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All Journal ComEngApp : Computer Engineering and Applications Journal JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jurnal Varian ESTIMASI: Journal of Statistics and Its Application Jurnal Diferensial HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Enthusiastic : International Journal of Applied Statistics and Data Science MATHunesa: Jurnal Ilmiah Matematika Buletin Sistem Informasi dan Teknologi Islam Journal of Information Systems and Technology Research Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Journal of Data Mining and Information Systems Kohesi: Jurnal Sains dan Teknologi Indonesian Journal on Data Science Parameter: Jurnal Matematika, Statistika dan Terapannya Emerging Statistics and Data Science Journal
Shindi Shella May Wara
Universitas Pembangunan Nasional Veteran Jawa Timur
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Public Health Social Sciences Other

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Klasifikasi Tingkat Kesejahteraan Kabupaten/Kota di Jawa Barat, Jawa Tengah, dan Jawa Timur Menggunakan Regresi Logistik Multinomial: Klasifikasi Tingkat Kesejahteraan Kabupaten/Kota di Jawa Barat, Jawa Tengah, dan Jawa Timur Menggunakan Regresi Logistik Multinomial Firqi Nashrullah, Ahmad; Kresna Wira Yudha, I Nyoman; Terza Damaliana, Aviolla; Shindi Shella May Wara; Dwi Mahardhika, Rivaldi
Emerging Statistics and Data Science Journal Vol. 3 No. 3 (2025): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol3.iss.3.art23

Abstract

Tingkat kesejahteraan daerah menjadi salah satu indikator utama dalam menilai kemajuan Pembangunan wilayah. Penelitian ini bertujuan untuk mengklasifikasikan kesejahteraan seluruh daerah setingkat kabupaten dan kota yang berada di wilayah Provinsi Jawa Barat, Jawa Tengah, serta Jawa Timur berdasarkan kelompok Indeks pembangunan manusia yang terdiri atas empat kategori, yaitu rendah, sedang, tinggi, mdan sangat tinggi menggunakan regresi logistik multinomial. Analisis melibatkan persentase penduduk miskin, rasio ketimpangan, angka harapan hidup, pengeluaran per kapita, kepadatan penduduk, dan akses sanitasi layak. Data diperoleh dari Badan Pusat Statistik tahun 2023. Hasil deskriptif menunjukkan 69 wilayah termasuk kategori tinggi, 17 kategori sedang, dan 14 kategori sangat tinggi. Uji statistik mengonfirmasi hubungan signifikan semua variabel dan menunjukkan bahwa perbaikan akses sanitasi serta peningkatan harapan hidup meningkatkan indeks pembangunan manusia suatu wilayah. Model menghasilkan akurasi 86,67 persen. Hasil analisis ini dapat dimanfaatkan landasan objektif untuk menyusun strategi pembangunan wilayah yang efektif.
ANALYSIS OF EDUCATION FUNDING ALLOCATION AND STUDENT ENROLLMENT DIFFERENCES BETWEEN SMA AND SMK STUDENTS IN INDONESIA : RM MANOVA APPROACH Zahwa, Aniq Farichatus; Ramadhani, Dafinah; Wara, Shindi Shella May; Damaliana, Aviolla Terza
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 1 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i1pp167-174

Abstract

The Indonesia Smart Program (PIP) is one of the government's efforts to improve access to education for underprivileged students. The purpose of this study is to examine how PIP educational aid was distributed and how successful it was in Indonesia in 2022 at the Senior High School (SMA) and Vocational High School (SMK) levels. The method used is Repeated Measures Multivariate Analysis of Variance (RM Manova) for education. The research data was obtained from the official government data portal of Indonesia (data.go.id). The results of the study do not show any significant differences in the distribution of assistance between SMA and SMK across various regions. Further research is needed to consider other factors that may have an impact.
Application of VAR-GARCH for Modeling the Causal Relationship of Stock Prices in the Mining Sub-sector Nasrudin, Muhammad; Setyowati, Endah; May Wara, Shindi Shella
Jurnal Varian Vol. 8 No. 1 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i1.4239

