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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Jurnal Teknologi Informasi dan Pendidikan Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat INCARE Jurnal Vokasi Informatika (JAVIT) Instal : Jurnal Komputer Journal of Community Service Tsaqofah: Jurnal Penelitian Guru Indonesia MASALIQ: Jurnal Pendidikan dan Sains Journal of Artificial Intelligence and Digital Business Jurnal Teknik Komputer dan Informatika (JTeKI) Journal of Authentic Research Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Jejak digital: Jurnal Ilmiah Multidisiplin Variable Research Journal Jurnal Publikasi Manajemen Informatika
Vera Irma Delianti
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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RANCANG BANGUN QUIZ APP BERBASIS WEB SEBAGAI MEDIA EVALUASI PEMBELAJARAN DI SMK TARUNA PADANG Hanif, Insan Matin; Zaus, Mahesi Agni; Delianti, Vera Irma; Budayawan, Khairi
Jurnal Publikasi Manajemen Informatika Vol. 5 No. 3 (2026): JURNAL PUBLIKASI MANAJEMEN INFORMATIKA
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupumi.v5i3.7757

Abstract

This study is motivated by the fact that many vocational high schools in Indonesia still rely on paper-based examinations despite the growing adoption of digital learning evaluation. At SMK Taruna Padang, examinations for around 100 active students are still conducted manually, although the school only employs 17 teachers, resulting in a heavy correction workload, repeated printing costs, and the absence of immediate feedback for students. This study aimed to design and build a web-based quiz application equipped with a reusable question bank and an analytics dashboard as a learning evaluation medium for SMK Taruna Padang. The system was developed using the Waterfall method and built with the Laravel framework and a MySQL database. The application provides three access roles, namely administrator, teacher, and student, and integrates automatic scoring with a dashboard that visualizes score distribution, question difficulty level, and class performance. System functionality was verified through Black Box Testing on 47 scenarios, all of which produced successful results, while feasibility was assessed by three media validators, yielding a feasibility score of 95.33 percent in the very feasible category. These findings indicate that the developed quiz application is feasible for implementation as a practical alternative to conventional paper-based examinations in vocational schools
Sistem Pendukung Keputusan Berbasis Simple Additive Weighting untuk Pemilihan Mahasiswa Terbaik: Rancang Bangun, Validasi Manual, dan Implementasi Web Muwaffaq, M. Taqy; Zulwisli, Zulwisli; Delianti, Vera Irma; Marta, Rizkayeni
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/detd7h51

Abstract

Pemilihan mahasiswa terbaik membutuhkan mekanisme penilaian yang objektif, transparan, dan efisien karena keputusan tidak hanya ditentukan oleh Indeks Prestasi Kumulatif, tetapi juga prestasi akademik dan non-akademik, absensi, sikap, serta peran penilai yang berbeda. Penelitian ini bertujuan merancang dan membangun Sistem Pendukung Keputusan (SPK) berbasis web untuk pemilihan mahasiswa terbaik menggunakan metode Simple Additive Weighting (SAW). Penelitian menggunakan pendekatan rancang bangun dengan model prototyping yang mencakup analisis kebutuhan pengguna, perancangan mock-up, implementasi sistem, pengujian, dan revisi. Sistem melibatkan empat aktor, yaitu mahasiswa, dosen penilai, ketua program studi, dan admin jurusan. Data utama yang diolah meliputi data mahasiswa, kriteria, bobot, nilai per kriteria, hasil normalisasi, nilai preferensi, dan laporan ranking. Hasil penelitian menunjukkan bahwa sistem mampu mengelola data mahasiswa dan kriteria, memproses penilaian, menampilkan tahapan perhitungan SAW, serta menghasilkan ranking otomatis. Validasi manual menunjukkan kesesuaian ranking antara perhitungan sistem dan perhitungan SAW manual, dengan alternatif A3 memperoleh nilai tertinggi, diikuti A1 dan A2. Pengujian black box pada modul login, mahasiswa, penilaian, perhitungan SAW, dan ranking menunjukkan seluruh skenario berjalan berhasil. Kebaruan penelitian ini terletak pada integrasi alur seleksi multi-aktor, konfigurasi kriteria berbobot, transparansi tahapan perhitungan, dan validasi komputasi manual dalam satu prototipe web yang dapat digunakan oleh program studi. Selecting the best student requires an objective, transparent, and efficient assessment mechanism because the decision is not only determined by grade point average but also by academic and non-academic achievements, attendance, attitude, and the involvement of different assessors. This study aims to design and develop a web-based Decision Support System (DSS) for selecting the best student using the Simple Additive Weighting (SAW) method. The study employed a design-and-development approach with a prototyping model consisting of user requirement analysis, mock-up design, system implementation, testing, and revision. The system involves four actors: students, assessors, the head of the study program, and the department administrator. The main data processed include student data, criteria, weights, scores for each criterion, normalization results, preference values, and ranking reports. The results show that the system can manage student and criteria data, process assessments, display SAW calculation stages, and generate automatic rankings. Manual validation confirmed the consistency between system-generated rankings and manual SAW computation, where alternative A3 achieved the highest score, followed by A1 and A2. Black-box testing on the login, student data, assessment, SAW calculation, and ranking modules showed that all scenarios were successful. The novelty of this study lies in integrating a multi-actor selection workflow, configurable weighted criteria, transparent calculation stages, and manual computational validation into a single web prototype that can be used by a study program.
Sistem Rekomendasi Menu Makanan Berbasis Content-Based Filtering dan XGBoost untuk Optimasi Kebutuhan Nutrisi Personal Erpiana, Erpiana; Syafrijon, Syafrijon; Hendriyani, Yeka; Delianti, Vera Irma
Journal of Authentic Research Vol. 5 No. 2 (2026): May
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/r3ne6g79

