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TIN: TERAPAN INFORMATIKA NUSANTARA
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27227987     DOI : -
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Jurnal TIN: TERAPAN INFORMATIKA NUSANTARA memuat tentang Kajian Bunga Rampai dari berbagai ide dan hasil penelitian para peneliti, mahasiswa, dan dosen yang berkompeten di bidangnya dari berbagai disiplin ilmu seperti: Komputer, Informatika, Industri, Elektro, Telekomunikasi, Kesehatan, Agama, Pertanian, Pembelajaran, Pendidikan, Teknologi Pendidikan, Ekonomi dan Bisnis, Manajemen, Akuntansi, dan Hukum
Arjuna Subject : Umum - Umum
Articles 582 Documents
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Implementasi Model Prototype untuk Perancangan Sistem Informasi Project Monitoring Berbasis Web Pratiwi, Rolita; Kholil, Ishak
TIN: Terapan Informatika Nusantara Vol 5 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i2.5307

Abstract

PT. Shuba Mitra Solusi is a business in the form of a limited liability company or PT, with a digital agency type of business. The company routinely receives projects from clients within a specified processing time. The large number of projects being carried out at the same time often makes the team overwhelmed, especially the target completion time. The project stages carried out are planning, work, monitoring and evaluation. Obstacles often faced by companies are that many team members report the results of their work manually so that the project leader does not update the information, team work targets are sometimes missed due to somewhat hampered coordination in reporting, team members do not know the next work after the work is completed, difficulty knowing progress of work carried out by the project team. Such obstacles mean that work plans and targets are not in accordance with initial planning, which results in delays in reporting project progress to clients by the project leader. The Project Monitoring Application Prototype that the author proposes tries to provide a solution as a support system to make it easier for teams to report work progress using the task menu and project menu. This facility also makes it easier to find solutions if there are problems or errors within the team, making the coordination and repair process easier. The application of this application at PT Shuba Mitra Solusi is to make it easier for the team to make work reports, provide information on the status of the work being done, and make it easier for leaders to monitor ongoing projects.
Optimasi Metode Support Vector Machine Menggunakan Seleksi Fitur Recursive Feature Elimination dan Forward Selection untuk Klasifikasi Kanker Payudara Septiany, Eva Senia; Handayani, Hanny Hikmayanti; Mudzakir, Tohirin Al; Masruriyah, Anis Fitri Nur
TIN: Terapan Informatika Nusantara Vol 5 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i2.5324

Abstract

Cancer, the leading cause of global death, results from abnormal cell proliferation that spreads beyond the boundaries of normal tissue. Breast cancer is one of the most common types of cancer, with approximately 2.26 million cases reported in 2020. This research aims to develop a more effective Support Vector Machine (SVM) algorithm for breast cancer classification through efficient feature selection techniques. Previous research has used various algorithms such as K-Nearest Neighbor and Logistic Regression for breast cancer identification. This research focuses on improving accuracy by using alternative feature selection methods such as Recursive Feature Elimination (RFE) and Forward Selection. The dataset used consists of 569 instances with 32 features sourced from the UCI Machine Learning Repository, and classified into benign and malignant categories. Data pre-processing methods, including data cleaning, coding, and feature selection, were applied to the dataset. RFE and Forward Selection techniques were used to identify the most important features for model training. Evaluation of the improved SVM model shows a training accuracy of nearly 100% and a Cross Validation accuracy of 97%, demonstrating the effectiveness of the proposed approach in the context of breast cancer. In addition, the Learning Curve and testing showed the stability of the SVM model with no signs of overfitting or underfitting. Thus, this study developed an SVM algorithm with a feature selection method that produces better accuracy results in breast cancer classification.
Rancang Bangun Sistem Monitoring Daftar Kehadiran Karyawan Berbasis Fingerprint dengan Metode Prototyping Danistian, Angga; Darmawan, Budi; Rachman, A. Sjamsjiar
TIN: Terapan Informatika Nusantara Vol 5 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i1.5345

Abstract

Employee attendance issues are a significant concern in many organizations, particularly regarding fraudulent practices such as proxy attendance and data inaccuracies. Conventional attendance systems relying on signatures or ID cards are often ineffective in preventing these frauds. To address this issue, this study developed a fingerprint-based attendance system integrated with a database and website. The primary objective of this system is to facilitate the attendance recapitulation process, eliminate proxy attendance, and enhance employee awareness and discipline. This system uses fingerprint technology to ensure that each employee is physically present at the time of attendance, thereby improving the accuracy and reliability of attendance data. The research method used is experimental, involving the development of hardware and software with various interconnected components. The results show that this system not only simplifies attendance recapitulation but is also effective in preventing fraud, increasing employee awareness and discipline, and ensuring data security accessible only by the admin. Thus, the fingerprint-based attendance system proves to be an effective solution in addressing attendance issues in the workplace.
Strategi Pengembangan Bisnis Kafe dengan Metode SWOT dan QSPM Ningsih, Margie Subahagia; Sikumbang, Raja Irhas; Rida, Rizkha; Fitri, Li Idi’il
TIN: Terapan Informatika Nusantara Vol 5 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i1.5346

