Article Per Year (5 Year)
p-Index From 2021 - 2026
5.041
P-Index
This Author published in this journals
All Journal Sainteks AKSIOMA: Jurnal Program Studi Pendidikan Matematika QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama Metode : Jurnal Teknik Industri JURNAL REKAYASA TEKNOLOGI INFORMASI JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Nasional Komputasi dan Teknologi Informasi Psychology, Evaluation, and Technology in Educational Research Jurnal Kridatama Sains dan Teknologi Journal of Innovation and Future Technology (IFTECH) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Sistem Informasi dan Sistem Komputer Mejuajua Jurnal Dinamika Informatika (JDI) Journal Of Computer Science And Technology BERBAKTI: Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas Indonesia Jurnal Bisnis Digital dan Sistem Informasi Jurnal Ilmu Komputer dan Matematika Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Fida Maisa Hana
Universitas Muhammadiyah Kudus
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Transportation Other

Published : 36 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 36 Documents
Search

 1   2   3   4 
Development of 3D Animated Story Media Through DRTA Strategy to Improve Reading Comprehension Skills of Elementary School Students Manggalastawa Manggalastawa; Dhina Cahya Rohim; Fida Maisa Hana; Sinta Nur Kalimah
QALAMUNA: Jurnal Pendidikan, Sosial, dan Agama Vol. 18 No. 1 (2026): Qalamuna - Jurnal Pendidikan, Sosial, dan Agama
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah Program Pascasarjana IAI Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/qalamuna.v18i1.8243

Abstract

Reading comprehension is a fundamental literacy skill that supports students’ learning across various subjects. However, observations in elementary schools show that many students still struggle to understand narrative texts due to limited comprehension skills and the lack of engaging and innovative learning materials. At the same time, technological advancements provide opportunities to develop digital learning media that can enhance motivation and comprehension. One promising innovation is the use of 3D animated stories, which can present narrative content in a more vivid, interactive, and meaningful way. This study aims to develop 3D animated story learning media integrated with the Directed Reading Thinking Activity (DRTA) strategy to improve the reading comprehension skills of fourth-grade elementary school students. The research employed the ADDIE development model and was conducted at an elementary school in Kudus Regency, Central Java, Indonesia. The developed product consists of 3D animated learning media and a learning guidebook. Validation results from media experts, subject matter experts, and elementary school learning device experts indicated that the product was highly valid. Field testing showed an improvement in students’ reading comprehension, as reflected by higher posttest scores compared to pretest scores. The effectiveness test revealed a high N-Gain value of 0.73. In addition, practicality assessments through student and teacher questionnaires produced very positive results, with scores of 94% and 87.5%, respectively. These findings indicate that 3D animated stories integrated with the DRTA strategy are effective and practical for improving elementary students’ reading comprehension, particularly in narrative text learning.
Klasifikasi Gangguan Tidur Menggunakan Algoritma XGBoost dengan SMOTE dan Grid Search Moh. Indra Kholid Khoirusshofi; Fida Maisa Hana; Taftazani Ghazi Pratama
Sainteks Vol. 23 No. 1 (2026): April
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/sainteks.v23i1.30171

Abstract

Gangguan tidur merupakan permasalahan kesehatan yang memiliki prevalensi tinggi dan berdampak signifikan terhadap kualitas hidup, sehingga diperlukan sistem deteksi dini yang akurat dan efisien. Perkembangan machine learning membuka peluang untuk membangun model klasifikasi gangguan tidur berbasis data, namun ketidakseimbangan kelas pada dataset medis sering menjadi tantangan yang menurunkan performa model, khususnya pada kelas minoritas. Penelitian ini bertujuan membangun model klasifikasi gangguan tidur menggunakan algoritma Extreme Gradient Boosting (XGBoost) dengan penerapan Synthetic Minority Oversampling Technique (SMOTE) dan optimasi hiperparameter menggunakan Grid Search. Dataset yang digunakan adalah Sleep Health and Lifestyle Dataset yang terdiri dari 374 data dengan tiga kelas target, yaitu Insomnia, No Disorder, dan Sleep Apnea. Penelitian ini menguji empat skenario model, yaitu XGBoost tanpa SMOTE dan Grid Search, XGBoost dengan SMOTE, XGBoost dengan Grid Search, serta kombinasi SMOTE dan Grid Search. Evaluasi kinerja model dilakukan menggunakan metrik accuracy, precision, recall, F1-score, Confusion Matrix, serta ROC Curve. Hasil penelitian menunjukkan bahwa penerapan SMOTE meningkatkan sensitivitas model terhadap kelas minoritas, sedangkan optimasi hiperparameter menggunakan Grid Search meningkatkan stabilitas dan akurasi model secara keseluruhan. Kombinasi SMOTE dan Grid Search menghasilkan performa terbaik dengan akurasi mencapai 97% serta nilai precision, recall, dan F1-score yang seimbang pada seluruh kelas. Selain itu, evaluasi menggunakan ROC Curve menunjukkan nilai AUC pada rentang 0,99 hingga 1,00, yang mengindikasikan kemampuan model yang sangat baik dalam membedakan setiap kelas. Hasil ini menunjukkan bahwa pendekatan yang diusulkan mampu meningkatkan performa klasifikasi gangguan tidur dan berpotensi menjadi alternatif dalam pengembangan sistem deteksi dini gangguan tidur.
Klasifikasi Kinerja Penjualan Produk Nike Menggunakan Algoritma Random Forest dengan Pendekatan Hold-Out dan K-Fold Cross Validation Divta Khoirun Nisa; Fida Maisa Hana; Saiful Ulya
Sainteks Vol. 23 No. 1 (2026): April
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/sainteks.v23i1.29930