Abstract

Pemilihan menu makanan yang sesuai dengan kebutuhan nutrisi personal masih menjadi persoalan praktis, terutama ketika pengguna harus menyeimbangkan preferensi rasa, jenis bahan, metode memasak, dan target makronutrisi. Penelitian ini bertujuan merancang dan mengevaluasi sistem rekomendasi menu makanan berbasis aplikasi Android yang mengintegrasikan Content-Based Filtering dan XGBoost untuk optimasi kebutuhan nutrisi. Sistem menghitung kebutuhan energi pengguna menggunakan rumus Revised Harris-Benedict berdasarkan usia, jenis kelamin, berat badan, tinggi badan, dan tingkat aktivitas fisik. Content-Based Filtering digunakan untuk menyaring kandidat lauk berdasarkan jenis bahan utama, cita rasa, dan metode memasak menggunakan cosine similarity berbobot, sedangkan XGBoost Regressor digunakan untuk menilai kesesuaian nutrisi setiap kombinasi menu nasi, lauk, sayur, dan buah. Model dilatih menggunakan 500 profil pengguna simulasi dan 1.000 kombinasi menu sehingga terbentuk 500.000 data pelatihan. Hasil pengujian menunjukkan akurasi perhitungan nutrisi sebesar 99,96% terhadap perhitungan manual dengan rata-rata selisih 0,24 kkal. Model XGBoost menghasilkan MAE 0,0285, RMSE 0,0360, R² 0,9465, Spearman Rank Correlation 0,9654, Top-3 Accuracy 1,0000, dan NDCG@3 0,9922. Pengujian Black Box mencapai keberhasilan 98,6%, sedangkan pengujian pengguna memperoleh skor 4,47 dari skala 5. Temuan ini menunjukkan bahwa integrasi penyaringan berbasis preferensi dan penilaian nutrisi berbasis machine learning mampu menghasilkan rekomendasi menu yang adaptif, terukur, dan relevan bagi pengguna dewasa sehat. Selecting meals that match personal nutritional needs remains a practical challenge because users must balance food preference, ingredient type, cooking method, and macronutrient targets simultaneously. This study aims to design and evaluate an Android-based food menu recommendation system that integrates Content-Based Filtering and XGBoost for nutritional needs optimization. The system calculates users' energy requirements using the Revised Harris-Benedict equation based on age, sex, body weight, height, and physical activity level. Content-Based Filtering filters side-dish candidates using weighted cosine similarity based on main ingredient type, taste, and cooking method, while XGBoost Regressor evaluates the nutritional suitability of each complete menu combination consisting of rice, side dish, vegetables, and fruit. The model was trained using 500 simulated user profiles and 1,000 menu combinations, resulting in 500,000 training records. The test results show that the nutritional calculation achieved 99.96% accuracy compared with manual calculation, with an average difference of 0.24 kcal. The XGBoost model obtained an MAE of 0.0285, RMSE of 0.0360, R² of 0.9465, Spearman Rank Correlation of 0.9654, Top-3 Accuracy of 1.0000, and NDCG@3 of 0.9922. Black Box testing reached a 98.6% success rate, while user testing achieved an average score of 4.47 out of 5. These findings indicate that integrating preference-based filtering and machine learning-based nutritional scoring can produce adaptive, measurable, and relevant menu recommendations for healthy adult users.  
Dominasi Computational Thinking atas Motivasi dalam Kemampuan Pemrograman C Siswa SMA Yusuffa, Alfajar; Marta , Riskayeni; Delianti, Vera Irma; Darni, Resmi
Journal of Authentic Research Vol. 5 No. 3 (2026): August
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jar.v5i3.6173

