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All Journal International Journal of Advances in Applied Sciences Jurnal Buana Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan InComTech: Jurnal Telekomunikasi dan Komputer JISKa (Jurnal Informatika Sunan Kalijaga) JATI (Jurnal Mahasiswa Teknik Informatika) JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknologi Informatika dan Komputer Yumary: Jurnal Pengabdian kepada Masyarakat Journal of Applied Computer Science and Technology (JACOST) Jurnal Pendidikan dan Teknologi Indonesia Engineering, Mathematics and Computer Science Journal (EMACS) Nusantara Hasana Journal Jurnal Informatika Terpadu Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Informatika Polinema (JIP) Journal of World Future Medicine, Health and Nursing Jurnal Indonesia : Manajemen Informatika dan Komunikasi The Journal of Enhanced Studies in Informatics and Computer Applications Journal of Informatics and Advanced Computing International Journal of Computer Science and Information Technology Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Risqy Siwi Pradini
Institut Teknologi, Sains, Dan Kesehatan RS.DR. Soepraoen Kesdam V/BRW
Agriculture, Biological Sciences & Forestry Humanities 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 Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Optimasi Weight AHP Menggunakan Genetic Algorithm untuk Rekomendasi Platform Media Sosial Sebagai Sarana Promosi Digital Pradini, Risqy Siwi; Anshori, Mochammad; Haris, M. Syauqi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 5: Oktober 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2024118011

Abstract

Tim pemasar suatu perusahaan dapat memanfaatkan media sosial untuk memperluas jangkauan pemasaran dan berinteraksi secara lebih intens dengan para pelanggan. Salah satu tantangan utama yang dihadapi tim pemasar untuk promosi digital adalah bagaimana memilih platform sosial media yang paling tepat agar dapat mencapai tujuan promosi yang optimal. Keputusan untuk memilih platform sosial media ini melibatkan sejumlah kriteria seperti content, impression, cost, look and feel, dan audience fit. Urutan rekomendasi platform media sosial sebagai sarana promosi yang dihasilkan penelitian ini adalah Facebook, Instagram, YouTube, Twitter, Pinterest, TikTok, dan LinkedIn. Urutan rekomendasi tersebut berhasil didapatkan dengan pendekatan optimasi weight Analytical Hierarchy Process (AHP) menggunakan Genetic Algorithm (GA) untuk rekomendasi platform media sosial sebagai sarana promosi digital. Optimasi yang dilakukan terbukti dapat meningkatkan keakurasian peringkat dari 95% ke 97% yang dihasilkan melalui perhitungan fitness yang menggunakan rumus Spearman Correlation. Penelitian ini juga berhasil menarik kesimpulan terkait bidang AHP-GA yang menyatakan bahwa popsize mempengaruhi nilai fitness. Semakin tinggi popsize, maka semakin besar potensi nilai fitness yang dihasilkan, namun peningkatan popsize itu sendiri tidak menjamin perolehan nilai fitness yang lebih baik sehingga perlu memikirkan faktor lainnya pula. Selain itu, semakin banyaknya jumlah generasi maka proses evolusi akan semakin sering terjadi. Tiap generasinya akan melakukan crossover dan mutasi, sehingga hal ini berpengaruh pada semakin beragamnya individu yang dihasilkan dan pada akhirnya dapat membantu menemukan solusi yang lebih baik.   Abstract A company's marketing team can use social media to expand marketing reach and interact more intensely with customers. One of the main challenges faced by marketers for digital promotion is how to choose the most appropriate social media platforms to achieve optimal promotional goals. The decision to choose a social media platform involves several criteria such as content, impression, cost, look and feel, and audience fit. The order of recommendations for social media platforms as a means of promotion resulting from this research are Facebook, Instagram, YouTube, Twitter, Pinterest, TikTok, and LinkedIn. The sequence of recommendations was successfully obtained using the weight Analytical Hierarchy Process (AHP) optimization approach using Genetic Algorithm (GA) for social media platform recommendations as a means of digital promotion. The optimization carried out was proven to increase ranking accuracy from 95% to 97% which was produced through fitness calculations using the Spearman Correlation formula. This study also succeeded in drawing conclusions related to the AHP-GA field which stated that popsize affects fitness values. The higher the popsize, the greater the potential fitness value generated, however increasing the popsize itself does not guarantee obtaining a better fitness value so you need to think about other factors as well. In addition, the greater the number of generations, the more frequently the evolutionary process will occur. Each generation will carry out crossover and mutation, so this influences the resulting more diverse individuals and can ultimately help find better solutions.
Decision Tree Regression Untuk Prediksi Prevalensi Stunting di Provinsi Nusa Tenggara Timur Putri, Irnanda Septian Ika; Pradini, Risqy Siwi; Anshori, Mochammad
Jurnal Teknologi Informatika dan Komputer Vol. 10 No. 2 (2024): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v10i2.2179