Abstract

Accurate modeling is expected to minimize risk and maximize profit in investment portfolios, one ofwhich is in stock price modeling. This research aims to model the causal relationship between stockprices using the Vector Autoregressive - Generalized Autoregressive Conditional Heteroskedasticity(VAR-GARCH) model. The VAR-GARCH model is used to overcome heteroscedasticity and modeldynamic volatility. The data used for the modeling consists of daily stock prices from July 2023 toMay 2024 for mining sub-sector companies listed on the Jakarta Islamic Index (JII), including ADMR,ADRO, and ANTM. The results showed that the VAR(1) model is stable, but this model indicates thepresence of heteroskedasticity or ARCH effects. Therefore, the VAR(1) model was combined with theGARCH model, and the results showed that the best model is VAR(1)-GARCH(1,1). The VAR(1)-GARCH(1,1) model is appropriate and meets the homoskedasticity assumptions for modeling the stockprices of the mining sub-sector in the Jakarta Islamic Index (JII). This indicates that the VAR-GARCHmodel could successfully handle the volatility of stock price data. In general, this research is in linewith previous research, i.e., the VAR-GARCH model showed a better model for capturing the volatilitypatterns in the data.
Analisis Sentimen Komentar Pengguna Terhadap Aplikasi Prime Video Di Google Playstore Dengan Pendekatan Machine Learning Pradipta, Alvino Hadiyan; Nugroho, Muhammad Rafli Feandika; Putri, Maretta Fairuz Luthfia Winoto; Wara, Shindi Shella May; Damaliana, Aviolla Terza
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 6, No 4 (2025)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v6i4.2856

Abstract

Analisis sentimen terhadap ulasan pengguna menjadi penting dalam memahami persepsi publik terhadap sebuah aplikasi digital. Analisis ini dilakukan untuk mengklasifikasikan 1000 komentar yang terdiri dari komentar positif dan negatif dari pengguna aplikasi Prime Video yang terdapat di Google Play Store. Tujuan penelitian ini adalah untuk membantu pengembang aplikasi memahami pendapat pengguna dalam jumlah besar secara otomatis, tanpa harus membaca komentar pengguna satu per satu. Tahapan awal dilakukan melalui proses pra pemrosesan teks, yang meliputi pembersihan data, normalisasi kata, case folding, stemming, dan filtering. Selain itu, visualisasi Word Cloud digunakan untuk mengidentifikasi kata-kata yang sering muncul dalam komentar pengguna. Analisis dilanjutkan dengan penerapan metode klasifikasi untuk menentukan sentimen komentar. Dalam penelitian ini, tiga metode pembelajaran mesin yaitu Neural Network (NN), Support Vector Machine (SVM) dan Naive Bayes Classifier (NBC) digunakan dan dibandingkan untuk memperoleh hasil klasifikasi terbaik. Hasil menunjukkan bahwa metode SVM memberikan tingkat akurasi tertinggi yaitu sebesar 89,5%, disusul dengan metode NN sebesar 87% dan NBC sebesar 75% dalam mengklasifikasikan sentimen komentar pengguna. Penelitian ini menyimpulkan bahwa pendekatan berbasis machine learning efektif digunakan dalam mengidentifikasi dan mengelompokkan opini pengguna terhadap aplikasi digital secara otomatis.
Segmentasi Faktor Perceraian berdasarkan Provinsi di Indonesia Tahun 2024 dengan K-Means dan DBSCAN Rizkiyah, Selly; Indira; Putri, Milla Akbarany Bakhtiar; Wara, Shindi Shella May; Saputra, Wahyu Syaifullah Jauharis
INDONESIAN JOURNAL ON DATA SCIENCE Vol. 3 No. 2 (2025): Indonesian Journal On Data Science
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/ijds.v3i2.1654

Abstract

Divorce is a complex social phenomenon that continues to increase in Indonesia. Based on data from 34 provinces, divorce is influenced by various factors, both internal and external to the household. This research aims to describe the main factors causing divorce based on national data and review relevant literature using machine learning methods, especially unsupervised learning techniques in the form of clustering. The dominant factors found include constant disputes and arguments, economic problems, domestic violence, abandonment of one of the parties, and infidelity. This research uses K-Means and DBSCAN algorithms to compare the results. It is known that the best modeling with Silhoutte Score comparison is DBSCAN of 0.331. DBSCAN with optimal clusters was obtained from a combination of epsilon parameter 2.9 and minimum sample 2. The clustering results were then further analyzed to evaluate the data distribution and identify the dominant characteristics in each cluster. These findings indicate the need for a multidisciplinary approach in understanding and addressing divorce issues in Indonesia in order to reduce the divorce rate and improve the quality of family life.
Optimalisasi Deteksi Wajah Real-Time Menggunakan HAAR Cascade Classifier berbasis OpenCV Alfan Rizaldy Pratama; Muhammad Nasrudin; Andri Faudzan Adziima; Shindi Shella May Wara
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i1.15485

