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Olivia Kembuan
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oliviakembuan@unima.ac.id
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jointer@unima.ac.id
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Program Studi Teknik Informatika Fakultas Teknik, Kampus Unima di Tondano, Minahasa, Sulawesi Utara
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JOINTER : Journal of Informatics Engineering
Published by Universitas Negeri Manado
ISSN : -     EISSN : 27237958     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Journal of Informatics and Engineering (Jointer) diterbitkan oleh Program Studi Teknik Informatika, Fakultas Teknik (FATEK) Universitas Negeri Manado (UNIMA) setiap bulan Juni dan Desember dengan nomor e-issn : 2723-7958. Jointer merupakan jurnal open-access atau dengan kata lain semua artikel yang diterbitkan bersifat terbuka dan dapat diakses tanpa biaya untuk mendukung pertukaran pengetahuan secara global. Jointer menerbitkan artikel penelitian (research article), artikel telaah/studi literatur (review article/literature review), laporan kasus (case report) dan artikel konsep atau kebijakan (concept/policy article), di bidang-bidang menyangkut Teknologi Informasi seperti berikut : Business Process Management Business Intellegent Computer Architecture Design Computing Theory Conceptual Modeling, Languages and design Computer Network Data Mining Data Warehouse Decision Support System e-Healthcare, e-Learning, e-Manufacturing, e-Commerce Embedded system Enterprise Application ERP dan Supply Chain Management Geographical Information System Human Computer Interaction Image Processing and Pattern Recognition Information Infrastructure for Smart Living Spaces Information Retrievel Information Security Information-centric Networking Intelligent Transportation Systems IT Management dan IT Governance Media, Game and Mobile Technologies Models, Methods and Techniques Natural Language Processing Network Computer Security Remote Sensing Robotic Systems Smart Appliances & Wearable Computing Devices Smart City Smart Cloud Technology Smart Sensor Networks Smart Systems Software Engineering
Arjuna Subject : Teknik (semua kategori) - Teknologi Media
Articles 5 Documents
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Search results for , issue "Vol 5 No 01 (2024): JOINTER : Journal of Informatics Engineering" : 5 Documents clear
Implementasi Algoritma Needleman-Wunsch dalam Pengujian Tingkat Kemiripan DNA Babi Sulawesi Utara Ngovangari, Rivchi Hanni; Rorimpandey, Gladly Caren; Kembuan, Olivia; Sumual, Hendro Maxwell
JOINTER : Journal of Informatics Engineering Vol 5 No 01 (2024): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v5i01.32

Abstract

Data is a collection generated from various media used by humans. DNA data is a form of data, which is data in the form of genetic code text to store biological identities and characteristics of living things. This study used DNA to test the similarity level of North Sulawesi pigs. The method used is the Pairwise Sequence Alignment method. With sequences of different DNA lengths, the researcher implemented the Needleman-Wunsch algorithm for alignment. Matching is used using the BioPython module, which is in pairwise2. And this study produces a model and proportion of the similarity level of North Sulawesi Pigs that can be used as future references for biological research on molecular biology or for the field of informatics in implementing Needleman-Wunsch algorithm in Python, or references and additional knowledge for research in Bioinformatics.
Rancang Bangun Repository Publikasi Dosen di Universitas Negeri Manado Menggunakan Metode Waterfall Fadly Iriansyah
JOINTER : Journal of Informatics Engineering Vol 5 No 01 (2024): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v5i01.88

