Claim Missing Document
Check
Articles

Found 8 Documents
Search

ANALISIS ASOSIASI PILIHAN PROGRAM STUDI PENDAFTAR UNIVERSITAS ISLAM NEGERI SUNAN KALIJAGA JALUR MANDIRI MENGGUNAKAN ALGORITMA APRIORI Dita Septasari
Aisyah Journal Of Informatics and Electrical Engineering Vol 2 No 1 (2020): Aisyah Journal Of Informatics and Electrical Engineering
Publisher : Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30604/jti.v2i1.25

Abstract

UIN Sunan Kalijaga memiliki banyak data pendaftar dari berbagai jalur, salah satunya jalur Mandiri. Program studi yang dipilih oleh pendaftar dapat digunakan sebagai informasi dengan melakukan analisis. Analisis pilihan program studi yang dipilih oleh pendaftar dapat informasi masing-masing program studi dalam menarik minat mahasiswa baru, selain itu mempermudah pendaftar dalam mendapatkan apa yang dicita-citakan melalui pemilihan program studi yang tepat dengan menggali pola-pola yang ada untuk pertimbangan pemilihan program studi. Dalam menganalisis pemilihan program studi pendaftar dapat menggunakan Algoritma Apriori. Algoritma Apriori merupakan algoritma yang berguna menemukan pola-pola data dengan nilai frekuensi. Program Studi yang dipilih oleh pendaftar memiliki hubungan yang dapat direpresentasikan dalam aturan asosiasi. Algoritma apriori berperan dalam melakukan proses perhitungan dalam menentukan nilai support setiap program studi dan kombinasi program studi yang banyak dipilih oleh pendaftar berdasarkan frekuensi item(program studi) dan menentukan nilai confidence kombinasi program studi untuk proses analisis asosiasi. Output/hasil dari analisis asosiasi yang dilakukan pada penelitian ini menghasilkan pengetahuan/knowledge tentang pendaftar yang memilih program studi Teknik Industri juga memilih program studi Teknik Informatika sebagai kombinasi program studi yang paling banyak dipilih pendaftar UIN Sunan Kalijaga tahun ajaran 2016/2017 dan mengetahui seberapa kuat
The Cyber Security and The Challenge of Society 5.0 Era in Indonesia: Cyber Security and The Challenge of Society 5.0 Era in Indonesia Dita Septasari
Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E) Vol. 5 No. 2 (2023): Aisyah Journal Of Informatics and Electrical Engineering
Publisher : Aisyah Journal Of Informatics and Electrical Engineering (A.J.I.E.E)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30604/jti.v5i2.231

Abstract

Keamanan informasi menjadi salah satu aspek krusial dalam era Society 5.0. Seiring memasuki era Society 5.0, di mana setiap aspek kehidupan manusia bergantung pada penggunaan teknologi informasi dan komunikasi. Hampir seluruh aspek kehidupan, terutama dalam interaksi antar manusia, memanfaatkan internet dan perangkat teknologi informasi. Era Society 5.0 mempermudah kehidupan manusia dibantu dengan berbagai kemajuan teknologi seperti IoT (Internet Of Things) dan AI (Artificial Intelligence). Kemudahan yang diberika oleh Era Society 5.0 juga terdapat tantangan yang menyerang dunia cyber. Cyber attack bisa menyerang individu perseorangan dan integritas bangsa dan negara. Serangan Cyber harus ditangani dengat tepat sesuai hukum yang berlaku di Indonesia. Indonesia merupakan negara dengan cyber security yang masih lemah, sehingga perlu kerjasama semua pihak dalam memperkuat cyber security di Indonesia, termasuk pembuatan Undang-Undang ITE yang memperkuat cyber security di Indonesia.
Pemodelan Artificial Neural Network Dalam Prediksi Penentu Penerima Beasiswa Septasari, Dita; Isni Kurnia , Ulfa
Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 1 (2025): Jurnal Rekayasa Perangkat Lunak (J-Rapa)
Publisher : Universitas Aisyah Pringsewu

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

Abstract

Scholarships play a vital role in supporting high-achieving students who face financial constraints. However, the selection process is often time-consuming and prone to subjectivity. This study develops a predictive model for scholarship recipients using the Artificial Neural Network (ANN) approach to create a more efficient and objective selection system. The dataset includes academic performance, parental income, number of dependents, and non-academic achievements. The ANN model is designed through data preprocessing, training, and evaluation stages, using metrics such as accuracy, precision, recall, and F1-score. The results indicate that ANN can accurately and effectively predict scholarship recipients, making it a valuable tool to assist decision-making in scholarship distribution.
IoT-Based Cup Sealer Machine Automation Using Nodemcu ESP32 Aminudin, Nur; Usmanto, Budi; Feriyanto, Dwi; Septasari, Dita; Andika, Tahta Herdian; Muhammad, Adamu Abubakar
JENTIK : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Vol. 4 No. 1 (2025): Jurnal Pendidikan Teknologi Informasi dan Komunikasi
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jentik.v4i1.442

