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All Journal JURNAL ILMIAH INFORMATIKA Infotech: Journal of Technology Information
Effendy, Vina Ardelia
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Computer Science & IT

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PERBANDINGAN ALGORITMA CANNY EDGE DETECTION DAN PREWITT PADA DETEKSI STADIUM DIABETIK RETINOPATI Vina Ardelia Effendy; Febri Maspiyanti
JURNAL ILMIAH INFORMATIKA Vol 9 No 02 (2021): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v9i02.3762

Abstract

Diabetes is a serious threat to human health. In 2016, non-communicable diseases including Diabetes accounted for 70% of the total causes of death in the world. Diabetes if left unchecked will cause complications that can attack other organs to cause blindness called Diabetic Retinopathy (DR). Ophthalmologists make a grouping of diabetic characteristics of retinopathy by observing the retinal images of the eye taken using a fundus camera. This method requires a long time in the observation that allows errors in making observations, so image processing is needed to detect and classify the stage of diabetic retinopathy suffered by the patient. Thus, this research aims to help the process of early treatment of patients with diabetic retinopathy so as not to cause blindness. The data used in this study is DB0 Diaret data with a pixel size of 128 x 104 and the amount of data is 131. The methods used in this system include Canny Edge Detection, Prewitt, and stadium readings using Artificial Neural Network Algorithms. In this study the highest accuracy results obtained on the Canny Edge Detection method with a value of 90% while the Prewitt method has a 79% result. So, we get the conclusion that Canny Edge Detection is considered better.
CRITICAL SUCCESS FACTOR ADOPSI TEKNOLOGI INFORMASI DAN KOMUNIKASI PADA LEMBAGA PEMASYARAKATAN: SEBUAH STUDI KASUS Sulasno, Mitsal Shafiq; Danutirta, Alif Shofa; Fathoni, Achmad Robbi; Qital, Dari Aulia; Effendy, Vina Ardelia
Infotech: Journal of Technology Information Vol 10, No 2 (2024): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v10i2.311

Abstract

The adoption of communication and information technology has a strategic role in realizing the vision and mission of an organization. The adoption of ICT can have a good influence on employee performance.  Correctional service is one of the aspects of life that also requires an improvement in ICT capabilities, one of which is through the adoption of ICT. The Correctional Technical Implementation Unit is required to always develop in order to meet the goals of corrections. Correctional institutions are expected to adopt ICT to improve the performance of officers. Often, the adoption of ICT in Correctional Institutions does not go as expected. In addition, the adoption of ICT also does not last long. The purpose of this study is to determine Critical Success Factors related to technology adoption in Tangerang Class I Correctional Institution. The TOE framework was used in this study because environmental factors were considered to have a great influence on the place of the case study. This study uses a qualitative-quantitative method (mixed method) with interviews, literature studies, and questionnaires as research instruments. The data obtained from the questionnaire was processed using the Analytical Hierarchy Process (AHP). The results of the study show that the three Critical Success Factors that are the main keys to the success of technology adoption in Tangerang Class I Correctional Institution are Government Support, Culture, and Top Management Support.ABSTRAKAdopsi teknologi komunikasi dan informasi memiliki peran yang strategis dalam mewujudkan visi serta misi sebuah organisasi. Adopsi TIK dapat memberikan pengaruh baik terhadap kinerja pegawai.  Pemasyarakatan merupakan salah satu aspek kehidupan yang juga memerlukan peningkatan dalam kapabilitas TIK yang salah satunya melalui adopsi TIK. Unit Pelaksana Teknis Pemasyarakatan dituntut untuk selalu berkembang dalam rangka memenuhi tujuan pemasyarakatan. Lembaga Pemasyarakatan diharapkan dapat melakukan adopsi TIK untuk meningkatkan kinerja petugas. Seringkali, adopsi TIK pada Lembaga Pemasyarakatan tidak berjalan sesuai harapan. Selain itu, adopsi TIK juga tidak bertahan lama. Tujuan penelitian ini adalah untuk menentukan Critical Success Factor terkait adopsi teknologi pada Lembaga Pemasyarakatan Kelas I Tangerang. TOE framework digunakan pada penelitian ini karena faktor environment dianggap memiliki pengaruh yang besar terhadap tempat studi kasus. Penelitian ini menggunakan metode kualitatif-kuantitatif (metode campuran) dengan wawancara, studi literatur, dan kuesioner sebagai instrumen penelitian. Data yang didapatkan dari kuesioner diolah menggunakan Analytical Hierarchy Process (AHP). Hasil penelitian menunjukkan tiga Critical Success Factor yang menjadi kunci utama keberhasilan adopsi teknologi pada Lembaga Pemasyarakatan Kelas I Tangerang adalah Government Support, Culture, dan Top Management Support.
ANALISIS PREDIKSI TUMBUH KEMBANG ANAK DENGAN MACHINE LEARNING Nugraheni, Murien; Widodo, Widodo; Lestari, Uning; Effendy, Vina Ardelia; Yunanto, Prasetyo Wibowo; Amannu, Ramadhan
Infotech: Journal of Technology Information Vol 11, No 1 (2025): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i1.389

