bluuebunny/crossref_metadata_2025 huggingface dataset:
THE STUDY OF TREE LEVEL IN ANGGOMATE WATERSHED AREA , SOUTHEAST SULAWESI
Authors: Ikbal Ikbal , Khaery Aqmal , Fachruddin Fachruddin
Published: February 2023

Anggomate River has ecological and economic value for the local community. Massive community activities in utilizing land in the Anggomate watershed area for plantation, inhabitation, and sand mining lands can cause the tree vegetation decline, even flood often occurs in Andowia region annually. The research method used was a quantitative method. Sampling was performed through a plot-transect method. The plots were placed on the downstream (Labungga Village river area), middle (Laronaga Village river area), and upstream (Andowia Village river area) regions. The study results showed that there are 35 tree species with the individual number of 64. The highest importance value index was obtained from Ficus benjamina L. at 29.38%, Anthocephalus cadamba (Roxb.) Miq) at 25.64%, andÂ  Lansium domesticum Corr. at 16.81%. The dominance index of the tree species in the Anggomate river area was 0.971, which indicates that one of the tree species dominated this area, namely, Anthocephalus cadamba (Roxb.) Miq) (Roxb.) Miq). The diversity index in the Anggomate watershed area includes in high category (Hâ€™= 3.402 atau Hâ€™ > 3). The distribution index includes in the evenly distribution category due to obtaining closely approaching the value of 1 (E= 0.818).
INCREASED RESISTANCE OF PENAEUS MONODON TO WHISPOVIRUS CAUSES WHITE SPOT SYNDROME THROUGH ANTIVIRUS GENE TRANSFER
Authors: Christanti Chelvieana A. , Widyanti Debora V. , Rhenata Yesica C. , Icasari Floreta D. , Gultom David L , Siburian Sudarsono , Irawati Wahyu
Published: February 2023

The shrimp species Penaeus monodon is the main commodity of Indonesian aquaculture. One of the obstacles when cultivating tiger prawns is the attack of white spot disease (White Spot Syndrome Virus) which makes the quality and quantity of production decrease. One attempteffective for overcoming the white spot virus attack on shrimp, namely through the transfer of antiviral genes. Previous researchers carried out the transfer of antiviral genes to provide immunological effects so that they were resistant to pathogen attack and could prevent the death of tiger prawns. Destinationwriting article that is This study aims to determine the increase in resistance of tiger shrimp to Whispovirus that causes White Spot Syndrome through the transfer of antiviral genes. The type of research conducted is descriptive qualitative with a literature review method that discusses five focus studies, namely Whispovirus as a cause of White Spot Syndrome Virus (WSSV) disease in tiger prawns, tiger shrimp infected with White Spot Syndrome Virus, the use of PmAV antiviral genes in the treatment of Whispovirus , the mechanism of transfection of antiviral genes in the treatment of Whispovirus infection against tiger prawns, and changes in tiger shrimp resistance after insertion of antiviral genes. The conclusion obtained is that the addition of antiviral genes in tiger shrimp DNA can increase its resistance to Whispovirus.
PROFILE OF PULMONARY AND EXTRA PULMONARY TUBERCULOSIS USE GENEXPER AT THE PIRNGADI HOSPITAL MEDAN
Authors: Daposang Eva Sartika , Hasanah Fenny , Silaban Dewi
Published: February 2023

Mycobacterium tuberculosis as the bacteria that causes TB disease where the healing process takes a long time, using boredom and drug blockages in TB sufferers. This is one reason germs become resistant to several types of anti-tuberculosis drugs known as TB Multi Drug Resistance (MDR TB). The molecular rapid test (TCM) method using GenExper can quickly determine ATD resistance. This study aims to see the results of TCM examination using GenExper in patients with pulmonary tuberculosis and extra pulmonary tuberculosis at dr. Pirngadi Medan. This study used a cross-sectional method by taking laboratory data from the GenExper examination contained in the medical records of patients diagnosed with tuberculosis at Pirngadi Hospital, Medan. Samples obtained from patients using GenExper from January to December 2018 obtained 354 patients with 68.1% more TB incidence in male patients (241/354) than women by 31.9% (113/354). The patients most affected by TB were elderly people aged 56-65 years with a proportion of 23.7%. The largest population affected by TB is self-employed 30.5% and the highest level of education diagnosed is high school graduates 60.5%. Most patients suffered from pulmonary TB at 86.4%.
DISTRIBUTION PATTERN OF THE EXOTIC PLANT (SYNEDRELLA NODIFLORA (L) GAERTN) IN THE REHABILITATION ZONE, RESORT OF WONOASRI, MERU BETIRI NATIONAL PARK
Authors: April Liana Yennita Dwi , Sulistiyowati Hari , Mohammad Siddiq Arif
Published: February 2023