Abstract

Nowadays, the face is one of the features that is widely used in various aspects of life such as security which includes access control and surveillance, biometrics which includes attendance systems, and many others. The obstacles found in implementing this are generally about speed performance when detecting, this is vital because if the process takes a long time, misconceptions and system errors will occur. HAAR Cascade Classifier is one of the most widely used lightweight face detection algorithms. In this research, by analyzing the use of grayscale color compared to RGB, a performance increase of 6.17% is obtained with an average FPS on RGB of 25.63 while on grayscale it is 27.21.
Detection of Ventricular Septal Defect in Pediatric Cardiac Ultrasound Videos Using Parasternal View and Faster R-CNN Nasrudin, Muhammad; Shindi Shella May Wara; Amri Muhaimin; Nur Indah Nirmalasari; Mega Rizkya Arfiana
Computer Engineering and Applications Journal Vol. 15 No. 1 (2026)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v15i1.1334

Abstract

Congenital heart disease (CHD), particularly ventricular septal defect (VSD), remains a major contributor to pediatric morbidity, while echocardiographic diagnosis is highly dependent on operator expertise and image quality. This study examines the feasibility of an object-detection-based intelligent imaging framework for localizing VSD in pediatric cardiac ultrasound videos acquired from the parasternal long-axis view. Rather than proposing a novel detection algorithm, this work adopts a system-oriented approach by evaluating the Faster R-CNN framework under practical clinical constraints, including limited annotated data and heterogeneous ultrasound characteristics. Three convolutional neural network backbones such as ResNet50, ResNet101, and Inception-ResNet V2 are comparatively analyzed within a unified detection pipeline. Experimental results indicate that the ResNet101-based model achieves the highest localization performance at an intersection-over-union threshold of 0.5, while ResNet50 provides more consistent precision across stricter localization thresholds. Although false-positive detections are observed in acoustically challenging frames, the proposed framework maintains real-time feasibility at approximately 7–8 frames per second. The findings offer practical insights into accuracy–efficiency trade-offs and backbone selection for the development of clinically aware intelligent echocardiography systems, supporting the application of information and communication technology in pediatric cardiac imaging.
Sharpe Ratio-Based Dynamic Crypto Asset Allocation with Trend Filtering Using SMA Fauzan Adziima, Andri; Wara, Shindi Shella May; Nasrudin, Muhammad; Pratama, Alfan Rizaldy
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 6 Issue 1, April 2026
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol6.iss1.art1

Abstract

This paper proposes a dynamic cryptocurrency asset allocation strategy that combines Sharpe Ratio-based weighting with trend filtering using the Simple Moving Average (SMA) of Bitcoin (BTC). The model reallocates capital among a portfolio of seven major cryptocurrencies (BTC, ETH, BNB, SOL, TON, TRX, XRP) every three days, conditional on BTC trading above its respective SMA threshold (50-day, 100-day, or 200-day). When BTC trends below the SMA, the strategy shifts fully to USDT to minimize downside risk. Using historical data from January 1, 2024, to January 1, 2025, the study evaluates performance across three SMA configurations and benchmarks against a buy-and-hold baseline. Results show that the SMA-50 strategy achieved the highest cumulative return (+231.51%) and Sharpe Ratio (2.51), significantly outperforming both the longer SMA-based models and the baseline average return (+132.14%). Risk analysis indicates that shorter SMA windows allow more responsive exposure during market uptrends but increase short-term volatility. Overall, the findings support the use of hybrid strategies combining trend-following filters and risk-adjusted allocation for managing crypto portfolios in volatile environments.
Pengembangan Algoritma Sharpe Ratio dengan Integrasi Filter Tren SMA dalam Strategi Portofolio Aset Kripto Andri Fauzan Adziima; Shindi Shella May Wara; Muhammad Nasrudin; Alfan Rizaldy Pratama
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 1 (2025): Juni 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i1.383

