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Jurnal Tekinkom (Teknik Informasi dan Komputer)
Published by Politeknik Bisnis Indonesia
ISSN : 26211556     EISSN : 26213079     DOI : https://doi.org/10.37600/tekinkom
Core Subject : Science,
Computer Science & IT
Jurnal TEKINKOM merupakan jurnal yang dimaksudkan sebagai media terbitan kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai isu Ilmu - ilmu komputer dan sistem informasi, seperti : Pemrograman Jaringan, Jaringan Komputer, Teknik Komputer, Ilmu Komputer/Informatika, Sistem Informasi, dan Multi Disiplin Penunjang Domain Penelitian Komputasi, Sistem dan Teknologi Informasi dan Komunikasi, dan lain-lain yang terkait. Artikel ilmiah dimaksud berupa kajian teori (theoritical review) dan kajian empiris dari ilmu terkait, yang dapat dipertanggungjawabkan serta disebarluaskan secara nasional maupun internasional.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 407 Documents
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IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI DALAM MENENTUKAN PERSEDIAAN OBAT Gesta Wulandari; Sasmita Sasmita; Fitria Rahmadayanti
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1270

Abstract

This study aims to enhance the efficiency of drug inventory management at UPTD Puskesmas Rawat Inap Bandar Kota Pagar Alam by applying the Apriori algorithm to analyze patient drug purchasing patterns. The dataset consists of 470 drug transactions from January to May 2023, with a minimum support of 12% and a minimum confidence of 10%. The research follows the CRISP-DM method, which includes business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Analysis using RapidMiner revealed several association patterns, such as patients who purchase ibuprofen 400 mg also tend to buy calcium lactate 500 mg with a confidence of 0.100, and patients who buy sanmol 500 mg also buy pyrantel pamoate tab scored 125 mg with a confidence of 0.122. Implementing this algorithm helps the health center manage drug inventory more effectively, reducing overstock and understock issues, and minimizing errors in drug data recording. The study concludes that the application of the Apriori algorithm is beneficial for identifying drug purchasing patterns, thereby improving the quality of healthcare services at the health center.
APLIKASI PENGENALAN PLANET PADA TATA SURYA BERBASIS AUGEMENTED REALITY Indrawan Gustha Wisesha; Ikrimach Ikrimach
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1059

Abstract

The use of Information Technology (IT) in the process of conveying information about the world of education is experiencing rapid development. Currently, the newest technology used to convey information is Augmented Reality (AR) technology. In AR technology, users can visualize objects in 3 dimensions. AR has the advantage of being interactive and real time so that AR is widely implemented in various fields, especially in the field of education. In the world of education, AR is used as a medium to introduce the planets in the solar system. The aim of this report is to review the use of AR technology in introducing elementary school students to the planets in the Solar System. Based on the results of a review of several journals relevant to AR research, information was obtained that AR technology can be used as a medium to introduce planets in the solar system to elementary school students. In making AR applications, the methods used can use Marker Based Tracking and Markless AR methods.
PENGEMBANGAN TEKNOLOGI OPTICAL CHARACTER RECOGNITION DI FLUTTER BERUPA DETEKSI TEKS PADA GAMBAR Shierly Mayco Angela; Ade Eviyanti; Metatia Intan Mauliana
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1167

Abstract

This research aims to develop Optical Character Recognition (OCR) technology integrated with the Flutter platform to detect text in images in mobile applications. OCR technology allows extracting text from images automatically, eliminating the need for manual intervention, and is implemented using the Tesseract OCR library which is known to have a high level of accuracy. By combining Flutter, a multi-platform application development framework developed by Google, this research produces an application that is able to detect text from images taken via the kamera or cell phone gallery with fast response and high accuracy. The Rapid Application Development (RAD) approach was used in developing this system. Research stages include requirements planning, system design, system development, and implementation. System testing is carried out using the Black box testing method to ensure all features work according to specifications, as well as User Acceptance Testing (UAT) to assess user satisfaction. The test results show that the application runs well and is accepted by users with a strongly agree level of approval (88%). This research contributes to creating an efficient and intelligent mobile application for detecting text in images, which can be used for various purposes, such as searching for digital comic references, detecting text on food menus, and identifying vehicle number plates.
PENERAPAN DATA MINING DALAM MEMPREDIKSI INFLASI LISTRIK DAN BAHAN BAKAR RUMAH TANGGA MENGGUNAKAN METODE REGRESI LINEAR Putra Edi Mujahid; Jansen Yudistira Sembiring Meliala; Albert Pratama Sembiring
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.931

