology-based MSMEs.
Co-Authors Aflah Rahman Maulidiyah Al Huda, Muhammad Iqbaluddin Alwy Abdullah Ananta, Ahmadi Yuli Andre Asmara, Rossa Anisa Dyah Fatmawati Anugrah Nur Rahmanto Anugrah Nur Rahmantyo Arief Prasetyo Arief Prasetyo Atiqah Nurul Asri Bagas Setya Dian Nugraha Banni Satria Andoko Betlian Fajrin Budi Harijanto, Budi Cahyana, Cahyana Cahyana, Yuanita Hendra Candra Bella Vista Deddy Kusbianto Purwoko Aji Defandy Fanny Abdillah Dian Hanifudin Subhi Didik Dwi Prasetya Dika Rizky Yunianto Efita Tria Wardani Eka Larasati Amalia Elly Setyo Astuti Embriani Dewi Lestari Endah Septa Sintiya Erfan Rohadi Erninda Ristiani Fablo Aimar Faiz Ushbah Mubarok Fakhris Khusnu Reza Mahfud Fredo Vale Yuda Ughay Galih Putra Riatma Gilang Lazuardi Hakimah, Rafidah Putri Hartati, Kirana Hendra Pradibta Hilmy Setya Purnama Putra Ibnu Tsalis Assalam Imam Fahrur Rozi Indra Dharma Wijaya Indra Dharma Wijaya, Indra Dharma Kurnia, Alwan Ghozi Lazuardi, Gilang Lisuardi, Dina Lumintang, Galur Arasy Margaretha Violina Putri Maulidiyah, Aflah Rahman Melani, Erlin Mita Kartina Sari Moch Hafiz Nasirrudin Moch Zawaruddin Abdullah Muhammad Dwi Aldi Rizaldi Muhammad Mujahid Muhammad Rizki Oktaviansyah Muhammad Shulhan Khairy Mula Agung Barata Mustika Mentari Nasirrudin, Moch Hafiz Ningtyas, Noviana Nugraha, Bagas Setya Dian Nur Rahmanto, Anugrah Nur Wijayaningrum, Vivi Nurindrasari, Diana Oktaviansyah, Muhammad Rizki Pamenang, Muhammad Unggul Pramana Yoga Pramana Yoga Saputra Pramudhita, Agung Nugroho Pratama Putra Marhendra Prihatmanda, Ryan Akbar Purnomo, Bagus Putra Prima Arhandi, Putra Prima Qori, Elsa Lusiana Rafandi, Hanif Naufal Rafidah Putri Hakimah Rahma Sabita, Almira Rahmanto, Anugrah Nur Rahmantyo, Anugrah Nur Rakhmat Arianto Retno Damayanti Retno Damayanti Retno Damayanti Soejoedono Riatma, Galih Putra Risa Juliadilla Rizky Alifian Rokhimatul Wakhidah Rosa Andrie Asmara Rozan, Naufal Rudy Ariyanto Rudy Ariyanto Ryan Akbar Prihatmanda Samsul Islam Baddrisshofa Saputro, Halim Teguh Satrio Binusa Suryadi Satrio Binusa Suryadi Sukmadewi, Ferina Sumiadji Suryadi, Satrio Binusa Suryani, Debhys Syaad Patmanthara Syalwa, Laduni Estu Tresna, Esa Luh Tresna, Tresna Triswidrananta, Odhitya Desta Ulfa, Farida Vivin Ayu Lestari Wardani, Efita Tria Wijanarko, Eko Setio Yoga, Pramana Zainal Abdul Haris Zainal Abidin