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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) Abdi Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Pengabdian Kepada Masyarakat Jurnal Abdi Masyarakat Indonesia Jurnal Algoritma eProceedings of Engineering Journal of Fuzzy Systems and Control (JFSC) Scientific Journal of Informatics Control Systems and Optimization Letters Jurnal ilmiah teknologi informasi Asia Journal of Soft Computing Exploration
Pima Hani Safitri
Telkom University
Aerospace Engineering 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 Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Veterinary Other

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Verifikasi Tanda Tangan Online Menggunakan Algoritma Genetika Dan Support Vector Machine Pima Hani Safitri; Anditya Arifianto; Kurniawan Nur RAMADHANI
eProceedings of Engineering Vol 5, No 2 (2018): Agustus 2018
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak Tanda tangan merupakan salah satu alat autentifikasi yang sering digunakan. Banyak hal didunia ini yang diresmikan menggunakan tanda tangan. Setiap orang memiliki karakteristik tanda tangan yang cukup beragam. Pengenalan tanda tangan secara offline masih mungkin memiliki banyak kesalahan karena itu dikembangkan pengenalan tanda tangan secara online dengan menggunakan fitur-fitur dinamis dari tanda tangan. Pada penelitian ini, dibangun dua skema yaitu tanpa pemilihan fitur menggunakan Algoritma Genetika dan tanpa pemilihan fitur. Sistem verifikasi ini menggunakan algoritma Support Vector Machine(SVM) untuk memverifikasi tanda tangan karena SVM sudah terbukti di penelitian sebelumnya dapat menghasilkan akurasi yang baik. Penelitian ini juga ditujukan untuk menemukan fitur-fitur yang penting dalam sebuah tanda tangan dari enam kelompok fitur yang diuji. Dataset yang digunakan adalah dataset SVC2004 yang berisi tanda tangan 5 orang yang masing masing memiliki 20 tanda tangan asli dan 20 tanda tangan palsu yang ditiru oleh professional. Hasil penelitian menunjukkan Algoritma Genetika dapat menghasilkan akurasi 94.40% dan lebih baik 4.21% dibandingkan tanpa melalui pemilihan fitur. Kelompok fitur yang berpengaruh adalah kelompok fitur Geometry dan Miscellaneous karena menghasilkan akurasi yang lebih baik daripada kelompok fitur lainnya. Kata kunci : verifikasi tanda tangan, algoritma genetika, Support Vector Machine(SVM), kelompok fitur Abstract Signatures are one of the most commonly used authentication tools. Many things in this world are inaugurated using signatures. Everyone has signature characteristics that are quite diverse. The verification of offline signatures may still have many errors because it developed the verification of signatures online by using the dynamic features of the signature. In this research, two schemes are built without the feature selection using Genetic Algorithm and without feature selection. This verification system uses the Support Vector Machine (SVM) algorithm to verify the signature because SVM has been proven in previous research to produce good accuracy. The study is also intended to find important features in a signature of the six groups of features tested. The dataset used is a SVC2004 dataset containing 20 authentic signatures and 20 fake signatures imitated by professionals of 5 users. The results showed Genetic Algorithm can produce 94.40% and 4.21% better than without the selection of features. Influential feature groups are Geometry and Miscellaneous feature groups because they produce better accuracy than other feature groups. Keywords: signature verification, Genetic Algorithm, Support Vector Machine(SVM), feature group
Creating E-commerce for MSMES in Panjunan Village: Steps towards a Smart Village Rahmawati, Dyah Putri; Amri, Arni Muarifah; Rahmawati, Dewi; Safitri, Pima Hani
Abdi Masyarakat Vol 6, No 2 (2024): Abdi Masyarakat
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/abdi.v6i2.7300

