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All Journal Teknika AUSTENIT Jurnal Informatika Jurnal Informatika Scientific Journal of Informatics INOVTEK Polbeng - Seri Informatika Jurnal Teknologi Informasi dan Terapan (J-TIT) Journal of Applied Health Management and Technology Jurnal Pengabdian Nasional TIERS Information Technology Journal Unram Journal of Community Service (UJCS) Batara Wisnu : Indonesian Journal of Community Services Indonesian Accounting Literacy Journal Proceeding Applied Business and Engineering Conference Jurnal Ilmu Komputer, Sistem Informasi, Teknik Informatika (JILKOMSITI) ROUTERS: Jurnal Sistem dan Teknologi Informasi Jurnal Ilmiah ESAI West Science Social and Humanities Studies Hanif Journal of Information Systems Student Journal of Business and Management (SJBM) Journal of Progressive Information, Security, Computer and Embedded System Riau Jurnal Teknik Informatika Journal of Software Engineering And Technology
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PENGGUNAAN METODE VIKOR UNTUK MEMBANTU MENENTUKAN KEPUTUSAN DALAM SELEKSI BEASISWA Fitra, Jaka; Saputra, Kurniawan
Journal of Software Engineering and Technology. Vol 3, No 1 (2023): SEAT: Journal Of Software Engineering and Technology
Publisher : Institut Teknologi dan Bisnis Diniyyah Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69769/seat.v3i1.80

Abstract

Beasiswa diartikan sebagai bantuan finansial yang diberikan kepada mahasiswa yang berprestasibaik dibidang akademik maupun non-akademik dan mahasiswa yang mengalami keterbatasan ekonomi. Seleksi penerima beasiswa masih dilakukan secara konvensional yaitu dilakukan oleh karyawan dan keputusan pembuat dalam hal ini dilakukan oleh Kepala perguruan tinggi,  seleksi secara konvensional sangat dipengaruhi waktu yang terbatas dan dilakukan oleh karyawan yang merangkap pekerjaan lain,  sehingga faktor Subjektivitas dalam pengambilan keputusan sangat besar. Seleksi beasiswa yang dilakukan seacara konvensional, memiliki kelemahan yaitu dalam melakukan seleksi dengan menggunakan banyak orang, sehingga dapat menimbulkan kesalahan dan ketidak konsistenan penilaian. Penulis menggunakan metode VIKOR sebagai perangkingan penentuan penerima beasiswa. Metode VIKOR adalah metode Multi-Criteria Decision Making (MCDM) yang bisa digunakan untuk memilih lebih dari satu kriteria. Hasil penelitian menunjukkan bahwa metode VIKOR dapat membantu proses seleksi dan menentukan penerima beasiswa. Selain itu, metode VIKOR bisa membuat peringkat kompromi alternatif dari sejumlah alternatif yang ada. Hasil penelitian menunjukkan bahwa VIKOR dapat diaplikasikan di program studi sebagai metode membantu pengambilan keputusan, metode VIKOR dapat membantu proses seleksi penerima beasiswa yang tepat. Selain itu, metode VIKOR bisa dapat melakukan pengurutan pemeringkatan sebagai alternatif kompromi dari sejumlah alternatif yang ada.
Assistance For MSMES in The Adoption of Digital Marketing of Local Food Products Sutarni, Sutarni; Berliana, Dayang; Saputra, Kurniawan; Fitriani, Fitriani
Unram Journal of Community Service Vol. 5 No. 4 (2024): December
Publisher : Pascasarjana Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ujcs.v5i4.741