Abstract

Dinamika industri ritel menuntut pemanfaatan data transaksi besar untuk pengambilan keputusan strategis. Penelitian ini bertujuan mengklasifikasi kinerja penjualan produk Nike ke dalam kategori rendah, sedang, dan tinggi menggunakan algoritma Random Forest. Penelitian ini memberikan kontribusi melalui pengujian model menggunakan dua pendekatan, yaitu Hold-Out dan K-Fold Cross Validation, untuk menjamin stabilitas performa. Dataset yang digunakan merupakan data sekunder dari Kaggle sebanyak 9.360 baris data transaksi Nike di Amerika Serikat periode 2020-2021. Tahapan penelitian meliputi preprocessing data melalui label encoding, pembagian data, pemodelan Random Forest, serta evaluasi menggunakan confusion matrix, hasil pengujian menunjukkan bahwa model memiliki performa yang sangat tinggi, dengan tingkat akurasi pada metode Hold-Out mencapai 98,13%. Sementara itu, pengujian menggunakan 10-Fold Cross Validation menghasilkan  akurasi tertinggi mencapai 94,39% pada fold ke-4. Secara keseluruhan, nilai weighted average precision, recall, dan F1-score mencapai 0,98 yang membuktikan efektivitas algoritma Random Forest dalam memberikan klasifikasi yang akurat. Temuan ini diharapkan dapat mendukung manajemen dalam pengambilan keputusan berbasis data di sektor ritel.
Implementation Of The Advanced Encryption Standard-128 Algorithm And Huffman Compression To Protect Student Grade Data Dzulfikar Ahmad Firdaus; Fida Maisa Hana; Widya Cholid Wahyudin
Journal of Computer Science and Technology (JOCSTEC) Vol 4 No 3 (2026): JOCSTEC - September
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v4i3.792

Abstract

Student grade data is personal data that must be protected under Indonesian Law Number 27 of 2022 on Personal Data Protection, yet the rising number of data breaches in the education sector shows that such protection has not been optimally implemented. This study implements the 128-bit Advanced Encryption Standard (AES) algorithm combined with Huffman compression to protect the confidentiality and integrity of student grade files in Excel (.xlsx) format, and evaluates its effectiveness through functional, performance, and security testing. The system was developed as a Python desktop application with a CustomTkinter interface, in which the encryption process runs Huffman compression before AES-128, while integrity verification uses SHA-256 hashing. Testing was conducted on seven student grade files from MA Ma'ahid Kudus. The results show that all files were successfully encrypted and decrypted without failure or data alteration, with encryption times of 0.0142-0.0828 seconds and decryption times of 0.0046-0.1417 seconds. The SHA-256 hash values of the original and decrypted files were identical for all samples, yielding 100% recovery accuracy, while the file size increase from padding and header insertion ranged only from 1,092 to 1,101 bytes. The study concludes that the combination of AES-128 and Huffman compression is an effective and efficient solution for protecting student grade data in educational institutions.
Analisis Sentimen Terhadap Kinerja Menteri Keuangan Purbaya Yudhi Sadewa Menggunakan Algoritma K-Nearest Neighbors Renoka Tresna Pramuda; Fida Maisa Hana; Agung Prihandono
Jurnal Rekayasa Teknologi Informasi (JURTI) Vol 10, No 2 (2026): Jurnal Rekayasa Teknologi Informasi (JURTI)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jurti.v10i2.26138