Abstract

Stunting adalah kondisi terhambatnya pertumbuhan linier anak-anak karena kekurangan gizi dan perawatan yang tidak memadai sejak dalam kandungan hingga usia dua tahun. Stunting disebabkan oleh berbagai faktor, termasuk kurangnya asupan gizi yang memadai, infeksi kronis atau berulang, praktik pemberian makanan yang tidak sesuai, sanitasi yang buruk, serta akses terbatas terhadap layanan kesehatan dan pendidikan gizi. Di Indonesia, provinsi yang memiliki prevalensi stunting paling tinggi berada di Nusa Tenggara Timur (NTT). Penelitian ini bertujuan untuk membuat model prediksi menggunakan Decision Tree Regression untuk memprediksi prevalensi stunting di NTT. Dengan demikian, hasil penelitian ini selain menghasilkan model prediksi juga dapat memberikan pemahaman yang lebih komperhensif mengenai faktor-faktor yang mempengaruhi tingkat stunting di NTT dan mendukung upaya untuk menurunkan angka prevalensinya di provinsi tersebut. Untuk menguji model prediksi yang dihasilkan, penelitian ini menggunakan metrik RMSE. Hasil pengujian dengan metrik RMSE menunjukkan nilai 0,093. Nilai ini membuktikan bahwa model Decision Tree Regression yang digunakan memiliki tingkat kesalahan prediksi yang relatif rendah, sehingga cukup efektif dalam memprediksi prevalensi stunting berdasarkan data yang digunakan.
Perancangan Prototype Sistem Monitoring Ternak Ruminansia dengan Metode Human Centered Design Putriana, Rena; Pradini, Risqy Siwi; Haris, M. Syauqi
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.2553

Abstract

The ruminant livestock sector, such as sheep and cattle, makes a significant contribution to food security and the national economy. However, livestock data management, which is still carried out manually, remains a major challenge in improving operational efficiency, as seen in the Sarwa Adem Mulya (SAM) Cooperative. This study aims to design a prototype of a mobile-based livestock monitoring system called Ruminant Watch, using the Human-Centered Design (HCD) approach to align with the needs and limitations of field users. The research was conducted through five main stages: literature review, specification of the usage context, identification of user needs, design solution development using Figma, and usability evaluation through the System Usability Scale (SUS) questionnaire. The testing results showed an average SUS score of 87, which falls into the “Excellent” category. This indicates that the developed prototype system is not only easy to use but also relevant and effective in supporting livestock monitoring activities. This design is expected to serve as an initial step toward the digitalization of ruminant farming that is more efficient and adaptive to users’ capabilities.
Pemetaan Disparitas Stunting di Jawa Timur dengan Spatial Autoregressive Model (SAR) dan Spatial Error Model (SEM) Haris, M Syauqi; Risqy Siwi Pradini; Ahsanun Naseh Khudori
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 1 (2025): September 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i1.8877

Abstract

Stunting masih menjadi masalah kesehatan masyarakat yang signifikan di Indonesia, khususnya di Provinsi Jawa Timur, di mana terdapat disparitas yang mencolok dalam prevalensi stunting. Penelitian ini bertujuan untuk mengevaluasi distribusi spasial stunting dan mengidentifikasi faktor-faktor yang mempengaruhinya, dengan mempertimbangkan perbedaan geografis antarwilayah. Untuk mencapai tujuan tersebut, penelitian menggunakan pendekatan analisis spasial dengan menggunakan data sekunder dari 38 kabupaten dan kota di Jawa Timur. Analisis ini melibatkan beberapa tahap, termasuk eksplorasi pola geografis melalui indeks autokorelasi global Moran's I dan analisis LISA, diikuti dengan pemodelan regresi spasial menggunakan Spatial Autoregressive Model (SAR) dan Spatial Error Model (SEM) berdasarkan matriks bobot tetangga terdekat. Klaster hotspot diidentifikasi di wilayah Tapal Kuda, sementara klaster outlier ditemukan di Sampang dan Tulungagung. Selain itu, model regresi spasial menunjukkan kinerja yang lebih baik dibandingkan dengan model Ordinary Least Squares (OLS), dengan nilai pseudo R² SAR sebesar 0,7203 dan penurunan Akaike Information Criterion (AIC) menjadi 259,05. Hasil analisis menunjukkan bahwa inisiasi menyusui dini, cakupan ibu hamil, dan pemberian tablet tambah darah merupakan faktor signifikan yang mempengaruhi prevalensi stunting (p <0,05). Secara keseluruhan, model spasial memberikan representasi yang lebih akurat tentang pengaruh spasial di seluruh wilayah dibandingkan dengan regresi linier biasa, sehingga dapat menjelaskan variasi geografis stunting dengan lebih baik. Temuan ini menyoroti kebutuhan mendesak untuk mengembangkan kebijakan berbasis wilayah yang disesuaikan dengan karakteristik spasial yang unik di setiap wilayah. Penelitian ini berkontribusi pada bidang studi spasial dalam epidemiologi gizi dan menawarkan dasar ilmiah untuk mengimplementasikan intervensi kesehatan masyarakat yang lebih tepat sasaran.
Convolutional neural network model for fingerprint-based gender classification using original and degraded images Pradini, Risqy Siwi; Kusuma, Wahyu Teja; Budi, Agung Setia
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1350-1358

