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Double exponential smoothing brown method towards sales forecasting system with a linear and non-stationary data trend

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Journal of Physics: Conference Series 2021年第1期1810卷

作者： P A S Dharmawan I G A A D Indradewi Study Program of Informatics Engineering STMIK STIKOM Indonesia Denpasar-Bali 80225 Indonesia

UD Parama Store is a trading company engaged in selling retail goods that sell various types of daily necessities retail. The major problems occurred are the difficulty in predicting the sales due to the maturity level of experience, customer demand changes, and the owner's limited memory. Therefore, there should be an increase of merchandise stock to prevent any sudden decrease in sales and overcome the stock shortage when there is an increase in sales. In this current research, a sales forecasting web-based system was designed and built to assist the owner in predicting the number of sales in the next period. As a result, decisions can be made in determining the number of goods to be provided. The forecasting method used was double exponential smoothing brown by improving forecasting, averaging (smoothing) the past value of a time coherent data, and decreasing (exponential), which requires one parameter only. It was used to increase and decrease the linear and non-stationary data. The calculation of forecasting accuracy using the MAPE (Mean Absolute Percentage Error) method in forecasting sales of merchandise produces the smallest error rate ranging from 7.99% to 32.42% for 10 different items.

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LoRaWAN Intelligent Outdoor Smart Street Lighting

LoRaWAN Intelligent Outdoor Smart Street Lighting

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Pandapotan Siagian Erick Fernando Faculty of Informatics and Electrical Engineering Computer Engineering Study Program Del Institute of Technology North Sumatera Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9780738125176

ISBN: (纸本)9781665418614

Nowadays, The roads have increased the number of streetlights for the roads vehicles/pedestrians, which raises investment and energy. Observations made to obtain most of the road lights are always active at night, even when there are no vehicles or pedestrians on the road. The problems that occur are the waste of energy sources that are used in streetlights. This research designs the concept of intelligent traffic flow based (LED) for energy optimization, maximum efficiency. This concept uses intelligent light architecture using the LoRaWAN Mesh network. The application of this concept offers system reliability, reduces costs, and makes user satisfaction. The results of this study are demonstrated by experimenting with comparing conventional LED lights. The proposed system, resulting in 33% to 62% energy savings depending on when the usage process in streetlights. Smart lighting LEDs with LoRaWAN provide a remote-control mechanism that can be dynamically adjusted based on environmental conditions, distance, and automatic motion.

关键词： Lighting Sensors Light emitting diodes Intelligent sensors Sensor systems Batteries Roads

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Canopy cover estimation based on support vector regression derived from Lidar & Landsat 8 OLI 40

Canopy cover estimation based on support vector regression d...

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40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019

作者： Hudjimartsu, Sahid Tampinongkol, Felliks Rudianto, Yoga Setiawan, Yudi Prasetyo, Lilik Budi Forests2020 Programme Environmental Analysis and Spatial Modelling Laboratory Department of Forest Resource Conservation Faculty of Forestry Bogor Agricultural University Bogor West Java Indonesia Geoinformatic of Informatics Engineering Study Program Faculty of Engineering and Science Ibn Khaldun University Jalan KH Soleh Iskandar KM 2 Tanah Sereal Bogor West Jawa Indonesia

Light detection and ranging (LiDAR) provides geospatial information with massive amounts of data to use in a variety of applications. Canopy cover percentage of tree crown is one application that is estimated through LiDAR data. This study aims to estimate a canopy cover derived from LiDAR used as reference data with multispectral Landsat 8 OLI. Statistical or machine learning approaches can be used to estimate a canopy cover. In statistical inference, the form of distribution chosen by the analyst and parameter is estimated from the data. This will be a problem in the construction function for the National scale, due to many ecosystems and then will have many functions for each ecosystem. Machine learning (ML) methods, in contrast, are various kinds of algorithms that are used to learn the mapping function or classification rules inductively, directly from the training data. ML can solve problems related to big data and global method and it will be used as a methodical approach to estimate canopy cover on the National scale. In this study, we use a support vector regression (SVR) as ML method to estimate the canopy cover. The estimated percentage of canopy cover will be used as one of the parameters to classify a forest. © 2020 40th Asian Conference on Remote Sensing, ACRS 2019: "Progress of Remote Sensing Technology for Smart Future". All rights reserved.

