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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro Jurnal Pseudocode Jurnal Pengabdian UntukMu NegeRI Jurnal Sains dan Informatika INOVTEK Polbeng - Seri Informatika JRST (Jurnal Riset Sains dan Teknologi) Conference SENATIK STT Adisutjipto Yogyakarta CYBERNETICS Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Building of Informatics, Technology and Science Indonesian Journal of Business Intelligence (IJUBI) International Journal of Informatics and Computation Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS Masyarakat Berdaya dan Inovasi Jurnal Pengabdian Masyarakat Kebidanan HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Jurnal Informatika Terpadu Journal of Information Technology (JIfoTech) JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Ilmu Komputer untuk Masyarakat PELS (Procedia of Engineering and Life Science) Digital Transformation Technology (Digitech) Jurnal Ilmiah Teknik Informatika dan Komunikasi Journal Of Artificial Intelligence And Software Engineering Fahma : Jurnal Informatika Komputer, Bisnis dan Manajemen
Silmina, Esi Putri
Program Studi Teknologi Informasi Universitas ‘Aisyiyah Yogyakarta
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Pelatihan Jaringan Komputer Menggunakan Cisco Packet Tracer di SMK Ar Rahmah Bantul hardiani, tikaridha; Esi Putri Silmina; Danur Wijayanto
DHARMA RAFLESIA Vol 21 No 1 (2023): JUNI (ACCREDITED SINTA 5)
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/dr.v21i1.25103

Abstract

SMK Ar-Rahmah berdiri pada tanggal 24 Oktober 2011. Sekolah berlokasi di komplek Pondok Pesantren Ar-Rahmah. SMK ini di bawah naungan Yayasan Bani Fakhruddin yang berlokasi di Kedungbule, Trimurti, Srandakan, Bantul, Provinsi Daerah Istimewa Yogyakarta. SMK Ar-Rahmah hanya memiliki penjurusan Teknik Komputer dan Jaringan. Untuk meningkatkan kemampuan lulusan, diperlukan pendalaman pengetahuan dan keterampilan mengenai Jaringan Komputer. Oleh sebab itu perlu diadakannya pelatihan jaringan komputer dengan memberikan penjelasan dasar-dasar Jaringan Komputer dan simulasinya menggunakan Aplikasi Cisco Packet Tracer. Pelatihan dilakukan dengan memberikan persoalan Jaringan seperti di dunia nyata yang kemudian disimulasikan dengan menggunakan Cisco Packet Tracer , sehingga dapat lebih memberikan gambaran dan meningkatkan kemampuan serta keterampilan siswa dalam bidang Jaringan Komputer. Peserta sangat antusias dengan materi yang diberikan dikarenakan sesuai dengan penjurusan dan hasil evaluasi  menunjukkan 75% peserta puas dengan pelatihan yang diberikan karena peserta mendapat wawasan lain selain pelajaran dari sekolah.
Prediction of Increased Mobility of Yogyakarta Residents in Controlling the Spread of COVID-19 Cases Using the Neural Network Algorithm Dana, Syaiful Rachmat; Silmina, Esi Putri
SENATIK STT Adisutjipto Vol 7 (2022): Generation Z's Participation in Aerospace
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v7i0.452

Abstract

High mobility in D.I Yogyakarta arises from tourist visits and educational activities as well as community activities which are quite dense. High mobility and density will affect the spread of COVID-19 in D.I Yogyakarta. Early preparation is needed to predict displacement in D.I Yogyakarta so that policies can be implemented as early as possible to prevent the emergence of a new wave of spread of COVID-19 in D.I Yogyakarta. In this study, the Neural Network Algorithm with Backpropagation model is used to predict the mobility of Yogyakarta D.I data from September 2021 to January 2022. To form the Neural Network Algorithm model using Rapidminer software with prediction criteria of accuracy and kappa. The prediction accuracy value obtained is 95.49% and the kappa value is 0.908. The results of this study indicate that the predictive value of Yogyakarta D.I mobility tends to be high.
Visualization of COVID-19 Data in Yogyakarta City Using Data Studio Cendana, Willy Pratama; Silmina, Esi Putri
SENATIK STT Adisutjipto Vol 7 (2022): Generation Z's Participation in Aerospace
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v7i0.444