Abstract

Kemampuan pemrograman tidak hanya ditentukan oleh penguasaan sintaks, tetapi juga oleh cara siswa memformulasikan masalah dan mempertahankan usaha ketika menghadapi kesalahan program. Penelitian ini bertujuan menguji kontribusi computational thinking skill dan motivasi belajar terhadap kemampuan pemrograman Bahasa C siswa SMA, sekaligus mengidentifikasi prediktor yang benar-benar dominan. Penelitian menggunakan desain kuantitatif korelasional ex post facto pada 138 siswa kelas XI SMA Negeri 1 Kubung yang dipilih secara proportionate stratified random sampling dari populasi 203 siswa. Computational thinking diukur dengan 13 soal objektif, motivasi dengan 22 pernyataan skala Likert, dan kemampuan pemrograman dengan 18 soal objektif; koefisien reliabilitas masing-masing sebesar 0,884, 0,852, dan 0,897. Hasil menunjukkan computational thinking berkorelasi sangat kuat dengan kemampuan pemrograman (r = 0,910; p < 0,001; R² = 0,829), sedangkan motivasi belajar tidak berkorelasi signifikan (r = -0,107; p = 0,210). Model simultan signifikan, F(2,135) = 331,81; p < 0,001, dengan R² = 0,831, tetapi penambahan motivasi hanya meningkatkan daya jelas model sebesar 0,2% (ΔR² = 0,002) dan koefisiennya tetap tidak signifikan (β = -0,044; p = 0,212). Kebaruan penelitian terletak pada bukti bahwa signifikansi model gabungan hampir sepenuhnya digerakkan oleh computational thinking, bukan motivasi. Temuan ini menegaskan perlunya pembelajaran Bahasa C yang memprioritaskan dekomposisi, pengenalan pola, abstraksi, perancangan algoritma, tracing, dan debugging, tanpa menafsirkan motivasi sebagai penyebab langsung capaian pemrograman. Programming ability depends not only on syntax mastery but also on how students formulate problems and sustain effort when code fails. This study examined the contributions of computational thinking skills and learning motivation to high school students’ C programming ability and identified the genuinely dominant predictor. A quantitative ex post facto correlational design involved 138 eleventh-grade students from SMA Negeri 1 Kubung, proportionally stratified and randomly selected from a population of 203. Computational thinking was measured using 13 objective items, motivation using 22 Likert statements, and programming ability using 18 objective items; reliability coefficients were 0.884, 0.852, and 0.897, respectively. Computational thinking showed a very strong correlation with programming ability (r = 0.910, p < 0.001, R² = 0.829), whereas learning motivation was not significantly related (r = -0.107, p = 0.210). The simultaneous model was significant, F(2,135) = 331.81, p < 0.001, with R² = 0.831; however, adding motivation increased explained variance by only 0.2% (ΔR² = 0.002), and its coefficient remained nonsignificant (β = -0.044, p = 0.212). The study’s novelty is evidence that the significant joint model was driven almost entirely by computational thinking rather than motivation. C programming instruction should therefore prioritize decomposition, pattern recognition, abstraction, algorithm design, tracing, and debugging while avoiding causal interpretations from correlational data.    
RANCANG BANGUN GAME EDUKASI KUDBLOX BERBASIS IMMERSIVE CODING SEBAGAI GAME PEMROGRAMAN DASAR Taufiq Rahman; Vera Irma Delianti; Syukhri; Dedy Irfan
Jurnal Publikasi Manajemen Informatika Vol. 5 No. 3 (2026): JURNAL PUBLIKASI MANAJEMEN INFORMATIKA
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupumi.v5i3.8033