Exotic plants are plants that are intentionally or unintentionally included in an area. Based on the results of the 2020 survey, one of the exotic plants found in the Donglo Block Rehabilitation Zone area of Meru Betiri National Park (MBNP) is cinderella weed (Synedrella nodiflora). The objective of this study is to determine the distribution pattern and area of cover of exotic S. nodiflora plants in the research location. Data were collected using a combination method of systematic plot transects measuring 2 x 2 meters which were placed along the transect with a total of 415 plots. The data recorded were the coordinate position of each individual S. nodiflora and the area of the cover. Analysis of distribution pattern data using the Morisita index and visualized with a spatial distribution map using Geographic Information System (GIS). Coverage area analysis was carried out by calculating the percent cover of S. nodiflora. The results of the analysis of the Morisita index showed the value of IÎ´ = 7.13, which indicates that the distribution pattern of the plants is clustered. In addition, the presence of this species in the study area was occupied 41.7% or 0.85 ha of the total area of 2.04 ha. It shows that this species still did not dominate the area, so it can be said that this species has not yet become an invasive species category in the research location.
ANALYSIS OF DNA SEQUENCE ENCODING GLYCERALDEHYDE-3-PHOSPHATE DEHYDROGENASE (GAPDH) ON COCOR BEBEK (KALANCHOE x LAETIVIRENS)
Authors: Agustina Putri , Roslim Dewi Indriyani
Published: February 2023

To understand the fundamental mechanisms on genes in plant cells can be performed by gene expression studies. The study needs reference genes that act as internal control to avoid expression data bias. Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH) gene is one of reference genes that has been validated in plants. This study aims to analyze the DNA sequences encoding GAPDH in cocor bebek (Kalanchoe x laetivirens). Methods included total DNA extraction from fresh leaf, polymerase chain reaction (PCR), electrophoresis at 1% agarose and DNA sequence data analysis. The DNA sequence of K. x laetivirens GAPDH gene obtained were 1107 bp and predicted to consist of 5 exons and 5 introns. This sequence had about 68.96%-73.81% similarity to the DNA sequence of the GAPDH gene in several plant species. The amino acid sequence of K. x laetivirens GAPDH had 5 conserved regions and residues of cysteine (C) and histidine. The sequence obtained in this study was the first to be reported from the genus Kalanchoe. This sequence can be used for analysis of gene expression in K. x laetivirens and can be as reference for isolating the GAPDH gene for other plant species in the genus Kalanchoe.
DEGRADATION OF SOME POLYSTRENE USING BEETLE LARVAE (TENEBRIO MOLITOR L.)
Authors: Indra Putra Ichsan Luqmana , Nurcahyasari Alfi
Published: February 2023

One alternative to waste processing polystyrene is to use Tenebrio molitor larvae. This study aims to determine the increase in body length and weight, rate of degradation, and value of Waste Reduction Index (WRI) of larvae T. molitor. This study used laboratory experimental using completely randomized design experimental design model (CRD) data analysis with control and 4 feed treatments. Each treatment level was repeated 5 times in order to obtain 25 experimental units. Larvae were reared in a plastic container containing 10 larvae. Each larvae were given bran feed for control and polystrene for treatment, each feed as much as 1 gram. The polystyrene used were food packaging, walls, electronic packaging, and ice boxes. Larvae were measured for length and body weight every 3 days for 30 days. Parameters observed were increase in length and weight of larvae, rate of degradation and WRI values.The highest mean value of increase in larval length on the polystrene wall was 1.69 cm. The lowest value was polystyrene food packaging (1.59 cm). The average weight gain of larvae has a uniform value in the control and treatment of 0.07 gr. The highest degradation rate and WRI values were polystyrene wall and electronic packaging at 0.019 and 0.63%. while the lowest values were polystyrene food packaging at 0.11 and 0.37%.
EVALUATION ON METHODS FOR IDENTIFICATION OF VIBRIO SP.: KAWAKAWA (EUTHYNNUS AFFINIS) BRINING SHREDDED AND CHITOSAN ADDITION AS PRESERVATIVE
Authors: Kusumaningsih Purwaningtyas
Published: February 2023