Abstract

Rajin Djalan wants to be more successful and competitive in the coffee shop business in Medan. This study aims to find the best business development strategy for Rajin Djalan in facing competition. Business development strategies are formulated based on SWOT and QSPM analysis. Alternative strategies undertaken for business development should prioritize strategy 2, namely by utilizing social media and creating content that is relevant to consumers and attractive. Results from the SWOT analysis, so the right business development strategy for Rajin Djalan is the S-O (Strengths - Opportunities) strategy, namely using strengths to take advantage of opportunities with alternative strategies: a. Endorsement by Influencer b. Utilize social media and create content that is relevant to consumers and interesting.
Analisis Risiko Pergudangan Menggunakan Metode Hazard Identification Risk Assessment and Risk Control (HIRARC) di Perusahaan Pengeboran Minyak dan Gas Vikaliana, Resista; Melani, Windy
TIN: Terapan Informatika Nusantara Vol 5 No 3 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i3.5356

Abstract

PT Pertamina EP Field subang is part of Pertamina EP which is located in zone 7 regional 2 and is engaged in oil and gas drilling. The production area is spread across Subang and Karawang districts. Pertamina EP Field subang has a division tasked with Supporting all workers' needs, including the need for tools, materials and services, namely the Supply Chain Management (SCM) division. The HIRARC document for the SCM warehouse area does not describe risks based on the actual conditions of the warehouse because the creation of the HIRARC document was carried out before the warehouse was operational so that this situation could influence the risk of work accidents being greater. The aim of this research is to analyze risk by identifying and assessing risks and providing recommendations for appropriate risk control. The method used in this research is the Hazard Identification Risk Assessment and Risk Control (HIRARC) method. HIRARC is a method that aims to minimize the occurrence of accidents in the work area by identifying, assessing and controlling risks. Risk assessment by determining the rating of severity (S) and Probability (P) of potential hazards on each risk obtained in the previous stage carried out by the appropriate experts in this study. Then based on the risk assessment at the general warehouse, the results were obtained that 2 high-risk activities and 6 medium-risk activities were obtained. In the chemical warehouse, it was obtained that there were 1 high-risk chemical material, 5 medium-risk activities and 3 low-risk activities. In the yard warehouse, 3 high-risk activities, 1 medium-risk activity and 1 low-risk activity were obtained. For control recommendations that companies can do to minimize the occurrence of high risks, namely carrying out administrative control in the form of adding safety signs in the loading unloading area of the warehouse yard, making forklift lines, and adding PPE storage areas in the chemical warehouse area.
Penerapan Metode CNN (Convolutional Neural Network) untuk Mengklasifikasikan Jenis Cacat pada Kulit Hewan Frannita, Eka Legya; Prananda, Alifia Revan
TIN: Terapan Informatika Nusantara Vol 5 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i2.5390

Abstract

Recently, leather industry was rapidly growth in several countries. In Indonesia, leather industry became one of the government's priority industries since there were quite a lot of leather industries developing in various regions in Indonesia. On the other hand, there were large number of consumer demand for leather products. Regarding to this fact, maintaining the quality of leather was strongly important. An alternative solution for maintaining leather quality is to conduct leather quality inspection process. However, currently the leather inspection process was still carried out manually by identifying directly the types of defects found on the surface of the leather. This manual inspection process certainly has several hurdles such as time consuming, requiring high accuracy, and requiring experienced operators. This research aimed to develop convolutional neural network architecture that can classify types of leather defects. This research was done by conducting four main processes which were literature study and data collection processes, develop CNN architecture, training process, and testing process. This research work used public dataset consisting of 3600 digital leather images distributed into six classes (folding mask, grain off, growth marks, loose grains, pinhole, non-defective). Based on the training and testing process, the model obtained training accuracy of 90.43% and testing accuracy of 88.47%.
Analisis Pola Penjualan Obat di Apotek Menggunakan Algoritma Apriori Untuk Optimalisasi Stok dan Penjualan Yulindawati, Yulindawati; Yusnita, Amelia; Mayasari, Renni; Melano, M Erick
TIN: Terapan Informatika Nusantara Vol 5 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i2.5407

