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All Journal Kompak : Jurnal Ilmiah Komputerisasi Akuntansi E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Pixel : Jurnal Ilmiah Komputer Grafis ROTOR: JURNAL ILMIAH TEKNIK MESIN Jurnal SOLMA Pendas : Jurnah Ilmiah Pendidikan Dasar Conference on Innovation and Application of Science and Technology (CIASTECH) Al-Banjari : Jurnal Ilmiah Ilmu-Ilmu Keislaman Viabel : Jurnal Ilmiah Ilmu-Ilmu Pertanian Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan Al-Bukhari: Jurnal Ilmu Hadis Revitalisasi : Jurnal Ilmu Manajemen Media Aplikom Teknik: Jurnal Ilmu Teknik dan Informatika MANAJEMEN Journal of Engineering, Electrical and Informatics (JEEI) Jurnal Teknologi Informasi Cyberku Jurnal Manajemen Informatika & Teknologi Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Al Yazidiy: Jurnal Sosial Humaniora dan Pendidikan Journal of Technology Informatics and Engineering Seminar Nasional Teknologi dan Multidisiplin Ilmu Future Academia : The Journal of Multidisciplinary Research on Scientific and Advanced Repeater: Publikasi Teknik Informatika dan Jaringan International Journal of Computer Technology and Science Legitima : Jurnal Hukum Keluarga Islam Systematic Literature Review Journal Journal of New Trends in Sciences Journal of Engineering, Electrical and Informatics
Eko Siswanto
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Nursing Public Health Social Sciences Other

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PENGARUH TRICHODHERMA sp. TERHADAP PERTUMBUHAN DAN HASIL TANAMAN MELON var Honey Orange DI GREENHOUSE UNISBA Serdani, Army Dita; Palupi Puspitorini; Tri Endrawati; Eko Siswanto; Budiman, Eko Wahyu
Viabel : Jurnal Ilmiah Ilmu-Ilmu Pertanian Vol 20 No 2 (2025): November 2025
Publisher : Universitas Islam Balitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35457/bdqhjk28

Abstract

Melon (Cucumis melo L.) Honey Orange variety is a horticultural commodity with superior taste, aroma, and nutritional content, but its productivity is relatively low. The purpose of this study was to examine the effect of various doses of Trichoderma sp. on the growth and yield of melon plants of the Honey Orange variety. The study used a Randomized Block Design (RBD) with six treatments, namely T0 = without Trichoderma sp., T1 = 5 g/L, T2 = 10 g/L, T3 = 15 g/L, T4 = 20 g/L, and T5 = 25 g/L. The parameters observed were the number of leaves (leaflets), stem diameter (cm), fruit diameter (cm), and fruit weight (g). The data obtained were analyzed using analysis of variance, followed by Duncan's Test at the 5% level. The results of this study showed that the administration of Trichoderma sp. had a significant effect on all observed growth and yield parameters. The T3 treatment (15 g/L) was the most effective treatment, with an increase in the number of leaves and stem diameter, and produced the highest fruit diameter and fruit weight, namely 36.48 cm and 876 g, respectively. Thus, the application of Trichoderma sp. at a dose of 15 g/L can be recommended as the optimum dose to increase the growth and productivity of the Honey Orange melon variety.
DEEP LEARNING ALGORITHM FOR CONNECTING SCIENTIFIC RECORDS AND SOCIAL PLATFORM Budi Santoso; Agustinus Budi Santoso; Eko Siswanto
Journal of Engineering, Electrical and Informatics Vol. 2 No. 2 (2022): Juni: Journal of Engineering, Electrical and Informatics:
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i2.913

Abstract

In the healthcare industry, professionals develop big amounts of disorganized data. The complexity of this data and the loss of computational capability lead to delays in the investigation. Nevertheless, with the advent of Deep Learning algorithms and connection to computing power such as Graphic Processor Units (GPUs) and Tensor Processing Units (TPUs), text and image processing has become usable. Deep Learning (DL) data bring about a big outcome in Natural Language Processing (NLP) and computer perception. The main purpose of this study is to build an undivided approach that can relate social platforms, literature, and scientific records to develop an approach to medicinal education for the public and experts. This study focuses on NLP in the healthcare industry and compiles data by Electronic Medical Records (EMR), medical literature, and social platforms. The framework proposed in this study is one for connecting social platforms, medical literature, and Electronic Medical Records scientific records using Deep Learning algorithms. Linking data sources requires defining the relationships between them, and finding concepts in medical texts. The National Library of Medicine (NLM) introduced the Unified Medical Language System (UMLS) and uses this system as the basis for the proposed system. The dynamic nature of a social platform can be recognized and supervised methodologies can be applied under supervision to develop conception. Named entity Recognition (NER) enables the active eradication of data or individuals by the pharmaceutical literature.
Cash Processing Administration System In The Indonesian Red Cross Blood Transfusion Unit, Semarang City Okky Dwianto Wahyu Nugrohojati; Eko Siswanto; Bagus Sudirman
Journal of Engineering, Electrical and Informatics Vol. 2 No. 3 (2022): Oktober: Journal of Engineering, Electrical and Informatics:
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i3.2849