The kawakawa (Euthynnus affinis) brine salting that used to make shredded were preservative with salt. Salt addition has aim to inactivate of bacterial contamination. Obviously, bacteria is still capable of growing in kawakawa brine shredding Therefore, in this study chitosan was added as antibacterial in shredded processing. Vibrio sp., is one of common halophilic bacteria found in seafood. If this bacteria is consumed, it can cause serious problems in human health. The objective of this study was to evaluate the factors that affect in identifying Vibrio sp., on kawakawa brine shredding (C), shredded non-chitosan (FC) and shredded contain of chitosan (FC+). The methods evaluated were steps in enriching bacteria, culturing bacterial in selective media and analysing bacterial by API 20E kit. Enriching and incubation periods were needed by halophilic bacteria to adaptation in new environment. It was required to observe the bacteria characteristics' that would be isolated. Bacterial colonies were growth on Thiosulphate citrate bile salt sucrose (TCBS)Â  were not Vibrio sp., but confirmed as Pseudomonas luteola and Proteus vulgaris based on API 20E analysis. It was showed that TCBS media had some advantages in identifying Vibrio sp. In conclusion, to get the best result in identifying bacteria, at least twoÂ  or more methods were used to avoid misidentification.
Motion Monitoring System Based on IoT
Authors: Susilawati Susilawati , Sembiring Zulfikar , Muhathir Muhathir
Published: February 2023

Every object is always moving, and movement of an object can occur at any time. The value of the motion which produced from an object can be very small to very large, and the impact of the movement can be at risk until very risky. For this reason, the movement of objects at risk must be observed whenever changes and observations for data retrieval can be done remotely. The purpose of this research to design an Internet of Things (IoT) devices that can observe and detect changes in the motion of an object. Â The device is designed to be small, around 44 x 48 millimeters with very low power consumption. The design phase begins with recording motion data using the MPU6050 accelerometer sensor as a motion detector, arduino nano as a control device, WiFi ESP8266 as a communication medium for sending data from a receiver apllication motion data with UDP protocol. The test results show that this device is very sensitive to detect changes in the motion and angle of X, Y and Z of an object.
Detection of Banana and Its Ripeness Using Residual Neural Network
Authors: Dhaniswara Erwin , Kristian Yosi , Setiawan Esther Irawati
Published: February 2023

Automatic fruit detection utilizing computer vision techniques has been carried out to help the agriculture and plantation industries. This study researches smart systems to detect bananas and ripeness classification utilizing residual neural networks. The method used to detect bananas is transfer learning from pretraned Model VGG-19. Whereas, in the bananas ripeness classification process, residual neural networks, which are trained from the start, are used. Sliding Windows is used to detect the position of bananas followed by Non-Max Suppression to summarize the results of several detected bananas. Previous studies were limited to the level of ripeness, but in this study, bananas are detected and followed by the level of bananas ripeness (raw, ripe, and overripe). This studyâ€™s data uses bananas which were mixed with other kinds of fruit. There two kinds of bananas detection architecture used in this study, VGG-19 and Restnet. After they were used to detect bananas, it was found that VGG-19 was more suitable. The results of this study are very satisfying as it is seen from the bananas detection testing percentage using VGG-19 architecture which shows 100% ripe bananas, 99 % raw bananas, and 100% overripe bananas.Keywords:Â Detection of banana, banana ripeness, Non-Max suppression, residual block.
Design Of Triangular Array Microstrip Patch For Antenna 5g Application
Authors: Simanjuntak Imelda Uli Vistalina , Rochendi Agus Dendi , Salamah Ketty Siti , Safitri Diah Sucita
Published: February 2023

The trend of research on microstrip antennas in the millimeter frequency range has been hotly discussed in recent years. With the aim of increasing the bandwidth, beam gain and return loss in accordance with the standards of 5G needs in a fairly small dimension and low complexity. Previously, several studies of microstrip antennas with conventional patches have been carried out, then followed by a triangular array patch model. The antenna designed using Duroid 5880 substrate with a thickness of 1.575 mm and a dielectric constant value of 2.2 was simulated using Computer Simulation Technology (CST) software. The simulation results work at a frequency of 28 GHz with a return loss value of -26.98 dB, VSWR 1.09, gain 8.8 dB, HPBW value of 25.6Â° and main lobe of 21.0 dBi. This antenna can work well on millimeter wave range for 5G technology. Compared with previous studies of microstrip antennas, this triangular array patch antenna provides better measurement results.
Internet Data Quota Assistance for Students Using Reference Point MOORA Decision Analysis
Authors: Hairah Ummul , Budiman Edy
Published: February 2023

