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Requirements Analysis of Tuberculosis Screening Information System Using PIECES Framework Dewi, Adinda Cipta; Adi, Kusworo; Martini
Jurnal Multidisiplin Madani Vol. 4 No. 6 (2024): June 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/mudima.v4i6.9715

Abstract

Tuberculosis (TB) remains a global health threat, especially in low and middle income countries, including Indonesia. In Indonesia, there is a surge in TB cases due to the lack of detection and treatment of TB that does not reach the target. To achieve TB elimination by 2030 in accordance with the global target, Indonesia must reach the target of finding cases at least 90% of estimated cases. TB case finding through the screening activities is the first step of TB control to reduce morbidity and mortality. This study aims to analyze the requirements of the TB screening information system. The analysis was conducted based on the PIECES Framework as a method of analysis as a basis for obtaining more specific issues. The results of the analysis resulted in the need for an information system that can be accessed by the Health Office, Health Center, and the community with several requirements including providing a menu of counseling schedules and consultation messages, adding data on educational materials, producing an information dashboard, a system equipped with a database for storage and a password for security, and producing accurate and real time information for the requirements of prevention and intervention efforts
Systematic Literature Review on Information Technology Governance in Government Wicaksono, Januar Agung; Widodo, Aris Puji; Adi, Kusworo
Telematika Vol 20 No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.9642

Abstract

Purpose: This article aims to assist the government in developing better, more efficient, and sustainable public governance by utilizing information technology and artificial intelligence. The article provides insights on how information technology and artificial intelligence can be applied in public governance to improve the efficiency, effectiveness, and sustainability of public services, as well as to enhance public trust in the government.Design/Method/Approach: The method used in this article is a Systematic Literature Review (SLR), which is a systematic and methodological research method for collecting, evaluating, and synthesizing evidence from previous studies in the field under investigation, through search terms and searching for information in online databases and creating inclusion and exclusion criteria.Results: This article is expected to achieve more efficient, effective, and sustainable public governance and improve the quality of public services and public trust. The article also shows that information technology and artificial intelligence have become an integral part of public governance in various countries, with many countries taking a holistic and sustainable approach.Originality/State of the art: The state-of-the-art of this article is that information technology and artificial intelligence can be effectively used to improve public governance to achieve better, more efficient, and sustainable goals. The article also emphasizes the importance of considering data privacy, cyber security, and unwanted environmental impacts, as well as considering ethical and human rights aspects in the development of artificial intelligence. This will help the government to develop and implement information technology and artificial intelligence in public governance in a responsible and sustainable manner.
Enhanced U-Net models with encoder and augmentation for phytoplankton segmentation Ardhi, Ovide Decroly Wisnu; Soeprobowati, Tri Retnaningsih; Adi, Kusworo; Prakasa, Esa; Rachman, Arief
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp1009-1018

Abstract

This study comprehensively analyzes U-Net models for semantic segmentation in phytoplankton image recognition, leveraging encoders such as EfficientNet-B5, MobileNetV2, ResNet50, and ResNeXt50 and employing the Adam optimizer. The research highlights the U-Net MobileNetV2 model with optical distortion, which achieves notable test scores with 93.69% Dice, 88.14% intersection over union (IoU), 99.89% Precision, and 100% Recall, underscoring the efficacy of the applied augmentation strategies, including geometric and distortion transforms, and color and blur techniques. The U-Net ResNet50 model with mix transform consistently demonstrates high accuracy in critical metrics, outperforming others, while EfficientNet-B5 with blur suggests increased model sensitivity with improved recall. These results underscore the crucial role of encoder-augmentation synergy in model performance. Training and testing times across models have remained under 250 seconds, reflecting methodological efficiency. Overall, these results demonstrate the model's excellent performance for the semantic segmentation task.
Literature-Driven Contributions to the Development of LLM-Based Customer Insight Systems Nugroho, Irwan Andriyanto; Kusworo Adi; Komang Budi Aryasa
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 01 (2026): JANUARY
Publisher : ISB Atma Luhur