Abstract

Perkembangan media sosial meningkatkan partisipasi publik dalam menyampaikan opini terhadap kebijakan dan kinerja pejabat pemerintah. Penelitian ini bertujuan untuk menganalisis sentimen terhadap kinerja Purbaya Yudhi Sadewa sebagai Menteri Keuangan berdasarkan komentar TikTok. Data diperoleh melalui teknik scraping dari video TikTok dalam periode satu bulan setelah pelantikan dan menghasilkan 1317 komentar setelah proses pembersihan data. Tahapan pengolahan meliputi preprocessing, pelabelan data menggunakan metode manual dan lexicon-based,  ekstraksi fitur menggunakan TF-IDF serta pemodelan menggunakan algoritma K-Nearest Neighbors. Penentuan parameter optimal dilakukan menggunakan GridSearchCV dengan 10-Fold Cross Validation, yang menghasilkan nilai K terbaik 13 untuk data dengan labeling manual dan 15 untuk data dengan labeling lexicon-based. Hasil pengujian menggunakan Holdout Validation (80:20) menunjukkan bahwa model KNN dengan labeling manual memperoleh akurasi tertinggi sebesar 94,32%, sedangkan model dengan lexicon-based memperoleh akurasi sebesar 75,38%. Hasil penelitian menunjukkan bahwa pelabelan manual menghasilkan performa klasifikasi yang lebih baik dan lebih konsisten dibandingkan metode lexicon-based. Temuan ini mengindikasikan bahwa kualitas pelabelan data berpengaruh signifikan terhadap performa klasifikasi sentimen, terutama pada komentar media sosial yang bersifat informal dan ambigu.
Metode DMAIC Untuk Peningkatan Efisiensi Pada Proses Produksi Mesin Rice Milling Unit (RMU) Di PT XYZ Ahmad Yogi Mahendra; Fida Maisa Hana; Nunung Agus Firmansyah
Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 6 No. 2 (2026): Juli : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/teknik.v6i2.12103

Abstract

The production process of Rice Milling Unit (RMU) machines at PT XYZ faces serious challenges, including excessively high operating times that exceed the ideal cycle time for most production components, resulting in low machine efficiency and overall effectiveness. This study aims to analyze the root causes of inefficiency, identify problems in the RMU production process, and provide improvement recommendations and continuous control mechanisms using the DMAIC (Define, Measure, Analyze, Improve, Control) method. A descriptive quantitative approach was employed using production data from 120 work items, encompassing a total operating time of 234.9 hours and an actual output of 1,308 units. Effectiveness measurements using Overall Equipment Effectiveness (OEE) revealed that the average performance value was critically low due to a significant gap between actual operating time and ideal cycle time, despite high availability and quality rate. Pareto analysis identified excessive operating time (40%) and low performance (30%) as the largest contributors to inefficiency, while the Fishbone Diagram revealed root causes in machine, work method, and human resource factors. Proposed improvements include SOP standardization, implementation of preventive maintenance, elimination of non-value-added activities, and periodic OEE monitoring. The findings demonstrate that the DMAIC method is effective in diagnosing and designing structured improvement solutions to enhance RMU production efficiency at PT XYZ.
Co-Authors Achmad Ridwan Achmad Ridwan, Achmad Ade Ima Afifa Himayati Ade Kurnia Bayu Firdaus Afrisia, Silviana Putri Agung Bakti Agung Prihandono Ahadin, Akbar Ihsanul Ahmad Yogi Mahendra Ahmad, Saiful Andi Kurniawan Arlinwibowo, Janu Avira Budianita Cikita Berlian Hakim Deka Setia Negara Dhina Cahya Rohim Diva Anastasya Divta Khoirun Nisa Dwi Elysia Dinata Dzulfikar Ahmad Firdaus Eko Hari Rachmawanto Elisya Pujasari Fadhila, Vera Farikha Tuzzahro Firmansyah, Nunung Agus Hafni Aulida Hafni Aulida Harjanti, Agustina Eka Hawa Suci Hermawan Abdillah Hamka Ihsanul Ahadin, Akbar Imam Abdul Rozaq Imam Prayogo Pujiono Indanah Janu Arlinwibowo Khoirul Umam Haqiqi Mahdarul Huda Ahmad Manggalastawa Manggalastawa Manggalastawa, Manggalastawa Moh Akbar Munajad Moh. Indra Kholid Khoirusshofi Muadzah Muadzah Nunung Agus Firmansyah Nurul Iman Rahmawan Bagus Trianto Rangga Primadasa Renoka Tresna Pramuda Sabiq Ismail Saharani, Safira Saiful Ulya Sayyidati Maulia Ashfa Sinta Nur Kalimah Siti Mahgfiroh Soma Setiawan Soma Setiawan P.N Syahrul Azmi Nawaf Taftazani Ghazi Pratama Tri Febriani Dewi Widya Cholid Widya Cholid Wahyudin Widya Cholid Wahyudin Yunus Mustaqim Yunus Mustaqim, Yunus