Abstract

In a period of several years, the Indonesian economy has experienced low inflation in all sectors, including Indonesia's electricity and fuel. This increase in the price of electricity and household fuel can trigger inflation in other economic sectors, because these two things are necessities human tree. The purpose of this study is to analyze the application of data mining in predicting household electricity and fuel prices using the regression method. Electricity and house gas prices are important indicators related to financial stability and public health. This study uses data mining methods to identify patterns and trends in local electricity and gas prices. The linear regression method is used as an analytical tool to develop predictive models based on historical data. The dataset was obtained through the Central Statistics Agency from 2021 to 2022 which includes monthly inflation data from 90 cities throughout the year. The results of this study are predictions of annual inflation that will occur. Using data mining and linear regression methods, this research has the potential to be a useful tool for generating better home electricity and fuel price control strategies. This research can also be the basis for further research in the same or other fields.
SISTEM INFORMASI PENGELOLAAN DATA HASIL PRODUKSI PADA PT.PUTRA MANDIRI INTIPACK Taufiki Ma'rufan; Nuril Lutvi Azizah; Ika Ratna Indra Astutik
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.910

Abstract

The development of the current era of globalization is very sophisticated. Therefore, information systems using computer technology will make it easier for us to manage data. In this case there are problems in the process of recording the production data management information system at PT. Putra Mandiri Intipack. using a manual or paper system which can result in errors in the management of production data. Therefore, to overcome these problems, a web-based production data management information system is needed. With this system, it can reduce errors in data storage and make it easier for the production department to input data. The purpose of this research is to build a production data management information system at PT. Putra Mandiri Intipack uses the codeigniter4 framework and uses the research and development (R&D) method and the results of the blackbox testing show that the production data management information system has all the features functioning as they should. Data from user testing observations with the highest presentation value of 64.7% and lowest 0.0%. The results of this study are in accordance with what is believed by PT. Putra Mandiri Intipack which includes management of data printing, lamination, slitting and sales. Data entry includes date, number, item name, amount and description. It is hoped that this system will make it easier for companies to manage production data and store data properly.
SMART ROBOT OBJECT DETECTION MENGGUNAKAN ESP-32 CAM Deni Nurdiansyah; Satrianansyah Satrianansyah; Ahmad Sobri
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1296

Abstract

Object detection is a method to recognize the class and location of objects in an image. The main challenge is integrating complex algorithms into lightweight and portable hardware, especially with expensive sensor and camera technologies. This research aims to develop an object detection system using the ESP-32 Cam for robotics monitoring and security. The focus is on utilizing the Yolov5 model transformed into TensorFlow Lite for integration with ESP32 AI CAMERA, expected to detect objects in real-time at a low cost. The methodology includes collecting 1710 datasets from 27 images, dividing the data into 70% training, 20% validation, and 10% testing, and labeling the dataset in Roboflow. The object detection model uses Yolov5, transformed into TensorFlow Lite, and implemented in ESP32 AI CAMERA with ESP-32 Cam as the microcontroller. Model evaluation shows high performance with mAP 95%, precision 97%, and recall 100%, indicating high accuracy. The research successfully develops an efficient and affordable object detection system with ESP-32 Cam and TensorFlow Lite from Yolov5. This integration enables the development of wheeled robots capable of real-time object detection, providing an effective solution for portable robotics monitoring and security.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PRODUKTIVITAS TANAMAN TERBAIK DENGAN MENGGUNAKAN METODE TOPSIS Nina Sari Rizki; Angga Putra Juledi; Deci Irmayani
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.1058