Abstract

One of the agro-industry players in processed food products in Punggur District, Central Lampung Regency, Lampung Province, is KWT Canala. KWT in Punggur Regency merged into an organization called the KWT forum of Punggur Regency. The application of digital marketing technology in KWT in Punggur District, Central Lampung Regency is;  The application of the internet is still very limited, this is due to the low skills of internet applications that can be used in business. The low use of digital media in business is caused by incompetent expertise in using the internet, social media, marketplaces, and product promotion.  Therefore, it is necessary to provide assistance to KWT members in implementing digital marketing so that sales volume increases. This program aims to provide assistance to MSMEs in Punggur Regency related to the manufacture of attractive labels and packaging that are able to compete in the market as well as the application of digital marketing in improving the performance of local food product businesses so that it can increase KWT's sales volume and revenue. The methods used are lectures, discussions and demonstrations through pre-activity activities (permit management, consolidation), exercises and demonstrations, development and evaluation of online stores (initial evaluation, process evaluation and evaluation of results or sustainability impacts). The result of this program is to improve the knowledge and skills of MSME managers in Punggur District about making labels, packaging and the use of digital marketing for products to be produced. 
RANCANG BANGUN PROTOTYPE PRESS TOOL PEMOTONG SIDE RUBBER SEBAGAI KOMPONEN CHUTE DENGAN SISTEM HIDROLIK Sundari, Ella; Asrafi, Ibnu; Prabudi, Darma; Kurniawan, Dede; Saputra, Kurniawan; Nopriansyah, Agi
AUSTENIT Vol. 7 No. 2 (2015): AUSTENIT: Oktober 2015
Publisher : Politeknik Negeri Sriwijaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (860.849 KB)

Abstract

Press tool adalah alat bantu yang digunakan untuk membentuk/memotong produk dari bahan dasar lembaran yang pengoperasiannya menggunakan mesin press. Pada saat ini, proses pemotongan side rubber yang ada di lapangan masih dilakukan secara manual dengan menggunakan tenaga kerja untuk melakukan pengukuran, pengeplongan dan pemotongan dari  rubber sheet. Dari hasil penelitian didapatkan bahwa gaya potong maksimum dari press tool yang dihasilkan sebesar 6646,53 kgf dan power hidrolik yang digunakan sebesar 8357,9 kgf. Kapasitas produksi dari press tool yaitu dapat menghasilkan 1 pola dalam waktu 40,8 detik atau sekitar 88 pola side rubber dalam waktu 1 jam. Ukuran pola side rubber yang dihasilkan dengan pengerjaan menggunakan alat bantu press tool lebih presisi dibandingkan dengan pengerjaan manual. Analisa kontrol kualitas dari side rubber dilakukan dengan menggunakan statistik, dimana didapatkan bahwa nilai pengukuran panjang dan tinggi yang dihasilkan dari pengujia masih berada diantara nilai Batas Kontrol Atas dan Batas Kontrol Bawah sehingga hasil pengerjaan masih bisa dianggap baik dan mesin dapat digunakan untuk proses produksi selanjutnya.
THE ROLE OF DCM4CHEE AS AN OPEN SOURCE PACS IN THE RADIOLOGY DEPARTMENT OF PRIMAYA HOSPITAL SEMARANG Nuha, M. Dzawin; Wibowo, Gatot Murti; Setjadiningra, Rr. Lydia Purna Widyastuti; Saputra, Kurniawan; Puspita, Mega Indah; Pranandya, Brian Ilham
Journal of Applied Health Management and Technology Vol. 6 No. 1 (2024): April 2024
Publisher : Postgraduate Program , Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31983/jahmt.v6i1.10886

Abstract

This research explores the potential use of DCM4CHEE as an open-source Picture Archiving and Communication System (PACS) that is highly flexible for development in the current era. Despite being open source, DCM4CHEE has proven to be effective and reliable in healthcare settings, particularly in radiology department. Primaya Hospital Semarang has successfully implemented DCM4CHEE as an integrated archive system directly connected to CT Scan and Conventional X-Ray modalities. Direct observations were conducted over a significant period at the radiology installation of Primaya Hospital Semarang, which utilizes DCM4CHEE. This provided direct insights into how the system is implemented and used in practical situations. Furthermore, in-depth interviews were conducted with radiographers to gain their perspective on the experience of using DCM4CHEE. The research results indicate that the use of DCM4CHEE contributes positively in various aspects, including user-friendly operation, adequate utility, workflow improvement, and cost savings in healthcare services. The implementation of this software not only aids in the efficient management of radiological data but also reduces dependence on traditional filming systems, supporting the transition towards a paperless workflow. In conclusion, DCM4CHEE is reliable and highly beneficial in the context of healthcare services. Its adaptability allows seamless integration with Hospital Information Systems (HIS) and Radiology Information Systems (RIS), enhancing overall interoperability and efficiency. This research provides a foundation for recommending the use of DCM4CHEE as a customizable PACS solution that can positively contribute to improving the quality of radiology services in various healthcare department.
Hybrid Machine Learning Approach for Nutrient Deficiency Detection in Lettuce Zuriati, Zuriati; Widyawati, Dewi Kania; Arifin, Oki; Saputra, Kurniawan; Sriyanto, Sriyanto; Ahmad, Asmala
TIERS Information Technology Journal Vol. 6 No. 2 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v6i2.7143