Abstract

The Corona virus, which has a very fast spread rate, has spread to all provinces in Indonesia, including in the Special Region of Yogyakarta. Information related to the development of COVID-19 data is needed by the government to handle COVID-19 cases. The purpose of this study is to visualize COVID-19 data in the form of Confirmed, Died, and Recovered data in the City of Yogyakarta, which later the results of the visualization can assist the government in making policies related to handling COVID-19 cases in the City of Yogyakarta. The research method used is visualization data processing using Data Studio, the data used is from October 2021 to January 2022. The result of the research is visualization of data in the form of a COVID-19 dashboard in the City of Yogyakarta which displays Confirmed, Died, and Recovered Cases. The visualization results show that in October and November, the graph results are quite high, while the graph in December, the Confirmed and Died graph is almost non-existent or zero, while the Healing graph is quite increasing.
Promosi Desa Berbasis Web Menggunakan Metode Prototype Silmina, Esi Putri; Bin Riedho, Al Bukhari
Digital Transformation Technology Vol. 4 No. 1 (2024): Periode Maret 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i1.4480

Abstract

Desa Hargorejo adalah salah satu desa yang terletak di Kecamatan Kapanewon Kokap, Kabupaten Kulon Progo, Provinsi Daerah Istimewa Yogyakarta. Desa ini memiliki potensi desa berupa wisata alam dan produk UMKM. Dikarenakan belum tersebarnya informasi secara luas membuat potensi desa kurang dikenal oleh masyarakat luas. Penelitian in bertujaun untuk mengenalkan potensi Desa Hargorejo agar diketahui oleh masyarakat luas, sehingga dengan tersebarnya informasi potensi Desa Hargorejo dapat mendatangkan banyak pengunjung yang ingin menikmati wisata alam yang ditawarkan serta memperbanyak pelanggan UMKM Desa Hargorejo. Website menjadi solusi atas permasalahan yang dihadapi oleh Desa Hargorejo sebagai media promosi yang memaparkan informasi terkait profil, paket-paket wisata dan katalog produk UMKM. Pembangunan website menggunakan CMS Wordpress yang didukung oleh plugin yang banyak dan open source sehingga dapat mempercepat dan mempermudah dalam hal pengembangan selain itu juga website-website besar sudah banyak yang menggunakan CMS Wordpress.
PROTOTYPE IOT UNTUK PEMANTAUAN NUTRISI DAN PH PADA HIDROPONIK MENGGUNAKAN ESP32 DI KEBUN HIDROPINIK VEFAR YOGYAKARTA Wijayanto, Danur; Silmina, Esi Putri; Firdonsyah, Arizona; Aditiya, Aqni Alam
HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Vol. 15 No. 2 (2024): Jurnal HOAQ - Teknologi Informasi
Publisher : STIKOM Uyelindo Kupang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52972/hoaq.vol15no2.p100-106

Abstract

Sektor pertanian di Indonesia menghadapi tantangan karena berkurangnya lahan pertanian, Upaya yang dilakukan untuk mengatasi hal tersebut dengan menerapkan Hidroponik. Salah satu metode hidroponik adalah Metode NFT, yang telah diterapkan di Kebun Vefar Yogyakarta. Namun dalam penerapan Hidroponik dengan Metode NFT ini sering mengalami kendala berupa gagal panen yang disebabkan oleh sistem pemantauan nutrisi dan pH yang masih manual, belum dilakukan secara berkala, keterbatasan waktu dan tenaga dari pemilik serta karyawan, ditambah dengan luasnya lahan kebun hidroponik, menjadi faktor penghambat dalam pemantauan yang intensif. Pemantauan secara real-time terhadap nutrisi air dan pH air juga sangat penting untuk memaksimalkan hasil produksi. Untuk mengatasi masalah ini, diperlukan sistem pemantauan berbasis IoT yang memanfaatkan sensor pH dan TDS meter, Wemos D1 R32 sebagai mikrokontroler, dengan menggunakan Platform Antares dan Aplikasi Mobile apps MIT APP Inventor. Hasil menunjukkan prototype dapat memantau kondisi pH dan jumlah partikel padatan yang terlarut dalam air dengan pengujian selama satu hari dan keberhasilan seluruh hasil skenario pengujian. Nilai pH dan TDS pada larutan nutrisi menunjukkan fluktuasi yang relatif stabil dalam rentang waktu pengukuran. Nilai pH rata-rata berkisar antara 6.9 hingga 7.1, sedangkan nilai TDS berada di sekitar 1674-1828 ppm.   The agricultural sector in Indonesia is facing challenges due to the decreasing amount of agricultural land. Hydroponics has been implemented as a solution to address this issue. One method of hydroponics is the Nutrient Film Technique (NFT), which has been applied in Vefar Garden, Yogyakarta. However, the implementation of NFT hydroponics often encounters obstacles such as crop failures caused by manual nutrient and pH monitoring systems, which are not conducted regularly. Limited time and labor from owners and employees, coupled with the vast area of the hydroponic garden, hinder intensive monitoring. Real-time monitoring of water nutrients and pH is crucial for maximizing production. To overcome these problems, an IoT-based monitoring system was developed using pH and TDS sensors, a Wemos D1 R32 microcontroller, the Antares  Platform, and the MIT App Inventor mobile app. The results show that the prototype can monitor pH conditions and the number of solid particles dissolved in water with testing for one day and the success of all test scenario.
Deteksi Bahan Pangan Tinggi Protein Menggunakan Model You Only Look Once (YOLO) Arjun, Restu Agil Yuli; Silmina, Esi Putri
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6889