Abstract

This research aims to identify product sales patterns at Teluk Bayur Pharmacy to optimize stock management and increase sales by using data mining techniques, especially the Apriori Algorithm. Pharmacies are very instrumental in providing drug-related information and are a form of retail trade that sells medicines at more affordable prices compared to hospital services. However, Teluk Bayur Pharmacy often faces difficulties in managing stock, analyzing product sales patterns and consumer behavior, which causes problems of over stock or under stock. Through the application of Association Rule Mining using the Apriori Algorithm, this research analyzes the correlation between products to find frequent purchase patterns. The methods used include literature study, data collection, data preprocessing, application of Apriori Algorithm, evaluation and interpretation of results, and application of conclusions and recommendations. To analyze sales patterns, the data collected exceeded 100 entries, and 12 transactions were selected that represented the most sales each month. The results of testing the analysis utilizing tanagra 1.4.41 software, by setting a minimum support of 40% and a minimum confidence of 70%, from the results of research and testing show that products that are often purchased together by customers are masks, vegeta, and antimo with a confidence value above 70%. The findings are expected to provide insight for Teluk Bayur Pharmacy in understanding consumer behavior and identifying new sales opportunities.
Optimasi Algoritma Machine Learning Menggunakan Seleksi Fitur Xgboost Untuk Klasifikasi Kanker Payudara Ramadhan, Naufal Cahya; H, Hanny Hikmayanti; Rohana, Tatang; Siregar, Amril Mutoi
TIN: Terapan Informatika Nusantara Vol 5 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i2.5408

Abstract

This research analyzes the performance of the K-Nearest Neighbors (KNN), Naïve Bayes, and Random Forest algorithms in the classification of breast cancer diagnosis using the Wisconsin Breast Cancer dataset. The problem discussed is how to improve the accuracy of breast cancer diagnosis classification through appropriate preprocessing techniques. The research objective is to evaluate and compare the performance of the three algorithms after the application of preprocessing which includes data cleaning, handling missing values, data duplication, and outliers, as well as feature selection using XGBoost and SMOTE oversampling. application of feature selection to identify the most relevant features and SMOTE to balance the class distribution in the dataset. Performance evaluation results using a confusion matrix show that Random Forest has the best performance with high accuracy, precision, recall, and F1-score, reaching an AUC of 98% after the application of SMOTE. The combination of feature selection and SMOTE was shown to significantly improve model performance, although KNN showed a decrease in performance with SMOTE, while Naïve Bayes experienced a considerable improvement. This study demonstrates the importance of preprocessing techniques in the development of machine learning models for medical applications, emphasizing that appropriate techniques can significantly improve classification performance and result in more accurate diagnoses.
Analisis Faktor Layanan, Reputasi dan Keamanan yang Mempengaruhi Keputusan Gen Z Menggunakan Perbankan Syariah Lauza, Atiqa; Rasyidin, M.; Saleh, M.; Zulfikar, Zulfikar; Nova, Nova; Rizkina, Azka
TIN: Terapan Informatika Nusantara Vol 5 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i2.5456

Abstract

TSharia banking is a bank that conducts business based on the principles of Islamic law or Sharia. Bank Shariah has introduced various products with features and amenities aimed at attracting Generation Z to use Bank Shariah's services. The objective of this study is to analyze the factors that influence decisions regarding the use of Islamic banking services. The subject of this research is Gen Z’s in Aceh. This type of research uses a quantitative approach. Data sources using online or electronic questionnaires with Google Forms Media. The data collection method uses an anonymous demographic technique with a sample size of 102 respondents. This study examines three factors of Shariah banking users' decisions to influence their decision to use Shariah banking services among Gen Z’s in Aceh, such as service, reputation and security variables. The results show that service, reputation and security variables influence Gen Z's decision of legitimate banking services in Aceh.
Designing and Evaluating an Effective Online Training Program for Health Information Systems Implementation in Indonesia Raharjo, Untoro Dwi
TIN: Terapan Informatika Nusantara Vol 5 No 3 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i3.5506

Abstract

Online training for health information system (HIS) introduction and capacity building offers a valuable solution for reaching remote healthcare providers. This approach provides cost-effectiveness and broad geographical reach. However, despite these advantages, online training presents several challenges, complicating its development. We aimed to design a precise online training program systematically which can be an alternative to reach remote healthcare providers. We also intend to give an important evaluation and possibility of online training in improving healthcare providers related to health information system. This paper shared insights from implementing online training for a zoonosis information system through an action research approach using a four-cycle process. We collaborated with stakeholders from various sectors, targeting healthcare providers at Primary Healthcare Centers (PHCs), zoonosis program coordinators from District and Provincial Health Offices across 10 regions in Indonesia, and national-level stakeholders. To ensure seamless online training, we used multiple platforms, including a Learning Management System, Wiki.js, Zoom Meetings, and an online discussion group. A hierarchical training model was developed, allowing national stakeholders to become trainers in future sessions. Despite the benefits in delivering new knowledge and experience in HIS, significant challenges included internet connectivity issues, affecting 60.00% of participants. The participants’ experience was a positive based on Community of Inquiry (CoI) evaluation framework. The evaluation showed that participants generally had a positive experience. Overall, online training proves to be an effective strategy for enhancing the information and technology skills of remote healthcare providers in HIS.

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