Abstract

Early detection of nutrient deficiencies in lettuce is essential for precision agriculture. However, this task remains challenging due to limited data availability and class imbalance, which reduce model sensitivity toward minority classes and hinder generalization. This study introduces a hybrid machine learning approach integrating SMOTE, Optuna, and SVM to enhance the accuracy of nutrient deficiency classification using digital leaf image analysis. The dataset, obtained from Kaggle, includes four categories: Nitrogen Deficiency (-N), Phosphorus Deficiency (-P), Potassium Deficiency (-K), and Fully Nutritional (FN). Image features were extracted using MobileNetV2 pretrained on ImageNet and classified with a Support Vector Machine. Three scenarios were tested: (1) SVM before SMOTE, (2) SVM after SMOTE, and (3) Optuna-SVM after SMOTE, evaluated using accuracy, precision, recall, and f1-score. The hybrid model achieved the best performance with accuracy 0.929, precision 0.946, recall 0.835, and f1-score 0.869, outperforming the other scenarios. This hybrid framework effectively addressed class imbalance and improved classification margin stability through adaptive hyperparameter tuning using the Tree Structured Parzen Estimator within Optuna. The novelty of this study lies in combining MobileNetV2 based feature extraction with SMOTE and Optuna-SVM for small agricultural datasets. The proposed approach offers an efficient, accurate, and practical solution for automated nutrient deficiency diagnosis and contributes to the development of AI-driven smart agriculture systems.
Analisis Pengaruh Service Quality, Perceived Value Dan Institution Image Terhadap Kepuasan Mahasiswa Universitas Bengkulu Saputra, Kurniawan; Hadi, Effed Darta; Anggarawati, Sularsih
Student Journal of Business and Management Vol. 8 No. 2 (2025)
Publisher : Universitas Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/sjbm.v8i2.33274

Abstract

This research was conducted to obtain an overview of service quality at Bengkulu University by linking it to various aspects as implications of the implementation of quality services. The aim of this research is to analyze the influence of service quality, perceived value, and institutional image on student satisfaction at Bengkulu University. The population of this research is Bengkulu University students from various faculties who have studied for at least 2 semesters (third semester and above). The sampling method that collects data is purposive. The sample size was 268 respondents. The research results found that: 1) Service quality has a positive and significant influence on student satisfaction at Bengkulu University. This means that the better the quality of educational services, the better the satisfaction of Bengkulu University students. 2). Perceived value has a positive influence on student satisfaction at Bengkulu University. This means that if the perceived value increases, student satisfaction will increase. 3). The image of the institution has a positive effect on student satisfaction at Bengkulu University. This means that improving the image of the institution will have an impact on increasing student satisfaction at Bengkulu University. 4). Service quality, perceived value, and institutional image have a positive influence on Bengkulu University student satisfaction.
Improving the Accuracy of Lettuce and Weed Classification Based on MobileNetV2 Features Through Segmentation Akhmad Jayadi; Kurniawan Saputra; Ahmad Rofi'i
Hanif Journal of Information Systems Vol. 3 No. 2 (2026): February Edition
Publisher : Ilmu Bersama Center