关键词： Ecosystems

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Design of Hexapod Robot Movement Based on Arduino Mega 2560 1

Design of Hexapod Robot Movement Based on Arduino Mega 2560

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1st International Conference on Vocational Education and Technology, ICONVET 2018

作者： Ariawan, K.U. Santyadiputra, G.S. Sutaya, I.W. Electronics Engineering Study Program Technical and Vocational Faculty Universitas Pendidikan Ganesha Indonesia Informatics Engineering Education Departement Technical and Vocational Faculty Universitas Pendidikan Ganesha Indonesia

This study aims to design the movement of the hexapod robot so that it can move straight forward, turn 90 degrees forward, and move forward 180 degrees by applying the tripod gait method to produce a maximum movement pattern. The robot control system uses Arduino Mega 2560 to control the motion of 18 servo motors through the I2C interface servo motor driver - PCA9685. In straight forward motion testing, an average velocity of 6 cm/s was obtained, 90 degree forward motion testing obtained an average speed of 18 degrees/s, while the 180 degree rotational forward motion test also obtained an average speed of 18 degrees/s. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Machine design

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Modified genetic algorithm for employee work shifts scheduling optimization

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Journal of Physics: Conference Series 2021年第1期1810卷

作者： N W S Saraswati I D M D Artakusuma I G A A D Indradewi Study Program of Informatics Engineering STMIK STIKOM Indonesia Denpasar-Bali 80225 Indonesia

Arranging an employee shift work's schedule requires high accuracy. It is because we have to pay attention to several constraints simultaneously. The genetic algorithm presents as a method which can automatize the process of arranging the schedule as well as optimizing the result of the schedule. The Shala Bali is a hospitality business whose scheduling was complicated because of the number of the employes. This research aimed at producing a shift work schedule of the employees in a week and to know the optimum genetic algorithm parameter in this case. The constraints that were taken into account in the arrangement of the schedule included the schedule conflict of the employees in one shift, schedule conflict of employees in 1 day, the same composition of employees per shift, employees should not get morning shifts after being in night shift the night before, each shift has at least 1 employee in the front office, and each employee is required to get 1 day off within 1 schedule period. This study was able to produce an optimal work schedule of employees with crossover probability (Pc) of 0.6, and mutation probability (Pm) of 0.3. The modification algorithm in chromosome generation and chromosome structure in this study results that changes in gene length (additional number of employees) do not have to be followed by an increase in the number of chromosome populations to get optimum results.

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The design of micro-perforated panel (MPP) on noise case of APU GTCP 331-350 airbus A330 aircraft

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AIP Conference Proceedings 2023年第1期2601卷

作者： Lazuardy Rahendra Pinandhita Thomas Ken Darmastono Study Program of Aerospace Engineering Faculty of Aerospace Technology Adisutjipto Institute of Aerospace Technology Jalan Majapahit Blok-R Lanud Adisutjipto Bantul D.I. Yogyakarta 55198 Indonesia Study Program of Informatics Faculty of Industrial Technology Adisutjipto Institute of Aerospace Technology Jalan Majapahit Blok-R Lanud Adisutjipto Bantul D.I. Yogyakarta 55198 Indonesia

In general, noise is a problem and it can be found everywhere, including at the aero activity such as aircraft maintenance vicinity. The object of the noise case selected in this study is the Auxiliary Power Unit (APU) which is the part of Airbus A330 aircraft with the APU type GTCP 331-350. The noise of APU while operate during maintenance can affect the occupational health and safety conditions of the worker. In this study, a micro-perforated panel (MPP) is used to absorb or reduce the sound intensity. MPP is made of a thin flat material where in this research using acrylic and placing small holes on its surface. Both experimental and numerical method are used in this research. The first step in performing the MPP design is numerically to obtain the geometry according to the absorption coefficient target at the specified noise frequency. For the experimental or testing phase of finished MPP design, a tool called an impedance tube is used. The test procedure refers to the ISO 10534-2 or ASTM E 1050-90 document. There are two types of impedance tube, first in diameter of 10 mm and the second one in 3 cm. The 10 mm impedance tube has the frequency range from low to medium frequency while the 3 mm for the high frequency testing. The absorption coefficient prediction value from numerically MPP design for the targeted frequency of 695 Hz gets 0.8819 versus the actual value after test in impedance tube is 0.8875. Furthermore, the highest absorption coefficient value for design or prediction and actual testing lies at the exact frequency of 750 Hz where for predictions has 0.95 and 1 for actual testing. Based on these results it can be concluded that MPP has the potency to reduce the APU noise. Henceforth it will be interesting to apply the MPP technology directly to the APU compartment on aircraft.

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Improvisation of Minimax Algorithm with Multi Criteria Decision Maker (MCDM) in the Intelligent Agent of Card Battle Game

Improvisation of Minimax Algorithm with Multi Criteria Decis...

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International Conference on Electrical engineering and Computer Science (ICECOS)

作者： Silvester Dian Handy Permana Ketut Bayu Yogha Bintoro Budi Arifitama Ade Syahputra Maya Cendana Informatics Engineering Study Program Universitas Trilogi Jakarta Indonesia

Choosing the right algorithm for Intelligent Agent is very important in determining the next step. Actions taken by an Intelligent Agent with less optimum algorithm can be figured out easily by the player competing with it. This certainly makes it easier for the player to win the game. Card Battle is a game that compares the strength of both card decks. They competed to determine who has the best cards on deck to reduce the enemy health point. Intelligent Agent need to act as the competing enemy called Non-Player Character (NPC). Presently, Intelligent Agent on Card Battle Games still use the Minimax Algorithm. This algorithm thinks only to counter enemy summoned card without considering other things such as enemy health point left, the cost for summoning a card, etc. Improvisation of Minimax Algorithm with Multi Criteria Decision Maker (MCDM) provides a new way of thinking for the decision making during the game. The results of this study increase the difficulty of the NPC by making it possible for the Intelligent Agent to consider more game properties and counter the player cards.