Abstract

Scientific publications and research are essential aspects of the development of science. Lecturer's scientific publications are also a requirement for accreditation and will be a continuous assessment cycle in the assessment of study programs at UNIMA. LPPM UNIMA has the task of managing the publications of each lecturer, but the collection of lecturer publications is still operated manually. LPPM must contact the lecturers individually to hand in the publication, which is recorded in Excel and archived in the LPPM storehouse. These problems prompted the creation of a repository at UNIMA to facilitate the management of lecturer publications and to present recapitulation reports for lecturer publications development. The repository uses the Waterfall method from the analysis, design, and coding to the testing stages. The system modeling is documented, namely Data Flow Diagrams (DFD). The testing method of the repository uses the Black-box testing method so that it can answer and show that the repository was created pursuant to the objectives of the researcher and is able to meet user needs.
Klasterisasi Daerah Rawan Kriminalitas di Sulawesi Tenggara Menggunakan Metode K-Means Clustering -, Muh. Afdal Ziqri Ramadhan
JOINTER : Journal of Informatics Engineering Vol 5 No 01 (2024): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v5i01.289

Abstract

Crime is anything that relates to unlawful behavior. In every society, the presence of crime affects social dynamics, levels of security, and general well-being. Southeast Sulawesi in the midst of its diversity is facing a significant increase in crime, this is evident from the 3,000 cases that have been reported. The purpose of this research is to categorize crime-prone areas in Southeast Sulawesi using the K-Means Clustering method. K-Means is a research data analysis method or a data mining method that will carry out modeling without supervision (unsupervised). The data from this research was taken from the sultra.bps.go.id web page. The data taken in the form of data on the number of crimes and the percentage of crime victims in the regions of Southeast Sulawesi. The results of this study obtained 3 clusters of crime-prone areas in Southeast Sulawesi. The clustering evaluation results if calculated by the Daviees Bouilden Index method is as much as 0.5904 index.
Sistem Pendukung Keputusan Seleksi Penerima Bantuan Sosial Menggunakan Metode Simple Additive Weighting Sitanayah, Lanny; Kansil, Rayuni A.F; Kumenap, Vivie D
JOINTER : Journal of Informatics Engineering Vol 5 No 01 (2024): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v5i01.313

Abstract

Social assistance is a program or provision of funds organized by the government or non-government to help individuals, families or community groups in need. The government allocates social assistance funds to protect society from possible social risks, increase economic capacity and/or social welfare. In Kelurahan Bebali Siau Timur, the distribution of social assistance has been implemented since 2011 in the form of assistance for family economic welfare (clothing and food). The distribution of social assistance is carried out by registering data on every family registered in Kelurahan Bebali, namely 325 heads of families. The large amount of data on families receiving social assistance with quite a lot of criteria makes employees in the selection section for receiving social assistance less efficient in inputting the existing data. This research aims to help selection employees for receiving social assistance in selecting families who are worthy of receiving social assistance and increasing efficiency in inputting existing data by building a Decision Support System for Selection of Social Assistance Recipients Using the Simple Additive Weighting Method. It is hoped that this system can help in selection and increase the efficiency of data entry. Based on the results of the tests that have been carried out, the Decision Support System for Selection of Social Assistance Recipients Using the Simple Additive Weighting Method can help selection employees in selecting and increasing the efficiency of data input.
Implementasi Random Forest dalam Klasifikasi Kanker Paru-Paru Benaya, Dony
JOINTER : Journal of Informatics Engineering Vol 5 No 01 (2024): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v5i01.331

Abstract

Lung cancer is a serious disease that threatens global health due to its high morbidity and mortality rates. To reduce lung cancer mortality, a more precise diagnostic approach is needed. The aim of this study was to improve the sensitivity and specificity in detecting lung cancer, to support early detection efforts and more effective management. The research method involved a series of steps from data collection to model performance evaluation. Data was collected, cleaned, and analyzed for correlation before going through the preprocessing stage. Model training was conducted using the Random Forest Classifier algorithm, which proved effective in modeling the complexity of lung cancer data. The results prove that the model used can achieve an accuracy rate of 78%. The uniqueness of this research lies in the application of machine learning techniques to improve lung cancer diagnosis. By combining ADASYN oversampling with the Random Forest Classifier algorithm, this research has proven potential in the sensitivity and specificity of detecting the disease. These findings provide an important foothold in the development of more advanced and efficient diagnostic methods for lung cancer, paving the way for more effective early detection efforts and better disease management.

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