Abstract

Fingerprint-based gender classification is a crucial component of soft biometrics, providing valuable additional information to narrow the search space in forensic investigations and large-scale identification systems. Although deep learning models, particularly convolutional neural networks (CNNs), have demonstrated significant potential, performance validation is typically performed on high-quality fingerprint images. This creates a gap between laboratory results and real-world applications, where fingerprint evidence is often found in a degraded state, such as smudged, distorted, or partially damaged. This study attempts to bridge this gap by proposing a more realistic training approach. We design a lightweight and computationally efficient CNN and train it on a comprehensive combined dataset. The main contribution of this study lies in the data training strategy, which explicitly combines real and synthetically modified fingerprint images from the Sokoto coventry fingerprint (SOCOFing) dataset into a single, unified training set. Experimental results show that the proposed model achieves very high classification accuracy (97.39%) on a test set that also includes a combination of original and degraded images. This finding not only confirms the effectiveness of diverse data-based training to produce more robust models but also establishes a new benchmark for fingerprint based gender classification research under conditions more representative of practical scenarios.
Komparasi Distance Measure pada K-Means dalam Klasterisasi Peserta KB Aktif Anshori, Mochammad; Ningrum, Afifah Vera Ferencia Fitria; Pradini, Risqy Siwi
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 11 No. 1 (2026): January 2026
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.5006

Abstract

The rapid population growth in Indonesia poses significant challenges to public welfare, economic stability, and sustainable development. The Family Planning program aims to regulate population growth through various contraceptive methods; however, participation rates often differ across regions. Understanding these variations is crucial for designing targeted interventions. This study investigates how different distance measures in the K-Means clustering algorithm affect the segmentation quality of KB participants in Kalirejo Village, Lawang District. Eight distance metrics—Euclidean, Manhattan, Minkowski, Chebyshev, Mahalanobis, Bray-Curtis, Canberra, and Cosine—were compared using standardized data from the local BKKBN office (January–September). Cluster validity was evaluated using the Silhouette Coefficient across k=2–10. Results show that the Manhattan distance with k=2 achieved the best clustering quality (SC = 0.7191), effectively distinguishing participant groups by contraceptive method preference. The study highlights the importance of selecting suitable distance measures to improve data-driven policy and decision-making in family planning management.
Website Development of Sarwa Adem Mulya Cooperative as a Digital Platform for Promotion and Education of Ruminant Livestock Farmers: Pengembangan Website Koperasi Sarwa Adem Mulya sebagai Sarana Promosi dan Edukasi Digital Peternak Ruminansia M Syauqi Haris; Risqy Siwi Pradini; Mochammad Anshori
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 9 No. 3 (2025): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

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

Abstract

Koperasi Multi Pihak Sarwa Adem Mulya is a ruminant livestock-based cooperative located in Malang, East Java. The cooperative has great potential for business development but faces challenges in utilizing information technology, particularly in digital promotion and education. This community service activity aims to develop a cooperative website using the WordPress-based Content Management System (CMS) to strengthen its position in the digital era. The implementation method includes needs analysis, website design and development, training for cooperative administrators, as well as monitoring and evaluation of website usage effectiveness. The developed website features key components such as a cooperative profile, livestock product catalog, educational modules, and basic e-commerce integration. The results show that the website has been successfully implemented through the cooperative's official domain, and administrators are able to independently manage the content. Furthermore, an increase in digital literacy among administrators was observed based on pre-test and post-test evaluations. This website is expected to serve as a sustainable medium for promotion and education, and as a replicable model for the digitalization of other livestock cooperatives.
Development of a Mobile-Based Ruminant Livestock Monitoring System at Sarwa Adem Mulya Multi-Party Cooperative M Syauqi Haris; Risqy Siwi Pradini; Achmad Jaelani Rusdi
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 9 No. 4 (2025): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