Abstract

Penelitian ini mengusulkan sebuah strategi alokasi aset kripto yang bersifat dinamis, dengan menggabungkan pembobotan berdasarkan Sharpe Ratio dan penyaringan tren menggunakan indikator Simple Moving Average (SMA) dari Bitcoin (BTC). Model ini melakukan alokasi ulang modal setiap tiga hari pada tujuh aset kripto utama (BTC, ETH, BNB, SOL, TON, TRX, XRP), dengan ketentuan bahwa harga BTC berada di atas ambang SMA tertentu (50 hari, 100 hari, atau 200 hari). Apabila BTC berada di bawah nilai SMA tersebut, seluruh portofolio secara otomatis dialihkan ke USDT untuk menekan risiko penurunan nilai. Studi ini menggunakan data historis dari 1 Januari 2024 hingga 1 Januari 2025 dan menguji performa model dalam tiga konfigurasi SMA, lalu dibandingkan dengan strategi dasar buy-and-hold. Hasil menunjukkan bahwa strategi dengan parameter SMA 50 hari menghasilkan return kumulatif tertinggi (+231,51%) serta rasio Sharpe terbaik (2,51), jauh melampaui model dengan SMA yang lebih panjang maupun rata-rata return dari strategi dasar (+132,14%). Analisis risiko mengindikasikan bahwa jendela SMA yang lebih pendek memberikan respons yang lebih cepat terhadap tren naik pasar, meskipun disertai dengan peningkatan volatilitas jangka pendek. Secara keseluruhan, temuan ini menguatkan efektivitas strategi hibrida yang mengombinasikan penyaringan tren dengan alokasi berbasis risiko dalam pengelolaan portofolio kripto di tengah kondisi pasar yang fluktuatif.
Optimasi Sistem Antrian Pada Medical Center ITS Dengan Simulasi Discrete Event Dan Response Surface Methodology Shindi Shella May Wara; Muhammad Nasrudin; Andri Fauzan Adziima; Alfan Rizaldy Pratama
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 1 (2025): Juni 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i1.411

Abstract

Medical Center ITS berfungsi sebagai unit rawat jalan yang melayani pemeriksaan, tindakan medis, penunjang medis, dan rujukan bagi civitas academica ITS serta masyarakat umum dengan biaya yang terjangkau. Penelitian ini bertujuan untuk mengoptimalkan sistem antrean di Medical Center ITS, yang sering menghadapi antrean panjang dan berdampak pada waktu tunggu pasien serta efisiensi pelayanan, menggunakan pendekatan simulasi diskrit. Data primer, meliputi waktu antar kedatangan dan waktu pelayanan (resepsionis, poli umum, poli gigi, resep, dan pengambilan obat), dikumpulkan secara empiris untuk memodelkan sistem antrean berbasis kejadian. Model simulasi yang dikembangkan secara akurat merepresentasikan seluruh alur pelayanan. Hasil simulasi menunjukkan bahwa sistem pelayanan saat ini belum optimal dengan hanya satu server di poli umum dan satu di poli gigi. Berdasarkan temuan, skenario penambahan server pada poli gigi menjadi empat dan tetap satu server di poli umum diusulkan sebagai konfigurasi optimum. Implementasi skenario ini terbukti secara signifikan mengurangi waktu tunggu rata-rata pasien dan meningkatkan tingkat utilitas sumber daya. Penelitian ini menegaskan bahwa simulasi diskrit adalah alat pengambilan keputusan yang efektif untuk meningkatkan kualitas dan efisiensi pelayanan di fasilitas kesehatan.
Co-Authors AA Sudharmawan, AA Abda Abda Abdillah, Indah Rahma Adziima, Andri Fauzan Ahmad, Davin Anezta Alfan Rizaldy Pratama Alvino Hadiyan Pradipta Alzam, Muhammad Arsyad Amellia Harmaimun Hidayah Amri Muhaimin Ananta, Aditya Putra Andri Faudzan Adziima Andri Fauzan Adziima Anugrah, Muhammad Cahya Raka Aviolla Terza Damaliana Aviolla Terza Damaliana Damaliana, Aviolla Terza Diana Novitasari Dwi Mahardhika, Rivaldi Elmaliyasari, Shifa Endah Setyowati Fauzan Adziima, Andri Fernando, Moch. Firman Firqi Nashrullah, Ahmad Indira Kaffi, Laisal Karina Auralia Kartika Maulida Hindrayani Khairunisa, Adenda Kresna Wira Yudha, I Nyoman Kurniawan, Muhammad Erlangga Mahardhika, Rivaldi Dwi Maretta Fairuz Luthfia Winoto Putri Marthalia Kusumarima Maulana, Mohammad Hikmal Maulida Hindrayani, Kartika Mega Rizkya Arfiana Muhammad Nasrudin Muhammad Nasrudin Muhammad Rafli Feandika Nugroho Nabila Yudhitya Larasati Nashrullah, Ahmad Firqi Nugroho, Muhammad Rafli Feandika Nur Indah Nirmalasari Pradipta, Alvino Hadiyan Pratiwi, Nanda Aulia Putri, Maretta Fairuz Luthfia Winoto Putri, Milla Akbarany Bakhtiar rachmanto, Nugroho Fajar Ramadhani, Dafinah Rhomaningtias, Lina Rizkiyah, Selly Rusdiyanto, Nur Rahmat Saputra, Wahyu Syaifullah Jauharis Terza Damaliana, Aviolla Vannesa Nathania Wahyu Syaifullah Jauharis Saputra Wiyono, Farhan Syah Putra Zahwa, Aniq Farichatus