Abstract

Micro, small, and medium enterprises (MSMEs) are crucial sectors that support economic growth in Indonesia. In the massive development of the digital economy, there has been a shift from offline to online transactions. MSME actors are now required to adopt technology to follow consumer shopping trends. One way to do this is by implementing e-commerce. The development of MSMEs through e-commerce is a smart step to increase visibility and market access. By leveraging e-commerce platforms, MSMEs can reach a wider audience, boost sales, and expand their business footprint without geographical limitations. In addition to digitalization, MSMEs need guidance in online sales, inventory management, digital marketing, and financial management. This guidance helps MSMEs maximize their potential in e-commerce. Desa Panjunan in Duduksampeyan District, Gresik Regency, is one village with MSME potential that needs to be developed through e-commerce. This community service activity will include creating an MSME e-commerce website for the village as a step towards becoming a Smart Village. The developed e-commerce has been tailored to the characteristics and needs of MSME actors in Desa Panjunan. This e-commerce initiative in Desa Panjunan can open up broader market access for local products, improve competitiveness, product quality, and MSME business management, as well as increase the income and welfare of the local community. 
Analisa Kematangan Manajemen Layanan Teknologi Informasi Dengan Standar Information Technology Infrastructure Library (ITIL V3): Studi Kasus Pengadilan Negeri Bondowoso Alhari, Muhammad Ilham; Safitri, Pima Hani; Amri, Arni Muarifah; Ramadan, Arip
Jurnal Ilmiah Teknologi Informasi Asia Vol 18 No 2 (2024): Volume 18 nomor 2 2024 (8)
Publisher : LP2M Institut Teknologi dan Bisnis ASIA Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v18i2.974

Abstract

This study aims to analyze the maturity level of Information Technology (IT) service management in Bondowoso District Court using the Information Technology Infrastructure Library (ITIL) version 3 (V3) framework. The use of IT in the state court has become crucial to support daily operations, efficiency, and quality of service to the community. The research method used is a case study, with data collection through interviews, observation, and document analysis. The results showed that Bondowoso District Court has a level of IT service management maturity that still needs to be improved. ITIL V3 is used as a guideline to evaluate IT service management processes in such courts. The results of this research can also be an important contribution in the context of developing IT service management in similar institutions, focusing on the application of the ITIL V3 framework. It is hoped that with corresponding improvements, the court can reach a higher level of IT service management maturity and provide better service to society. Keywords: Information Technology Infrastructure Library (ITIL); Pengadilan Negri Bondowoso, Manajemen layanan
A Deep Learning Model Comparation for Diabetic Retinopathy Image Classification Mustaqim, Tanzilal; Safitri, Pima Hani; Muhajir, Daud
Scientific Journal of Informatics Vol. 12 No. 1: February 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i1.20939

Abstract

Purpose: This study compares the performance of various deep learning models for diabetic retinopathy (DR) classification, emphasizing the impact of different optimization functions. Early detection of DR is vital for preventing blindness, and the research investigates how optimization functions influence the classification accuracy and efficiency of several convolutional neural networks (CNNs). This study fills a gap in the existing literature by examining how optimization functions affect model performance in conjunction with architectural considerations. Methods: This paper uses the APTOS 2019 dataset, which comprises 3,663 retinal fundus images classified into five classes of diabetic retinopathy severity. Four CNN-based models, including CNN, ResNet50, DenseNet121, and EfficientNet B0, were trained using five optimization techniques: Adam, SGD, RMSProp, AdamW, and NAdam. The performance of the experimental scenarios was evaluated through accuracy, precision, recall, F1-score, training duration, and model size. Result: EfficientNet B0 demonstrated superior computational efficiency with a minimal model size of 16.16 MB. Subsequently, DenseNet121 with the SGD optimizer achieved the highest test accuracy of 96.86%. The experimental results indicate that the optimizer significantly influences model performance. AdamW and NAdam yield superior outcomes for deeper architectures such as ResNet50 and DenseNet121. Novelty: This paper offers an analytical examination of deep learning models and optimization techniques for DR classification, helping to clarify the trade-offs between computational efficiency and classification performance. The findings contribute to the development of more accurate and efficient DR detection systems, which could be utilized in real-world, resource-limited settings.
Implementasi Digitalisasi Pembuatan Rapor untuk TPQ Al-Mubaarok Surabaya dalam Mendukung Evaluasi Santri Vessa Rizky Oktavia; Rausanfita, Alqis; Safitri, Pima Hani; Satria Bahari Johan, Ahmad Wali
PaKMas: Jurnal Pengabdian Kepada Masyarakat Vol 5 No 1 (2025): Mei 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/pakmas.v5i1.4102