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

Abstract

This study presents the conceptual development of a sentiment analysis model using Large Language Models (LLMs), integrated with a dynamic weighting system based on the strategic value of product attributes. While previous research has demonstrated the effectiveness of Natural Language Processing (NLP) techniques in analyzing customer satisfaction and online reviews, few efforts have aligned sentiment insights with product prioritization in decision-making. Drawing from a systematic review of seven recent studies—most of which rely on traditional NLP approaches—this research identifies critical gaps, including fragmented sentiment extraction and the lack of contextual, strategic weighting. The proposed LLM-based framework advances prior insights by combining sentiment analysis, customer voice modeling, and adaptive prioritization mechanisms. The outcome is intended to enhance product improvement strategies, align customer feedback with strategic objectives, and support data-driven decision-making in dynamic business environments.
Co-Authors - Magister Sistem Informasi Universitas Diponegoro, Vincencius Gunawan S.K Abdillah Noor Fajrin Achmad Widodo Adi Pamungkas Adian Fatchur Rohim Adila Safitri Agus Atabik Anwar Agustini, Eka Puji Agvion Virsaw Alfajri, Willy Bima Andrian Bayu Suksmono Andriyan B. Suksmono Andriyan Suksmono Andriyan Suksmono, Andriyan Antono Suryo Putro Apoina Kartini Aprilia Ayu Andarinny Ardhi, Ovide Decroly Wisnu Ari Bawono Putranto Arief Rachman Aris P Widodo Aris Puji Widodo Aris Puji Widodo Aris Sugiharto Ary Setyadi Atik Zilziana Muflihati Noor Baital, Muhammad Sawal Basuki Wibowo Beta Noranita Cahya Tri Purnami Carissa Devina Usman Catur Adi Widodo Catur Edi Widodo Chakim Annubaha Choirul Anam Choirul Anam AM Diponegoro Dartini Dartini Dartini Dartini, Dartini Dedi Apriyandi Dedi Sepriana Delfia, Fila Dewi, Adinda Cipta Dian Anggraini Didi Supriyadi Dwi Ely Kurniawan Dwi Rochmayanti Dyah Apriliani Eka Vickraien Dangkua, Eka Vickraien Eko Adi Sarwoko Eko Sediono Elvira Situmorang Esa Prakasa, Esa Evi Setiawati Evita Ayu Suryaningtyas Faikhin . Faisal Rahman Fanny, Nabilatul Fardana, Nouvel Izza Farid Agushybana Farid Farid Agushybana Fatkhurrazi Basyid Figur Humani Fila Delfia Frida Fallo Gatot Murti Wibowo Gatot Murti Wibowo, Gatot Murti Hadyan Arifianto Hariri, Ahmad Harnanto, Rudy Haryati Haryati Hastuti, Dyah Dewi Havez Vazirani Al Kautsar Hendra Gunawan HENDRA GUNAWAN B11211055 Hernowo Danusaputro Ibrahim, Muhammad Rivani Imam Syafii Ircham Ali Isnain Gunadi Isnain Gunadi Jatmiko Endor Suseno Jatmiko Endro Suseno Jatmiko Endro Suseno Jayawarsa, A.A. Ketut Julianto, Dewa Rizki Rahmat Komang Budi Aryasa Laila Rahmawati Linda Nuryanti M.Irwan Katili Mailia Putri Utami Mailia Putri Utami MAIZZA NADIA PUTR Maratullatifah, Yulaikha MARTINI Martini Martini Mengko, Tati L.R. Muhammad Ikhsan Nahdi Saubari Nanang Sulaksono, Nanang Natalia Kristiani Nava Muzdalifah Nelly Mirnasari Neneng Neneng Nina Dwi Astuti Noor Azizah Nugroho Adhi Santoso Nugroho, Irwan Andriyanto Nur Hamid Nurul Firdausi Nuzula, Nurul Firdausi Nurul Huda Prasetyo Oky Dwi Nurhayati Pamungkas, Ardian Prakasa, Fawwaz Bimo Puji Widodo, Aris Purwanto Purwanto Putri Nuriskianti Qoriani Widayati R Rizal Isnanto Rachmat Gernowo Rachmatullah, Robby Rahmat Gernowo Rahmat Gernowo Rasyid Rasyid, Rasyid Retnaningsih Soeprobowati, Tri Ria Amitasari Rima Ayuning Ratri Riris Trima Derita Sari Rizky Ayomi Syifa Rr. Tony Yulianto Saiful Widianto Salsabila Naqiyah Sari, Kiki Puspita Septya Maharani, Septya Setyowati Setyowati Shahmirul Hafizullah Imanuddin Sidin Hariyanto Sifaunajah, Agus Siti A'isyah Siti Nur Endahyani Sri Bintang Pamungkas Suandari P.V.L Suryono Suryono Suseno, Jatmiko Endor Sutopo Patria Jati Tati Mengko Tati Mengko, Tati Tito Rano Pradibto Toni Wijanarko Adi Putra Tri Mulyono Tri Retnaningsih Soeprobowati Tri Sandhika Jaya Tutur Urip Undari Nurkalis Vincencius Gunawan, Vincencius Vincensius Gunawan S.K. Wahyu Setia Budi Wahyudi Setiawan Wahyuni, Wilda Waliyansyah, Rahmat Robi Weirna Yusanti Wicaksono, Januar Agung Widagdo, Krisan Aprian Willy Bima Alfajri Wisnu Ardhi, Ovide Decroly Wiwit Agus Triyanto Yuliani Setyaningsih Zaenal Arifin Zaenul Muhlisin Zainal Bachrudin