Abstract

Stunting has a high prevalence of 21.6% from the government target of 14% and is one of the health problems in Indonesia. Lack of nutrition, especially protein, is the main cause that plays a role in child growth. One of the preventive solutions is to provide protein-rich complementary foods (MP-ASI). To enhance this solution, technology that can swiftly and precisely identify high-protein food components is imperative. This research seeks to create a high-protein food detection model utilizing the YOLOv11 framework, chosen for its efficacy in object detection, particularly in intricate environments and with overlapping items. The research methodology includes several stages: dataset collection and annotation, data pre-processing, model training, model evaluation, and model testing. The dataset is divided into three parts: 70% for the training set, 20% for the validation set, and 10% for the test set. The YOLOv11s model is used for training. Evaluation is based on precision, recall, and mean Average Precision (mAP) metrics to ensure the model’s detection accuracy. The evaluation results indicate a precision of 96%, recall of 92.3%, mAP50 of 96.4%, and mAP50-95 of 81.5%. During testing, the model achieved a success rate of 98.2%. These results demonstrate the model’s potential in detecting protein-rich foods, which could significantly contribute to addressing malnutrition and stunting.
Comparative Analysis of K-Means and K-Medoids Algorithms in New Student Admission Tikaridha Hardiani; Esi Putri Silmina
International Journal of Informatics and Computation Vol. 6 No. 2 (2024): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v6i2.91

Abstract

Universitas ‘Aisyiyah Yogyakarta is one of the private universities in Yogyakarta. The large number of private universities in Yogyakarta has intensified the competition for new student admissions. In this situation, every university requires the right strategy to attract prospective students. One of the strategies used by Universitas ‘Aisyiyah Yogyakarta to capture the interest of potential students is by conducting direct promotions to schools in Yogyakarta, Java, and Sumatra. In the admission process for new students in the Information Technology Study Program, a common problem arises, which is the number of prospective students who do not complete re-registration each year. These students pass the selection and are declared accepted, but they do not proceed with re-registration. The school presentation strategy contributes to student admissions, making it a good strategy, but it requires significant operational costs. Promotion area segmentation is needed so that this strategy can be more targeted, resulting in more efficient spending. Segmenting or grouping promotion areas can be addressed using data mining techniques, specifically clustering. This study aims to segment promotion areas using clustering algorithms, namely K-Means and K-Medoids, along with the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. The evaluation of DBI (Davies-Bouldin Index) showed that the K-Means algorithm performed better than the K-Medoids algorithm. The comparison between the K-Means and K-Medoids algorithms was assessed based on the DBI evaluation results, with the smallest DBI value observed in the K-Means algorithm. The DBI value for K-Medoids was 0.196, while for K-Means it was 0.170.
EDA and Tableau Analysis for Identification of Heart Disease Risk Factors Silmina, Esi Putri; Perkasa, Legawan
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6389

Abstract

Heart disease is one of the leading causes of death worldwide, influenced by various risk factors such as high blood pressure, cholesterol levels, and lifestyle. This study analyzes the risk factors for heart disease using the Heart Disease Dataset which includes more than 1,000 records with variables such as age, blood pressure, cholesterol, and alcohol consumption. Exploratory Data Analysis (EDA) was applied to identify patterns and relationships between variables, while Tableau was used to present the results visually and interactively. The results showed that high blood pressure was the main risk factor, with the majority of patients having blood pressure in the range of 130-135 mmHg, which is considered high risk. In addition, high cholesterol levels (200-205 mg/dL) also contributed significantly to the increased risk of heart disease, while alcohol consumption in the "Heavy" category worsened heart health conditions. Data visualization shows an increasing trend in heart disease cases, especially in individuals with a combination of these risk factors. Therefore, this study emphasizes the importance of routine blood pressure and cholesterol monitoring, implementing a healthy diet, regular physical activity, and health education to reduce the incidence of heart disease in the future.
Deteksi Kesegaran Daging Sapi Menggunakan Augmentasi Data Mosaic pada Model YOLOv5sM Yudhana, Anton; Silmina, Esi Putri; Sunardi
JRST (Jurnal Riset Sains dan Teknologi) Volume 9 No. 1 Maret 2025: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrst.v9i1.24990