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

Abstract

The Sarwa Adem Mulya Multi-Party Cooperative, located in Dusun Petung Wulung, Toyomarto Village, Singosari District, Malang Regency, oversees more than 80 ruminant livestock farmers with 13 key livestock management activities. Until now, record-keeping has been conducted semi-manually using Google Forms, which presents several challenges: slow processing, low accuracy, and limited accessibility for farmers with low digital literacy. This community service program aims to develop a mobile application based on a Progressive Web App (PWA) that facilitates real-time livestock recording, integrates with the cooperative’s dashboard, and can be used offline. The implementation methodology includes socialization, training, technology deployment, mentoring, and evaluation. As a result, over 70% of cooperative members participated in the training, and 57 farmers actively used the application, recording more than 1,200 activity entries within the first three months. Evaluation indicates a 25% improvement in data recording accuracy, a significant reduction in data duplication, and the availability of an analytical dashboard for the cooperative. This program supports SDG (Sustainable Development Goals) 2 (Zero Hunger), SDG 3 (Good Health and Well-Being), SDG 8 (Decent Work and Economic Growth), as well as SDG 13 and 15 (Climate Action and Life on Land).
Peningkatan Akurasi Rekomendasi Dokter pada Kondisi Data Sparsity Menggunakan Algoritma Content-Based Filtering Alwan Prasetya; Ahsanun Naseh Khudori; Risqy Siwi Pradini
Jurnal Buana Informatika Vol. 16 No. 01 (2025): Jurnal Buana Informatika, Volume 16, Nomor 01, April 2025
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v16i01.10836

Abstract

Perkembangan aplikasi layanan kesehatan seperti Halodoc, Alodokter, dan Klikdokter telah menyediakan sistem rekomendasi yang memudahkan pasien untuk menentukan dokter yang relevan. Namun, rekomendasi dokter yang relevan masih menjadi tantangan. Salah satu permasalahannya adalah data sparsity, yaitu kelangkaan atribut data yang menyebabkan akurasi sistem rekomendasi bekerja kurang akurat. Penelitian ini mengembangkan sistem rekomendasi dokter menggunakan pendekatan Content-Based Filtering (CBF) untuk melakukan rekomendasi dokter sesuai dengan preferensi pasien dengan mempertimbangkan lima atribut utama: spesialisasi, rating, biaya konsultasi, lama praktik, dan jenis kelamin. Aturan imputasi data dan pembobotan atribut telah diimplementasikan untuk meningkatkan akurasi sistem rekomendasi. Hasil dari analisis data menunjukan teknik tersebut telah menurunkan Mean Absolute Error (MAE) dari 0,142 menjadi 0,102 dan Root Mean Squared Error (RMSE) dari 0,205 menjadi 0,150, sehingga teknik yang diimplementasikan meningkatkan sistem rekomendasi dokter dengan kondisi data sparsity.
Co-Authors ACHMAD JAELANI RUSDI Agung Setia Budi, Agung Setia Agus Widodo Ahsanun Naseh Khudori Ali Hasan, Hildan Adisqi Alwan Prasetya Apriyani Puji Hastuti Bintang Pramudya Cantika Nur Previana Danis Rifa Nurqotimah Dinda Chesar Putri Ramadhani Dio Wahyu Saputra Fery Fajar, Muhammad Geraldo, Tostes Henokh Kristiawan Hilda Nuzulul Mujaddidah Indra Dharma Wijaya Irnanda Septian Ika Putri Jenike Gracelya Noke Kurniawan, Ardhiles Wahyu M. Syauqi Haris Makhrus, Moh Ali Makhrus, Moh. Ali Marilia, Busatto Mawardi, Ade Bagus Mayang Anglingsari Putri, Mayang Anglingsari Mochamad Anshori Nindynar Rikatsih Ningrum, Afifah Vera Ferencia Fitria Nugroho Teguh Yuono Prasetya, Alwan Putri Salsabila, Dhea Putri, Irnanda Septian Ika Putriana, Rena Rahmania Ambarika Rika, Faurika Roesardhyati, Ratna Salsabila, Dhea Putri Saputra, Dio Wahyu Saputra, Zainal Setia Budi, Agung Shaktyanti, Frenchyani Anggi Trihapningsari , Denisha Trihapningsari Wahyu Tejakusuma, Wahyu Wisam Syahputra, Kelvin