Article Per Year (5 Year)
p-Index From 2021 - 2026
0.817
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JIKO (Jurnal Informatika dan Komputer) Prosiding Seminar Nasional dan Call Paper STIE Widya Wiwaha
Dison Librado
Universitas Teknologi Digital Indonesia
Computer Science & IT Economics, Econometrics & Finance

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
KLASTERISASI NOMINASI PENERIMA BANTUAN SOSIAL MENGGUNAKAN METODE TECHNIQUE ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION Tri Prabawa Marto Soetrisno; Dison Librado
JURNAL INFORMATIKA DAN KOMPUTER Vol 6, No 1 (2022): ReBorn - February 2022
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (132.266 KB) | DOI: 10.26798/jiko.v6i1.512

Abstract

Program Bantuan Langsung Tunai bagi masyarakat yang bersumber dari Dana Desa adalah program pemerintah untuk mengurangi beban masyarakat miskin dan rentan miskin dari dampak pandemi COVID-19.  Khususnya masyarakat miskin dan rentan miskin yang belum menerima bantuan dari skema jaminan kesejahteraan sosial lainnya. Persoalan timbul ketika banyaknya calon penerima bantuan sosial tidak sebanding dengan banyaknya kuota bantuan sosial yang tersedia, sehingga perlu dipilih nominasi penerima bantuan yang layak dan tepat sasaran. Penggunaan sistem pendukung keputusan dengan metode  TOPSIS dapat dipandang sebagai alternatif dalam penyelesaian masalah ini, sehingga peyaluran bantuan sosial dapat berjalan dengan baik, efektif dan tepat sasaran. Data calon penerima bantuan sebagai alternatif penerima diolah berpedoman pada 14 kriteria warga atau masyarakat miskin menurut versi Badan Pusat Statistik. Dari hasil pengolahan data calon penerima Bantuan Langsung Tunai Dana Desa tahun 2020, diperoleh hasil nilai preferensi tertinggi 0.68435 dan nilai preferensi terendah 0,25321, dan reratanya 0,49676 dari sampel data sebanyak 204 kepala keluarga.  Dari banyak sampel tersebut, jika diambil rangking 25, 50, 100, 150, dan 200 terbesar menunjukkan bahwa distribusi tingkat kemiskinan penduduk tidak merata, sehingga perlu adanya kebijakan pemerintah kelurahan untuk penanggulangan kemiskinan lebih spesifik.
UTILIZATION OF INTERNET OF THINGS (IoT) FOR ENERGY EFFICIENCY IN SMALL AND MEDIUM RETAIL BUSINESSES Dison Librado; Dixian Bhikuning; Dara Kusumawati
Prosiding Seminar Nasional dan Call Paper STIE Widya Wiwaha Vol 4 No 1 (2025): International Seminar Proceedings and Call for Paper STIE Widya Wiwaha
Publisher : Sekolah Tinggi Ilmu Ekonomi Widya Wiwaha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32477/semnas.v4i1.1297

Abstract

Energy costs and sustainability pressures have encouraged retail businesses to adopt technologies that optimize electricity usage without reducing customer comfort. Internet of Things (IoT) enables real-time monitoring and control of electrical devices through sensors and network connectivity, offering new opportunities for energy management in retail stores. This paper aims to analyze the potential utilization of IoT for energy efficiency in small and medium retail businesses by discussing the conceptual design, implementation scenarios, and indicative benefits. The research employs a qualitative-descriptive approach based on literature review and scenario modeling for typical energy uses in retail, namely lighting, air conditioning, and main electrical equipment. The proposed IoT architecture consists of three layers: device layer (sensors and actuators), network and gateway layer, and application and analytics layer. Implementation scenarios include presence-based lighting control, schedule and temperature-based air conditioning control, and smart load monitoring to detect anomalies. A simple comparative illustration between conventional and IoT-enabled operations indicates that automation and data-driven control can reduce operating hours of selected devices, which translates into potential savings in kWh and electricity costs, while also supporting green business objectives. The findings provide a conceptual and practical reference for retail business owners, SME development programs, and technology providers to design digital green innovation initiatives in the retail sector.
DIGITAL CONTENT MARKETING FOR ENVIRONMENTAL AWARENESS: EFFECTIVENESS OF SOCIAL MEDIA CAMPAIGNS IN PROMOTING GREEN CONSUMERISM Dixian Bhikuning; Dara Kusumawati; Dison Librado
Prosiding Seminar Nasional dan Call Paper STIE Widya Wiwaha Vol 4 No 1 (2025): International Seminar Proceedings and Call for Paper STIE Widya Wiwaha
Publisher : Sekolah Tinggi Ilmu Ekonomi Widya Wiwaha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32477/semnas.v4i1.1299