Abstract

The cash processing administration system in a company plays a very important role. One of the problems that often arises in a cash processing administration system is the inaccurate calculation results of cash administration reports. This can result in inaccurate calculations of a company's profits and losses. Besides that, the use of company funds for something is not necessary, because every income and expenditure of company funds can be seen clearly and can be checked at any time. In short, companies will be able to quickly and easily find out the income and expenditure of funds. Information technology which is developing rapidly at this time provides very helpful benefits for the development of a company's information system, especially with the use of computer-based information technology, because by using computer technology in an information system you will be able to process data more quickly with lower error rates. minimal and saves time. The procedures that will be processed consist of the administration section and the finance section. If there is an income or expenditure of money or funds, the data can simultaneously be entered into the computer and will automatically influence or add to the existing data in the company. In this way, the condition of the money or funds in the company can be known with certainty and accuracy.
Evaluating Trust Aware Machine Learning Models for Secure Data Sharing in Distributed Internet of Things and Edge Computing Infrastructures Eko Siswanto; Danang Danang; Sunarmi Sunarmi
International Journal of Computer Technology and Science Vol. 1 No. 1 (2024): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i1.359

Abstract

The rapid growth of Internet of Things (IoT) and edge computing technologies has introduced new security challenges due to the distributed, heterogeneous, and dynamic nature of these environments. Conventional static security mechanisms, such as rulebased authentication and fixed trust models, are often inadequate for addressing evolving threats and abnormal behaviors in largescale IoT systems. To overcome these limitations, this study proposes a machine learningbased trust evaluation framework for enhancing security in distributed IoT environments. The proposed approach dynamically assesses the trustworthiness of IoT nodes by analyzing behavioral and interactionbased features collected at the edge layer. Machine learning models are trained to classify nodes into trusted and malicious categories and continuously update trust values in response to changing network conditions. Based on the predicted trust levels, adaptive security decisions are enforced to allow or restrict node participation in data sharing and computation processes. A quantitative experimental evaluation is conducted using simulated distributed IoT scenarios that include both normal and malicious behaviors. The performance of the proposed framework is evaluated using standard metrics such as accuracy, precision, recall, F1score, and detection effectiveness, and is compared against conventional static trust and rulebased security mechanisms. The results demonstrate that the proposed machine learningbased trust evaluation approach achieves significantly higher detection accuracy and robustness while maintaining low computational overhead. Overall, the findings confirm that integrating machine learning into trust management provides an effective and scalable solution for securing distributed IoT systems under dynamic and adversarial conditions.
Co-Authors Agustinus Budi Santoso Ahmad Ashifuddin Aqham Ahmad Ridwan Alex Ristanto Pratama Arsito Ari Kuncoro Bagus Sudirman Bella Amiria Rahmahima Bilaly Sangare budi hartono Budi Santoso Budi Santoso Budi Winarno Budiman, Eko Wahyu Danang Danang Dani Sasmoko Dendy Kurniawan Dieta Wahyu Asry Dita Riyanto Putro Edwin Zusrony Eka Satria Wibawa, Eka Satria Endrahadi Rahadian Febryantahanuji Febryantahanuji Haris Ihsanil Huda Hendry Syahputra Herry Erwanto I.N.G. Wardana Indra Ava Dianta Islamy, Athoillah Lilik Muslichati M Munifah Mochammad Danara Indra Pradigta Mohamad Badrun Zaman Muhamad Khoirul Umam Muhammad Abduh Muhammad Akmal Mulyono Muhammad Sholikhan Nasrudin Nasrudin Ngurah Ayu Nyoman M Noor Miyono Novi Sri Setiyawati Nuris Dwi Setiawan Nurkholis Hamidi Okky Dwianto Wahyu Nugrohojati Priyo Wibowo Purwanto Purwanto Puspitorini, Palupi Rachmat Subagyo Saputra, Mahmuda Sepriyatno, Riswan Serdani, Army Dita Sifa, Geubrina Dara Sigit Winarko sigit winarno Sigit Winarto Siti Mundrikah Siti Qamariah Tiflen Soedjono Sony Susanto sudirman, bagus Sunarmi Suprapedi Suprapedi Suprapti Suprapti Suwarno Suwarno Toni Wijanarko Adi Putra Tri Endrawati Yosef Cahyo Setianto Zurriyani