Decisions are made by those who are authorized and responsible decision makings for an institution or organization. Many decisions involve stakeholders who are individuals and organizations who can be affected by the future consequences of these decisions, including decision-making on Internet data quota assistance distributed by the Ministry of Education and Culture to support students' online learning from home (LFH). This Assistance Policy is very appropriate and well provided during the Covid-19 Pandemic. However, in an effort to optimize and objectify distribution so that it is right on target, this research is proposed solutions for applying the analysis decision-making mode using Multi-criteria Decision-making (MCDM). The criteria used include the amount of internet data consumption, Academic credits, courses, and student's economic capacity. The criteria weighting method uses Rank-order Centroid (ROC) and reference point MOORA for determining the best alternative. Â The results showed that the implementation of the MCDM ROC-Reference MOORA method affected the preference value and alternative ranking of internet data quota assistance. This shows that the criteria weight value and the analysis method are critical aspects in decision-making. Differences in weight, even the slightest change in weight, can drastically change the final decision
Machine Learning Dengan Decision Tree untuk Prediksi Pembayaran Invoice, Case Study : Gramedia Jakarta
Authors: Firmansyah Firmansyah , Yulianto Agus
Published: February 2023

Arus keuangan yang lancar merupakan salah satu kunci agar perusahaan tetap bertahan dan memiliki keberlangsungan. Pembayaran atas faktur penjualan adalah salah satu masalah yang dapat mempengaruhi keuangan, jika pembayaran faktur terlambat maka perputaran kas menjadi lambat dan berdampak pada operasional perusahaan. Belum adanya alat yang dapat memprediksi pembayaran faktur di Gramedia menyulitkan bagian keuangan. Dari permasalahan itu, maka diterapkan machine learning untuk memprediksi pembayaran faktur oleh customer, apakah pembayarannya terlambat atau tidak terlambat. Proses dalam data mining menggunakan framework CRISP-DM (Cross Standard Industry for Data Mining). Fitur data yang digunakan sebagai parameter yaitu invoice amount, payment method, paid invoice, average days late dan ratio amount of overdue by amount of balance. Data faktur penjualan diprediksi menggunakan model decision tree algoritma C5.0 dengan hasil akurasi mencapai 71.84%.Â  Algoritma C5.0 terbukti mampu memprediksi faktur yang pembayarannya terlambat (melewati jatuh tempo) dan pembayarannya tepat waktu (sebelum jatuh tempo).
Expert System For Diagnose Covid19 Using Certainty Factor Method
Authors: Nulhakim Lukman , Andriansyah Doni
Published: February 2023

AbstractAt the end of 2019 the world was shocked by the emergence of a new type of virus from the Corona family, namely the Novel Coronavirus (2019-nCoV) which had never been previously identified in humans, later known as Coronavirus disease 2019 (Covid-19). Early symptoms in people with Covid-19 include fever, cough and shortness of breath, similar to flu and cough symptoms in general, making it difficult to detect early. The certainty factor method can measure a certainty and uncertain thing. Research with certainty factor methods has been carried out to diagnose a disease based on the symptoms experienced. Types of diseases are focused only on types of diseases with almost the same symptoms, namely Upper Respiratory Tract Infection, Pneumonia, and Covid-19. The purpose of this study is to build an expert system application that can be accessed online to detect early symptoms experienced by sufferers. Based on the results and discussion, the expert system application can run well and the results of manual CF calculations are the same as the results of CF calculations on the system.
Design of 2x1 MIMO Microstrip Antenna Using Slit and Inset Technique For 5G Communication
Authors: Solehudin Fahrul , Sanaz Zikra Aulia , Alam Syah , Sari Lydia , Surjati Indra
Published: February 2023

The fifth generation (5G) technology offers high speed communication systems and requires a multi input and multi output (Multiple Input Multiple Output / MIMO) antenna system to increase customer capacity. This research proposes a microstrip antenna design for a fifth-generation (5G) communication system that works at a frequency of 3.5 GHz. The antenna was designed using the RT-Duroid R5880 substrate type with dielectric constant (Îµr) = 2.2, thickness (h) = 1.57 mm and loss tan (tan Î±) = 0.0009. To produce optimal parameter, the antenna is optimized using slit on the edge with a total of 2 pairs. The addition of an inset aims to reduce the reflection coefficientÂ  of the proposed antenna. From the simulation results, the reflection coefficient value is -25 dB at a frequency of 3.5 GHz with a bandwidth of 220 MHz. The gain of the proposed antenna is 10 dB at a frequency of 3.5 GHz. The isolation coefficient obtained is -70 dB with a distance between (d) = 43 mm. The application of the MIMO antenna increases the gain by 49.52% compared to the single element microstrip antenna.
E-Commerce Customer Segmentation Using K-Means Algorithm and Length, Recency, Frequency, Monetary Model
Authors: Siagian Romadansyah , Pahala Sirait Pahala Sirait , Halima Arwin
Published: February 2023