Abstract

Taman Pendidikan Al-Quran (TPQ) is a non-formal educational institution. Often, TPQ prioritizes the quality of educational materials so that it slightly ignores the administrative aspects. A TPQ ​​usually contains asatidz (ustadz and ustadzah) who have expertise in the field of religion, but do not have staff who are experts in administrative matters. Not a few TPQs still use manual recording such as using paper to make report cards. As a result, there are still often errors in recording grades on report cards and asatidz who find it difficult to manage report cards. The problems faced by asatidz become more complicated when the number of students increases. Digitalization is a solution that can solve the problems faced by TPQ. With the digitalization of report cards, asatidz will easily manage student grades and print report cards massively in a short time. Application creation is carried out by analyzing needs, designing interfaces, implementing, and training. This activity was carried out by a community service team from Telkom University and partners of TPQ Al-Mubaarok Surabaya. The result is an application that has reliability in managing student grade data. This application can be accessed from anywhere by TPQ, making it easier for TPQ to manage student report cards. Positive impacts felt include reducing errors when entering data and ease in storing digital data.
Rancang Bangun Prototipe Sistem Deteksi Dini Retinopathic Diabetic Berbasis Website Muhajir, Daud; Mustaqim, Tanzilal; Safitri, Pima Hani; Oktavia, Vessa Rizky
Jurnal Algoritma Vol 22 No 1 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-1.2255

Abstract

Diabetic Retinopathic (DR) is one of the retinal disorders caused by high blood sugar levels. There are fewer ophthalmologists available, and treating DR patients manually is a time-consuming process. Therefore, there is a need for an automatic DR early detection method using Deep Learning. The purpose of this research is to build a web-based DR early detection prototype with retinal image classification using the DenseNet121 Deep Learning model and the Stochastic Gradient Descent (SGD) optimizer to improve the accessibility and efficiency of screening. The software development method used in this research is waterfall which consists of analysis phase, design phase, implementation phase, and testing phase. To ensure the prototype runs as planned, black-box testing is carried out on each of its features to ensure system functionality in accordance with predetermined specifications. This research produces a RD early detection prototype that has been tested with all 16 test cases and has a suitable status. Future research can be carried out further system development by involving real users such as ophthalmologists and can be applied in hospitals.
Implementasi Klasifikasi Dosis Obat Pil Menggunakan Naive Bayes Pada Penyakit Gagal Jantung Zulkarnaen, Feiticeira; Yusuf Wicaksono, Ardian; Hani Safitri, Pima
eProceedings of Engineering Vol. 12 No. 2 (2025): April 2025
Publisher : eProceedings of Engineering