Abstract

Digital transformation has changed the landscape of environmental communication, where social media has become an important instrument in shaping people's ecological awareness. This study explores the effectiveness of digital content marketing campaigns in encouraging environmental awareness and green consumption behavior in Indonesia. The research uses a descriptive qualitative approach with a content analysis method on digital campaigns conducted by environmental organizations such as Greenpeace Indonesia, Zero Waste Indonesia, as well as various local eco-friendly brands on TikTok, Instagram, and YouTube platforms for the period January 2023 to December 2024. The findings show that content strategies that integrate educational, emotional, and actionable approaches result in significant audience engagement rates, with short video content achieving an engagement rate of 8-12%. Campaigns that successfully build emotional connections and provide practical solutions have proven to be more effective in turning awareness into sustainable consumption actions. Ecological and environmental awareness plays an important role as an important mediator in the adoption of green practices. This research makes a theoretical contribution to the development of sustainable digital marketing literature and practically serves as a guide for practitioners in designing more effective digital campaigns to drive the transformation of consumer behavior towards sustainability.
AI-Based Pharyngitis Detection Expert System Using the Certainty Factor Method Emy Susanti; Robby Cokro Buwono; Dison Librado; Faiz Rifki Syuhada
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 3 (2026): Article Research July 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i3.16463

Abstract

Pharyngitis, an inflammation of the pharynx commonly known as a sore throat, is one of the most frequent complaints in Indonesian primary health care, yet the uneven distribution of physicians, especially in remote regions, often delays timely triage. This study develops an Android-based expert system that provides an early-screening indication of two types of pharyngitis, acute and chronic, using the Certainty Factor (CF) method. Rather than treating the disease application itself as the main contribution, the novelty lies in the validation framework: a dual-source certainty model that keeps expert-elicited rule weights separate from user-reported symptom confidence, and a class-level accuracy evaluation, including a confusion matrix, sensitivity, specificity, precision, recall, and F1-score, that is rarely reported alongside comparable Certainty Factor systems. Knowledge was acquired from a general practitioner and clinical references and encoded as thirteen symptoms, two disease classes, and a rule base of IF-THEN rules with expert certainty weights. User certainty is captured through six linguistic terms and combined with the expert CF values using the single-evidence formula CF[H,E] = CFuser x CFexpert and the parallel combination formula. The application was built with Android Studio and a local SQLite knowledge base so that it operates entirely offline. A worked example involving five symptoms of acute pharyngitis produced a combined certainty of 0.9890, or 98.90%, illustrating a high-confidence screening output. The system's screening conclusions were compared with a general practitioner's diagnosis on 30 patient cases, agreeing in 28 cases for an overall agreement accuracy of 93.33% (class-level sensitivity of 94.12% for acute and 92.31% for chronic pharyngitis); because this figure reflects agreement with a single practitioner rather than a laboratory-confirmed reference standard, it is reported as an agreement accuracy rather than a universal clinical accuracy. Black-box testing confirmed that all functional features operated as intended. The results indicate that the Certainty Factor method can quantify screening uncertainty effectively and that the resulting offline mobile application can serve as an accessible early-screening aid for the public and a decision-support tool for paramedics, complementing rather than replacing a professional medical examination.
Co-Authors Dara Kusumawati Dixian Bhikuning Emy Susanti Faiz Rifki Syuhada Robby Cokro Buwono Tri Prabawa Marto Soetrisno