Abstract

Stunting is a major chronic nutritional issue that remains a significant challenge in Indonesia. This study aims to predict the risk of stunting in children and enhance prevention efforts by analyzing the health and nutritional status of parents. The research employs Machine Learning methods by comparing the performance of the Decision Tree and Gaussian Naive Bayes algorithms. The dataset was obtained from open data sources and analyzed using Google Colab, with a Technology Readiness Level (TRL) of level 3. Evaluation results show that both algorithms achieved an accuracy of 95.35% based on the confusion matrix. The model accurately identified 2 stunting cases (True Positive) and 41 non-stunting cases (True Negative), indicating a high level of classification reliability. These findings suggest that Machine Learning approaches can be effectively utilized as early detection tools to support stunting prevention strategies in children.
IMPLEMENTASI SAMPAH CERDAS DI UNIVERSITAS: SEBUAH SYSTEMATIC LITERATURE REVIEW Effendy, Vina Ardelia; Sulasno, Mitsal Shafiq
Infotech: Journal of Technology Information Vol 11, No 1 (2025): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i1.371

Abstract

The problem of waste management in DKI Jakarta is a major challenge for the local government, especially with the increase in waste generation which reaches an average of 41,079,420.38 tonnes per year and 112,546.36 tonnes per day by 2023. The limited management capacity means that around 30 tonnes of waste, or 16,286,946 tonnes, are not optimally handled. Waste management in the DKI Jakarta area is classified into household waste, household-like waste, and specific waste, which covers various sectors, including offices, universities, and public facilities. Universities have an important role to play in promoting environmental sustainability through the implementation of smart waste management concepts. This study aims to explore the application of an effective waste management system in an academic environment, as well as to provide comprehensive insights into research trends in the field of solid waste management. This study uses the application of a Systematic Literature Review (SLR) which is expected to provide insights into the application of smart waste management from various developed countries in the scope of Higher Education in the future and to support the implementation of sustainable waste management practices in Higher Education. By reviewing existing literature, this research also contributes to enriching academic understanding and empowering communities and stakeholders to realise more efficient and sustainable waste management systems. The results of this research are expected to provide insights for the academic world and the application of smart waste. In addition, the findings obtained can form the basis for further research to enrich understanding and the development of innovative solutions in this field.
PARADIGMA SISTEM DALAM TATA KELOLA ETIKA DAN INFRASTRUKTUR AI: ANALISIS PERAN SISTEM OPERASI Effendy, Vina Ardelia; Syabifi, Fiqla; Febriansyah, Muhammad; Alifiansyah, Fadlan Nur; Zukhruf, Elevina
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.552

Abstract

The rapid development of Artificial Intelligence (AI) has brought transformative impacts across various sectors but simultaneously raises multidimensional challenges, particularly regarding ethics and infrastructure governance. This study aims to analyze AI governance through a system paradigm approach by using the operating system (OS) as an analytical analogy. The research employs a qualitative method through a literature study of reputable journals and academic databases, focusing on AI ethics, system paradigms, and infrastructure governance. Findings indicate that the system paradigm provides a holistic framework to integrate ethical principles, regulatory mechanisms, and technical functions within AI ecosystems. The OS analogy highlights governance components such as ethical kernels, access control, and security layers as integral to ensuring transparency, accountability, and fairness. The study concludes that responsible AI governance requires a systemic, adaptive, and sustainability-oriented approach, bridging technological innovation with social and ethical values.
Co-Authors Alif Shofa Danutirta Alifiansyah, Fadlan Nur Amannu, Ramadhan Fathoni, Achmad Robbi Febri Maspiyanti Febriansyah, Muhammad Murien Nugraheni Qital, Dari Aulia Sulasno, Mitsal Shafiq Syabifi, Fiqla Uning Lestari Widodo Widodo Yunanto, Prasetyo Wibowo Zukhruf, Elevina