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Abstract

Penyakit gagal jantung memerlukan pengelolaan dosis obat yang tepat untuk meningkatkan efektivitas pengobatan. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi dosis obat menggunakan algoritma Naive Bayes dengan pendekatan Gaussian dan Multinomial, serta meningkatkan performa model dengan teknik oversampling SMOTE dan VAE. Data pasien diklasifikasikan berdasarkan usia, jenis kelamin, berat badan, riwayat penyakit, metabolisme, dan toleransi obat. Implementasi sistem dilakukan melalui GUI berbasis Tkinter, memungkinkan pengguna memasukkan data pasien dan mendapatkan prediksi dosis obat yang sesuai. Hasil evaluasi menunjukkan bahwa kombinasi Naive Bayes dengan SMOTE memberikan performa terbaik dengan akurasi 73,90%, presisi 74,99%, recall 73,36%, dan F1-score 73,90%. Metode VAE memiliki performa lebih rendah dibandingkan SMOTE. Analisis lebih lanjut menunjukkan bahwa Bernoulli Naive Bayes memiliki akurasi tertinggi dalam klasifikasi tanpa oversampling, sementara model Naive Bayes standar kurang efektif dalam menangani data multi-label. Kesimpulannya, pendekatan Naive Bayes dengan oversampling SMOTE dapat meningkatkan akurasi prediksi dosis obat bagi pasien gagal jantung dan dapat digunakan sebagai alat bantu dalam pengambilan keputusan klinis. Kata kunci— Naive Bayes, Klasifikasi dosis obat, Gagal Jantung, SMOTE, VAE, GUI
Implementasi Sistem Perpustakaan Digital Berbasis Website untuk Peningkatan Efisiensi dan Kualitas Layanan Satria Bahari Johan, Ahmad Wali; Safitri, Pima Hani; Rachmaniar, Desita Nur; Wicaksono, Ardian Yusuf; Sebastian, Gerrard; Firdaus, Raihan; Saputra, Ananda Bintang; Putra, Muhammad Alifian; Krishna Lokajaya, Gabriel Azarya
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 3 (2025): Edisi Juli - September
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i3.6455

Abstract

Perpustakaan sebagai fasilitas penunjang yang menyediakan sumber bacaan mengelola bahan pustaka, baik berupa buku maupun bukan berupa buku untuk mendukung proses pembelajaran di dunia Pendidikan. Layanan perpustakaan yang masih bersifat konvensional ataupun manual banyak sekali menimbulkan berbagai kendala dalam pemberian dan pemenuhan layanan. Solusi permasalahantersebut dengan menghadirkan terobosan terbaru dibidang perpustakaan yaitu terciptanya inovasi produk perpustakaan digital yaitu berupa website. Metode yang digunakan dalam kegiatan pengabdian kepada masyarakat ini adalah sosialisasi hasil pengembangan website perpustakaan. Hasil kegiatan pengabdian kepada masyarakat ini berupa website perpustakaan yang terdiri atas informasi-informasi seperti koleksi buku favorit, fitur-fitur utama yang dapat dinikmati, layanan yang dapat diakses, lokasi perpustakaan serta informasi mengenai sosial media dan contact person maupun hotcall. Hal ini menunjukkan bahwa peran serta teknologi informasi menjadi solusi yang efektif bagi permasalahan perpustakaan konvensional
Freshwater Filling Optimization Based on Price Using XGBoost and Particle Swarm Optimization on Cargo Ship Voyage Yulianto, Ilham; Fauzi, Muhammad Dzulfikar; Safitri, Pima Hani
Scientific Journal of Informatics Vol. 12 No. 2: May 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i2.24988

Abstract

Purpose: Efficient freshwater management is critical in cargo ship operations, yet current practices often involve fixed refilling strategies that ignore price differences across ports and fail to predict actual consumption accurately. These inefficiencies lead to unnecessary operational costs. To address this, the study introduces a combined approach using XGBoost for predict freshwater usage and Particle Swarm Optimization (PSO) to minimize refilling costs through optimal port selection. Methods: Freshwater demand was predicted using an XGBoost regression model trained on real operational data from 2024, which included historical voyage distances and freshwater consumption records from cargo ships. Based on these predictions, Particle Swarm Optimization (PSO) was applied to identify cost-efficient refilling locations along each ship’s route, minimizing total water procurement cost while satisfying operational constraints. The proposed framework was validated through simulated voyage scenarios to evaluate its impact on cost efficiency and planning effectiveness. Result: The integration of XGBoost and PSO effectively optimized freshwater refilling strategies, achieving a relative prediction error of 9.48% in freshwater consumption prediction and cost savings from 9 to 40% from across 3 ships sample through strategic port selection based on consumption patterns and price variability. Novelty: Unlike prior works focused on fuel or generic logistics optimization, aim of this study is to combine XGBoost and PSO for optimizing freshwater refilling on cargo ship voyages using actual operational data. The results demonstrate practical, scalable improvements in cost efficiency, making a novel contribution to maritime resource planning.
Analisis Perbandingan Metode Preprocessing untuk Citra Retinopati Diabetik Menggunakan Deep learning Safitri, Pima Hani; Mustaqim, Tanzilal; Muhajir, Daud
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.22-2.2324