Abstract

Deteksi kesegaran daging sapi secara otomatis sangat penting dalam mendukung kualitas bahan pangan, terutama dalam mencegah konsumsi daging yang sudah tidak layak dan berisiko terhadap kesehatan. Metode manual yang saat ini umum digunakan bersifat subjektif, lambat, dan tidak efisien jika diterapkan pada skala industri. Oleh karena itu, diperlukan pendekatan berbasis kecerdasan buatan yang mampu melakukan deteksi secara cepat dan akurat. Penelitian ini mengusulkan model deteksi kesegaran daging sapi menggunakan YOLOv5sM, yaitu modifikasi dari YOLOv5s yang menggabungkan teknik augmentasi data Flip, Rotation, dan Mosaic. Dataset yang digunakan terdiri dari 4.000 citra daging sapi, terbagi menjadi 2.000 citra daging segar dan 2.000 citra daging tidak segar. Data kemudian dibagi menjadi data pelatihan, validasi, dan pengujian. Tiga model dikembangkan: model YOLOv5s tanpa augmentasi, model dengan Flip dan Rotation, serta model YOLOv5sM dengan tambahan Mosaic. Hasil penelitian menunjukkan bahwa YOLOv5sM menghasilkan kinerja terbaik dengan Precision dan Recall sebesar 100%, mAP50 sebesar 99,5%, dan mAP50:95 sebesar 96,2%. Hal ini menunjukkan peningkatan signifikan dibanding dua model lainnya. Dengan hasil tersebut, model YOLOv5sM memiliki potensi besar untuk diimplementasikan sebagai sistem pendeteksi kesegaran daging sapi dalam industri pengolahan pangan yang membutuhkan efisiensi dan keakuratan tinggi.
Analisis Faktor Sosial yang Mempengaruhi Percobaan Penggunaan Narkoba Menggunakan Exploratory Data Analysis (Eda) dan Linear Regression Esi Putri Silmina; Syarifah Najmah
Journal of Information Technology Vol 5 No 1 (2025): Journal of Information Technology
Publisher : Institut Shanti Bhuana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46229/jifotech.v5i1.967

Abstract

Penyalahgunaan narkoba di kalangan remaja dan dewasa muda menjadi permasalahan sosial yang terus meningkat. Namun, faktor sosial yang memengaruhi keputusan awal untuk mencoba narkoba masih perlu diteliti lebih lanjut. Penelitian ini bertujuan untuk menganalisis faktor sosial utama yang berkontribusi terhadap percobaan penggunaan narkoba dengan menerapkan Exploratory Data Analysis (EDA) dan model Regresi Linear. Dataset yang digunakan adalah “Youth Smoking and Drug Dataset” dari Kaggle, yang mencakup variabel seperti usia, status sosial ekonomi, pengaruh teman sebaya, kesehatan mental, kondisi keluarga, dan akses terhadap program sekolah. Melalui eksplorasi data, penelitian ini mengidentifikasi pola, tren, dan hubungan antar variabel untuk memahami faktor dominan dalam percobaan penggunaan narkoba. Model Regresi Linear digunakan untuk memprediksi tren percobaan narkoba pada periode 2025–2030. Hasil analisis menunjukkan bahwa pengaruh teman sebaya (34%) dan kondisi keluarga (28%) merupakan faktor utama yang mendorong percobaan penggunaan narkoba, diikuti oleh status sosial ekonomi, kesehatan mental, dan akses terhadap program sekolah. Model prediksi yang diterapkan menunjukkan tingkat akurasi yang baik, sementara visualisasi data interaktif menggunakan Tableau membantu dalam memahami hubungan antar variabel secara lebih mendalam. Penelitian ini diharapkan dapat memberikan wawasan berbasis data bagi pembuat kebijakan dalam merancang strategi pencegahan yang lebih efektif dan tepat sasaran.
Co-Authors Aditiya, Aqni Alam Almon Lanang Prasojo Anggit Widcaksono Anton Yudhana Aris Rakhmadi Arjun, Restu Agil Yuli Bin Riedho, Al Bukhari Cendana, Willy Pratama Dana, Syaiful Rachmat Fadlillah, Umi Fikamelyalla, Naura Firdonsyah, Arizona Firmansyah Hanafi Fajar Hidayati, Ririn Wahyu Intan Mutiara Putri Intan Putri Irwanda Budi Pangestu Laily Maghfira Luluk Rosida Mufreni, Sadr Lufti Perkasa, Legawan Retantyo Wardoyo Rovalia Adhella Attya Amanda Salsyabila Vidia Nur Afni Salsyabila Vidia Nur Afni Sri Lestari Linawati Sri Winiarti Sunardi Suyani Suyani Syaiful Rachmat Dana Syaifurrahman, Rizky Syarifah Najmah Tikaridha Hardiani Wahyudi, M. Ilham Wijayanto, Danur Willy Pratama Cendana Yuliana Putri Yusuf Sulistyo Nugroho