Abstract

Background of study: The development of the food and beverage industry demands innovation in efficient and reliable packaging processes. Conventional cup sealing machines often face limitations in speed and precision, necessitating technology-based solutions. Aims and scope of paper: This objective of the study is to design and implement an automated cup sealer system based on the Internet of Things (IoT), using the NodeMCU ESP32, capable of performing sealing and real-time monitoring. The system integrates a flowmeter sensor to detect the presence of cups, a stepper motor for the sealing process, and an LCD display along with WiFi connectivity for monitoring production data. Methods: The methodology involves hardware design, control system programming, and performance testing of the device under various temperature and motor speed parameters. Result: The results show that the system can increase production efficiency by up to six times compared to the manual method, with a capacity of 300 cups per hour and a sealing success rate of 95% at an optimal temperature of 100°C and a motor speed of 10 RPM. Synchronization among components was enhanced through sensor calibration and algorithm development. Conclusion: In conclusion, this automated system not only improves efficiency and accuracy but also offers flexibility and IoT-based control, making it highly relevant for small and medium-sized industries.
A User-Driven E-Audit System for Improving Transparency and Efficiency in Regional Government Supervision Aminudin, Nur; Hidayat, Nurul; Feriyanto, Dwi; Mukaromah, Hafsah; Septasari, Dita; Awaliyani, Ikna
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5145

Abstract

Internal audit processes in regional government institutions often face challenges such as time inefficiency, low transparency, and poorly digitized documentation. This study aims to develop an E-Audit system to enhance the effectiveness of internal supervision in a regional inspectorate environment. Employing a user-centered design approach and a structured system development methodology, this research involved key roles—auditors, technical controllers, and follow-up teams—throughout the design and testing stages. The developed system integrates three core phases of the audit process—planning, reporting, and follow-up—into a single, modular, and interactive digital platform. Implementation results indicate a significant improvement in audit efficiency, with a reduction of more than 50% in process duration compared to manual methods. The system also enhances documentation consistency through digital audit trails, role-based dashboards, and automatic reporting features. User acceptance testing revealed a high level of satisfaction, with users highlighting the system’s ease of use, increased accuracy, and alignment with daily audit tasks. Additionally, user feedback emphasized the need for integrated notification features and inter-unit communication tools, indicating readiness for more advanced digital transformation. Overall, this study provides practical value as a model for digital audit implementation at the regional government level while contributing to the advancement of Computer Science through the application of software engineering principles and information systems to support digital government oversight. The developed E-Audit model can serve as a reference for designing real-time collaborative public auditing systems relevant to the development of information systems engineering and computational governance.
Pelatihan Blender Untuk Pengembangan Media Pembelajaran Augmented Reality (AR) Bagi Mahasiswa Kurnia, Ulfa Isni; Septasari, Dita; Awaliyani, Ikna
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 7 (2025): September
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i7.2882

Abstract

Pelatihan ini bertujuan untuk meningkatkan kompetensi mahasiswa pendidikan dalam mengembangkan media pembelajaran berbasis Augmented Reality (AR) menggunakan perangkat lunak Blender. Dengan pesatnya perkembangan teknologi, AR menjadi solusi inovatif untuk menciptakan pengalaman belajar interaktif dan imersif. Metode pelatihan meliputi workshop, praktik langsung, dan pendampingan dalam pemodelan 3D, animasi, serta integrasi AR dengan aplikasi pendukung seperti Unity atau Spark AR. Peserta diajarkan langkah-langkah pembuatan objek 3D, tekstur, dan interaktivitas sederhana untuk materi pembelajaran. Evaluasi dilakukan melalui hasil projek mahasiswa. Hasil pelatihan menunjukkan peningkatan dalam keterampilan teknis mahasiswa serta kemampuan merancang media AR yang relevan. Pelatihan ini membuka peluang pemanfaatan teknologi AR dalam pembelajaran sekaligus mempersiapkan calon pendidik yang adaptif terhadap era digital.
Digital Landscape and Behavior in Indonesia 2024: A National Survey Analysis of Internet Penetration, Cybersecurity Risks, and User Segmentation Using K-Means Clustering and Logistic Regression Aminudin, Nur; Hidayat, Nurul; Feriyanto, Dwi; Septasari, Dita; Awaliyani, Ikna
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5117

Abstract

Digital transformation in Indonesia reveals significant disparities in internet access, digital behavior, and cybersecurity vulnerabilities. This study analyzes the digital landscape using national survey data from 8,720 respondents across 38 provinces. This research employs a quantitative approach, utilizing chi-square tests, logistic regression for risk analysis, and K-Means clustering for user segmentation, supported by Principal Component Analysis (PCA) for dimensionality reduction. The results show a national internet penetration rate of 79.5%, with significant disparities across regions and socio-economic segments. Logistic regression analysis reveals that higher education, greater income, and the use of fixed broadband are negatively correlated with cybersecurity risks. Furthermore, K-Means clustering identifies three distinct user profiles: 'Digital Savvy', 'Pragmatic Users', and the 'Vulnerable Segment', each with unique characteristics regarding digital access and literacy. This research provides a critical empirical basis for understanding digital transformation in a developing nation. The findings underscore the necessity of data-driven, segmented policies to foster digital inclusion and enhance national cybersecurity, offering actionable insights for policymakers and service providers.
Perbandingan Metode Artificial Neural Network (ANN) dan Classification And Regression Tree (CART) Dalam Menentukan Penerima Bantuan Program Keluarga Harapan (PKH) Septasari, Dita; Abdul Aziz, RZ.
Jurnal Algoritma Vol 21 No 2 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-2.1794

Abstract

Poverty in Indonesia is influenced by several factors. In this case, the government is implementing various programs to improve the welfare of the community. One of these programs is the Family Hope Assistance Program (PKH). Predictions regarding PKH assistance recipients use the Artificial Neural Network (ANN) and Classification and Regression Tree (CART) methods to assist in the process of determining recipients of the family hope program. The Artificial Neural Network (ANN) and Classification and Regression Tree (CART) methods produce performance measurements (accuracy, precision, recall, and f1-score) from the data of Family Hope Assistance Program (PKH) recipients. The results of this study show that the Artificial Neural Network (ANN) method performs better than the Classification and Regression Tree (CART) method in predicting PKH recipients in Pringsewu Regency.