Abstract

Retinopati diabetik adalah gejala yang disebabkan oleh komplikasi diabetes yang menyerang mata penderitanya. Bercak-bercak pada retina penderita menjadi ciri gejalanya. Semakin banyak bercak, maka semakin parah retinopati diabetik yang diderita. Upaya peneliti untuk mendeteksi retinopati diabetik dengan citra retina sudah mulai dikembangkan dengan teknologi kecerdasan buatan, salah satunya berbasis deep learning. Kesulitan selanjutnya adalah kualitas citra retina yang kurang baik, sehingga mengakibatkan hasil deteksi yang kurang baik. Oleh karena itu, penelitian ini mengusulkan analisis perbandingan teknik untuk meningkatkan akurasi pengolahan citra deteksi retinopati diabetik berbasis deep learning. Data yang digunakan adalah data APTOS2019, yang terdiri dari 5 kelas berdasarkan tingkat keparahan penyakit. Ada tiga teknik yang digunakan: CLAHE, gamma correction, dan Retinex. Arsitektur deep learning yang digunakan adalah DenseNet121 dan EfficientNetB0 karena telah banyak digunakan pada data citra medis. Hasilnya, kombinasi gamma correction dan DenseNet121 menghasilkan akurasi tertinggi yaitu 81,4%. Sedangkan akurasi terendah diperoleh dari kombinasi menggunakan Retinex. Arsitektur terbaik secara keseluruhan adalah EfficientNetB0, dengan rata-rata akurasi sebesar 81,9%. Selanjutnya, penelitian ini dapat digunakan untuk memperbaiki citra retinopati diabetik sehingga deteksi dapat dilakukan sedini mungkin.
Co-Authors Achmad Dany Alfansyah Affifah Mutiara Pertiwi Afifah Fikriyah Dhiya'ulhaq Ahmad Akbar Megantara Ahmad Wali Satria Bahari Johan Akbar Muhammad Sadat Alqis Rausanfita Ananda Bintang Saputra Anditya Arifianto Ardian Yusuf Wicaksono Arip Ramadan Dafi’us Shidqi , Mochamad Desita Nur Rachmaniar DEWI RAHMAWATI Didik Purwanto Dimas Adiputra Dimas Chaerul Ekty Saputra Dyah Putri Rahmawati Firdaus, Raihan Galih Ananta, Whisnumurty Imam Prasetyo Suherman Irianna Futri Khansa Nailah Anjani Kharisma Monika Dian Pertiwi Krishna Lokajaya, Gabriel Azarya Kurniawan Nur Ramadhani Muhajir, Daud Muhammad Dzulfikar Fauzi Muhammad Fadli Zamzami Muhammad Ihsan Diputra Muhammad Ijaz Shafarin Muhammad Ilham Alhari Nilla Rachmaningrum Nur Aulia Dinda Putri Putra, Muhammad Alifian Saputra, Ananda Bintang Satria Putra Buana, Elang Sebastian, Gerrard Tanzilal Mustaqim Thinzar Aung Win Vessa Rizky Oktavia Yulianto, Ilham Zulkarnaen, Feiticeira