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

Abstract

Automating the separation of commodity crops and weeds is a major challenge in the implementation of precision agriculture . The presence of complex backgrounds such as soil, rocks, and shadows often degrades the performance of feature extraction in computer vision classification models. This study proposes an image preprocessing approach using the GrabCut segmentation method to extract key crop objects cleanly before performing Deep Learning- based feature extraction . Representative features from the image are extracted using the lightweight and efficient MobileNetV2 architecture. Next, classification is performed by comparing three Machine Learning algorithms , namely Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RF). Testing is carried out on two data scenarios, namely the original dataset ( Original ) and the segmented dataset ( GrabCut ). The experimental results show that the use of original images produces an accuracy of 98.89% for all three classification models. However, after being integrated with GrabCut segmentation, the accuracy of all three models increases significantly to 100.00%. These results prove that GrabCut-based segmentation effectively eliminates background noise information , thereby improving the generalization capabilities of classification models perfectly on edge computing devices .
Smart Farming: Optimalisasi Produksi Telur Ayam Petelur menggunakan Sistem Cerdas Monitoring Suhu dan Kelembaban Kandang Berbasis IoT Panji Pratomo; Kurniawan Saputra; Dita Novita Sari; Yoeyong Rahsel; Ricco Herdiyan Saputra; Bambang Suprapto; Henry Simanjuntak
Riau Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Maret 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i1.3264

Abstract

Egg production of laying hens is influenced by various factors, including temperature, humidity, and the quality of the cage environment. The main problem in this study is the fluctuation of production due to changes in environmental conditions that are not optimal. This study aims to develop and implement a smart farming system based on the internet of things (IoT) that is able to optimize egg production of laying hens through automatic monitoring of cage temperature and humidity. The methods used include needs analysis, design, implementation and testing. The results showed that the accuracy of the system reached 80% which could maintain the cage environmental conditions within the optimal range, so that egg production increased from an average of 383.67 eggs per month to 390.33 eggs per month.
Analisis Kebutuhan Fitur Minimum pada Klasifikasi Lettuce dan Weed Berbasis MobilenetV2 dan Support Vector Machine Akhmad Jayadi; Ahmad Rofi'i; Kurniawan Saputra
Progressive Information, Security, Computer, and Embedded System Vol. 4, No. 1 Maret (2026)
Publisher : Sakura Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/pisces.v4i1.1388

Abstract

Automating weed removal in lettuce cultivation requires a lightweight and fast computer vision system for implementation on mobile or edge devices. This study aims to analyze the minimum number of features extracted from the MobileNetV2 architecture to accurately classify lettuce and weeds. Features extracted from the global average pooling layer of MobileNetV2 yielded 1,280 base features. The SelectKBest method with Mutual Information criteria was used to reduce the feature dimensionality, followed by classification using a Support Vector Machine (SVM) based on the Radial Basis Function (RBF) kernel. Experimental results showed that the model achieved 100% accuracy using only two minimum features, representing a feature reduction of 99.84%. This feature reduction significantly speeds up computation time, making it ideal for mobile-based computing in the smart agriculture sector.
Co-Authors - Nurmala - Nurmala Ade Irma Rilyani Ahmad Rofi'i Ahmad Syarief, Ahmad Ahmad, Asmala Akhmad Jayadi Andhika Pratomo, Panji Arifin, Oki Asrafi, Ibnu Bambang Suprapto Darma Prabudi Dayang Berliana Dede Kurniawan Dita Novita Sari Dita Novita Sari, Dita Dwi Setiawan Dwirgo Sahlinal Dwirgo Sahlinal, Dwirgo Fitra, Jaka Fitriani Fitriani Gatot Murti Wibowo, Gatot Murti Hadi, Effed Darta Halim Fathoni, Halim Hamid, Farid Alfalaki Henry Simanjuntak Imam Asrowardi Jaya, Tri Sandika Mega Indah Puspita Mochammad Yusman Muhammad Farhan, Farhan Nopriansyah, Agi Nugroho, Budi Sulistiyo Nuha, M. Dzawin Nurrahman, Arif Oki Arifin Panji Pratomo Pranandya, Brian Ilham Pratomo, Panji Andhika Putra, Rizky Bimantara Rahsel, Yoeyong Ricco Herdiyan Saputra Rima Maulini Sahlinal, Dwrigo Setjadiningra, Rr. Lydia Purna Widyastuti Sriyanto, Sriyanto Subyantoro, Eko Sularsih Anggarawati Sundari, Ella Supriatna, Iyeh Sutarni, Sutarni Tri Sandhika Jaya Widyawati, Dewi Kania Yanti Rufaedah, Yanti Yoeyong Rahsel Zuriati, Zuriati