Abstract

This research aims to solve the problem of selecting plants that have the best agricultural productivity, especially in the Bagan Sinembah area. The selection of these plants is based on plants that are quick to harvest and easy to cultivate, which is done to support food security and the local economy. To overcome the complexity in decision making related to plant selection, this research designed a Decision Support System (DSS) using the TOPSIS Method. This method was chosen because it can provide plant recommendations that are effective, efficient, and in accordance with the specified criteria. The research method involves preliminary studies, determining relevant criteria, and collecting data through field surveys. The criteria used in this research consist of Growth Time, Ease of Cultivation, High Production Yield, Production Cost, and Adaptation to the Environment. Criteria weights are determined based on preference and relative importance. The data is then processed using the TOPSIS method to rank alternative plant choices. The analysis results show the ranking of plants based on their relative proximity scores to positive and negative ideal solutions. The results of this research showed that the recommendation for the plant with the best productivity was Alternative A5 with a preference value of 0.74732. The existence of this decision support system can make a positive contribution to the development of the agricultural sector, especially in increasing the productivity of crops that are quick to harvest and easy to cultivate in the Bagan Sinembah area.
MENGGALAKKAN KEPARIWISATAAN KABUPATEN BIMA DENGAN KONSEP PENYEBARAN INFORMASI WISATA MENGGUNAKAN MODERNISASI WEBSITE Layati Layati; Joko Aryanto
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.1027

Abstract

Bima Regency has a lot of tourist attractions, but there are still many people who do not know about them, including the people of Bima itself and also from outside the region, because of the difficulty of getting information about tourist attractions in Bima Regency. This research aims to create a web-based Bima Regency tourism information system that can introduce various tourist attractions to the wider community in order to improve the performance of tourism marketing in Bima Regency. This tourism information system was built using the PHP programming language and MySQL as the database. The system development method used is waterfall, which consists of the stages of needs analysis, system design, coding, testing, and maintenance. The tourist data displayed includes descriptions of attractions, locations, accessibility, facilities, costs, and documentation in the form of photos. The result of the research is an information system that can help make it easier for tourists to get information about tours in Bima district, and this website makes it easier for tourists from outside the area to book tour packages and hotel reservations.
IMPLEMENTASI REST API PADA APLIKASI DONOR DARAH BERBASIS MOBILE DAN WEB Rizky Ramadhani; Adam Sekti Aji
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.1016

Abstract

Blood is one of the most important parts of the human body. Blood is useful for circulating oxygen throughout the human body. If someone experiences anemia due to an accident or suffers from anemia, even the accumulation of dirty blood in the body can cause diseases that endanger life, health and even human life. Blood donation activities are the process of transferring blood from donors to people who lack blood and the process is carried out by parties authorized to carry out blood processing processes such as the Blood Transfusion Unit (UTD) under the auspices of the Indonesian Red Cross (PMI). However, PMI's blood stock is sometimes not enough to meet existing blood needs, so patients who need blood must look for donors who have the appropriate blood type. Therefore, a Web and Mobile-based blood donation application with Rest Api was created so that patients can get donors quickly
PERBANDINGAN DISTANCE SPACE PADA K-NEAREST NEIGHBORS DALAM KLASIFIKASI CITRA BIJI KOPI TIMOR BERDASARKAN EKSTRAKSI FITUR GRAY LEVEL CO-OCCURRENCE MATRIX Budiman Baso; Risald Risald
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.727

Abstract

Each type of robusta and arabica coffee grown in different places will have significant differences in shape and taste because the coffee itself has a rich taste. Each type also has a different price depending on the grade and taste produced. So far, knowing the types of Robusta and Arabica coffee from Timor is only based on sight and knowledge, so it does not rule out the possibility of errors due to differences of opinion for each assessment, because of this a classification system for Timor coffee beans was developed. using digital image processing techniques. In classifying coffee images, an algorithm is needed that can work properly according to the characteristics of the data to be processed. The feature extraction process is carried out using the Gray Level Co Occurrence Matrix (GLCM) method, which is a texture-based feature extraction method that aims to obtain information from an image to be classified. The classification process is carried out by comparing the Distance Space in the K-Nearest Neighbors (K-NN) method. The data used in this study were 200 datasets which were divided into 150 training data and 50 test data, with the distribution of datasets using the Holdout method. The performance of K-Nearest Neighbors with the GLCM feature which gives the best results is the Euclidean Distance space with 1 Neighbors with an accuracy result of 88%.

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