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Logistic Regression Model of Relationship between Breast Cancer Pathology Diagnosis with Metastasis

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Journal of Physics: Conference Series 2021年第1期1752卷

作者： M N Bustan B Poerwanto Statistics Study Program Universitas Negeri Makassar Makassar Department of Informatics Engineering Universitas Cokroaminoto Palopo

Management of breast cancer requires a diagnosis of breast cancer, including an accurate pathology diagnosis to direct the provision of appropriate treatment. Part of inseparable diagnosis of breast cancer itself is determining the presence of metastasis. This study aims to determine the relationship model of pathological diagnosis with the possibility of metastasis to other organs of the breast. Pathology diagnosis results include tumor position, topography, behavior, grade, and tumor status. This study used secondary data from the Hospital Information System (SIRS) of the hospital in Makassar, Indonesia. Data obtained from the results of pathology and clinical examinations of breast tumor as many as 204 patients were hospitalized during the year of 2018. Binary regression analysis modeling was performed to see the relationship between types of pathological diagnosis (laterality, topography, behavior, grade, tumor status) of breast cancer with the possibility of metastases to other organs. The results of the analysis found a significant relationship between the position and status of the tumor with the presence of metastasis. The results of the metastatic binary logistic regression model was L(Y) = 1.330 – 0.670lat1 – 0.779lat2 – 0.724status Chi-square analysis between metastasis with surgery and chemotherapy found the significant relationships between metastasis with surgery (X2 = 15.951; p value = 0.001) and metastasis with chemotherapy (X2 = 20,796; p value = 0.001). The results of this analysis indicate that the position and status of the tumor have a relationship with the likelihood of metastasis. In addition, this metastasis further determines the management of treatment whether surgery or chemotherapy or both.

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An indoor video-based for single face identification among people 3

An indoor video-based for single face identification among p...

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3rd International Conference on Science, ICOS 2019

作者： Indrabayu Areni, I.S. Arafah, M. Jusman Rachmat, M.P. Nurtanio, I. Informatics Department Hasanuddin University Makassar Indonesia Electrical Engineering Department Hasanuddin University Makassar Indonesia Informatics Study Program STMIK AKBA Makassar Indonesia Communication and Information Department Makassar City Official Makassar Indonesia

The purpose of this research is to build a system that can detect certain face among several people. The system works using face recognition in searching suspects from a database. 30 images and 9 videos are used for training and testing. In the training process carried out several stages: (1) pre-processing of face images, (2) extraction of facial image training features using the Histogram of Oriented Gradient (HOG) method, (3) face classification using the SVM method. There are several steps for testing process i.e.: (1) video frame extraction, (2) cascade classifier method with the Local Binary Pattern (LBP) feature descriptor, (3) HOG for extracting facial features detected in the frames, and (4) SVM as the face classifier. The processed video data is 1920x1080 pixel resolution which has been recorded using a CCTV camera which is mounted on a wall with height and slope angle of 2.5 meters and 60 degrees. There are two goals implemented in this research. The first goal is to find the highest accuracy from several testing of frame sampling by setting the best threshold value. The second goal is to find the lowest processing time. © Published under licence by IOP Publishing Ltd.

关键词： Local binary pattern

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Review the Utilization of Big Data and K-Means Algorithm in Supporting The Determination of Village Status As Support To The Ministry of Village PDTT

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Journal of Physics: Conference Series 2021年第1期1811卷

作者： Paska Marto Hasugian Harvei Desmon Hutahaean Bosker Sinaga Sriadhi Saronom Silaban Informatics Engineering Study Program STMIK Pelita Nusantara Medan Indonesia Computer Science and Informatics Education Study Program Faculty of Engineering Universitas Negeri Medan Medan 20221 Indonesia Departement of chemistry Universitas Negeri Medan Medan 20221 Indonesia

Big data refers to big data, fast data processing, diversity of data structures, and data values so that it is not possible to be processed with outdated methods. Big data technology is used in various industrial sectors. Big data technology is the whole technology that can handle Big Data. Some of the uses of big data are based on the largest significant data traffic sources such as social media, financial transactions, public data, sensor data, and corporate data. The same is the case with the status of so many villages in Indonesia, so it is better to use big data for the classification of village status based on the village index build by involving an algorithm process. This research aims to produce a description of the role of big data in supporting activities in a grouping. The method used is a qualitative approach related to data collection based on scientific work with the source of data information needed to study literature techniques from various studies that have been published in national and international journals. A decision is made that big data has been widely used in different circles to facilitate performance and speed up the decision-making process.

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