Abstract

The high level of abstraction in basic programming concepts sequential, branching, looping, and functions frequently hinders early-stage university students from constructing accurate mental models of control flow. Existing game-based learning media largely operate on two-dimensional displays and have yet to represent the dynamics of algorithm execution spatially. This study developed KudBlox, an educational game built on the Roblox platform that integrates an immersive coding approach into a mission-based game format with 12 progressive levels across four programming concept zones. Development followed the Multimedia Development Life Cycle (MDLC) method. Product feasibility was assessed through two stages: media validation by three expert lecturers using an instrument adapted from the Learning Object Review Instrument (LORI), and a usability test involving 10 early-stage university students using the System Usability Scale (SUS). Media validation yielded an average score of 91.75%, categorized as Very Feasible. The SUS usability test produced an average score of 82.00, classified as grade A Acceptable. These findings indicate that KudBlox is feasible and usable as an independent learning medium for early-stage university students to understand basic programming logic concepts through three-dimensional visualization
RANCANG BANGUN APLIKASI KUIS GAMIFIKASI UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR KOMPUTASIONAL SISWA SMK MUHAMMADIYAH 1 PADANG Luqyana, Sifa; Delianti, Vera Irma; Mubai, Akrimullah; Tasrif, Elfi
Jurnal Publikasi Manajemen Informatika Vol. 5 No. 3 (2026): JURNAL PUBLIKASI MANAJEMEN INFORMATIKA
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupumi.v5i3.8038

Abstract

Computational Thinking competence among vocational high school students remains suboptimal, as reflected in the low mastery levels found among Grade X students at SMK Muhammadiyah 1 Padang, where conventional learning media and uniform, non-adaptive evaluation methods failed to provide personalized feedback. This study aimed to design and develop a web-based gamified quiz application featuring tiered questions based on Bloom's Taxonomy, gamification elements (points, badges, leaderboard), rule-based material recommendations, and quiz security features to support Computational Thinking learning. The Waterfall development model was employed, covering requirement analysis, system design, implementation, testing, and maintenance, with the system built using Laravel and MySQL. System feasibility was evaluated through media validation, Black Box Testing, GTmetrix performance testing, and User Acceptance Testing. Results showed a media validity percentage of 93.66% (Very Valid), all 29 Black Box Testing scenarios successful, an A performance grade on GTmetrix, and a practicality percentage of 89.13% (Very Practical). These findings indicate that the application is feasible and practical for use as a web-based learning evaluation medium, offering both pedagogical benefits for teachers in identifying student learning gaps and practical implications for improving Computational Thinking evaluation in vocational schools.
Co-Authors Agariadne Dwinggo Samala alfatakh, Muhamad amin Amri, Alwi Dwi Anori, Sartika Aresta, Meysella Khanza Asmara, Delvi Asnil Asnil Budayawan, Khairi Chania, Sylvia Atifah Dedy Irfan Dwiprima Elvanny Myori, Dwiprima Elvanny Efrizon Elfi Tasrif Erpiana, Erpiana Fadilla Fadli, Radinal Fajri, Bayu Ramadhani Falda, Regina Fitri, Desmawati Fivia Eliza Geovanne Farell Gunawan Fauzi Hakiki, Muhammad Hanif, Insan Matin Hudiya Mubarokah Ika Parma Dewi Irawan, Inneke Fortuna Julianti, Delia Khairi Budayawan Laila Najmi Lativa Mursyida Legiman Slamet Luqyana, Sifa Mahesi Agni Zaus Marta , Riskayeni Marta, Rizkayeni Mubai, Akrimullah Mubarokah, Hudiya Mursyida, Lativa Muwaffaq, M. Taqy Nurindah Dwiyani Nurlatipah, Nurlatipah Oktrilani, Rentika Pranoto, Dzenata Achmad Pratama, Megi Putra, Rido Ramadhani, Liza Resmi Darni Rizka Amanda Rizkayeni Marta Saputra, Noris Dwi Sheanny Ocmi Sakti sinaga, lotar mateus Sintia Okta Rina Sitepu, Raynald Syafrijon, Syafrijon Syintia Syukhri Taufiq Rahman Thamrin Thamrin Urrahmah, Syifa Wulandari, Yelfifa Yandra, Sidik Rama Yasdinul Huda Yeka Hendriyani Yusuffa, Alfajar Zandra, Arif Zulwisli .