The growth of the e-commerce business sector presents competitors and creates company competition. Customers are the company's main asset that must be maintained. Understanding the different characteristics, behaviors and habits of each customer segment is important for companies to identify potential customers, establish important strategies, manage customer relationships and increase company profitability. The needs and desires of each customer are different, so that determining a strategy requires a method of segmenting customers according to their respective similarities. Using the clustering method with the K-Means algorithm helps determine customer segmentation based on transaction history data. Determination of the optimal k cluster randomized K-Means doesn't always give good result, so the Elbow, Silhouette and Davies-Bouldin Index methods are used. The determination of the test variables is based on the LRFM model (Length, Recency, Frequency, and Monetary), so that the customer segmentation obtained is more accurate in recognizing customer behavior and loyalty. The results of test 3606 dataset through the preprocessing stage using these methods results in three groups of customers that is New Customers, Lost Customers and Core Customers adjust the Customer Loyalty Matrix LRFM
News Opinion Classification Application With Support Vector Machine Algorithm Using Framework Codeigniter
Authors: Tjut Adek Rizal , Fikry Muhammad , Khalil Umar
Published: February 2023

News is an information that contains a lot of data, one of which is data about opinion / sentiment. The opinion / sentiment data of a news can be used for many things. To get the opinion value of a news, it is necessary to do a sentiment analysis technique on the news data that wants to know the level of opinion produced. Sentiment analysis is a technique that uses the data mining method. To see the height of the opinion value of a news item, the Support Vector Machine algorithm is used, which is one of the algorithms in the data mining method that is able to classify data sets into two classes. Using the CodeIgniter framework based on the PHP programming language, an application was developed that can classify the news into two classes, namely the positive class and the negative class. By using 100 pieces of news data from the national news portal, namely detik.com, about 700 sentences and more than 1000 words are generated which are then classified using the SVM algorithm. Applications are able to achieve an accuracy rate of 76%
Applied of Information Gain Algorithm for Culinary Recommendation System in Lhokseumawe
Authors: Dinata Rozzi Kesuma , Hasdyna Novia , Alif Muhammad
Published: February 2023

Information gain is an algorithm that can be used to rank datasets. This research applied the information gain algorithm to the culinary recommendation system in Lhokseumawe city.Â  Lhokseumawe is one of the tourist destinations in the northen region ofÂ  Aceh, due to its strategic location near the beach.Â  Apart from the beach, culinary is the main choice of tourists when visiting Lhokseumawe city.Â  The purpose of implementing this recommendation system is to make it easier for tourists to find the best culinary recommendations in Lhokseumawe city based on the value of the data ranking with the information gain algorithm.Â  The results of this research shown that the highest rank of information gain values is 0.545715, 0.530769, and 0.497328, continuously.Â  This value provided in the culinary recommendation system in Lhokseumawe city, namely Mie Ayah, Bakso Pim, and Bakso Pak De.
Comparison of Neural Network Algorithms, Naive Bayes and Logistic Regression to predict diabetes
Authors: Utami Dwi Yuni , Nurlelah Elah , Hasan Fuad Nur
Published: February 2023

Diabetes is a disease that affects many people with the characteristics of high blood sugar levels. The International Diabetic Federation (IDF) estimates the number of Indonesians aged 20 years and over, suffering from diabetes at 5.6 million people in 2001, and increasing to 8.2 million people in 2020. The problem that occurs is that many people do not know that they suffer from diabetes because they do not have basic knowledge about diabetes and the existing methods to detect diabetes are time consuming. In this study, three data mining methods were compared, namely the neural network algorithm, naÃ¯ve Bayes, and logistic regression using the rapid miner application by applying the Confusion Matrix Evaluation (Accuracy) and the ROC Curve. The result of this research is that logistic regression method is a fairly good method in predicting early diagnosis of diabetes compared to the naÃ¯ve Bayes method and the neural network. From the evaluation and validation, it is known that logistic regression has the highest accuracy and AUC values among the comparable methods, namely 75.78% and AUC 0.801, followed by the naÃ¯ve Bayes algorithm which is 74.87% and AUC 0.799, and the neural network is 69.27% and AUC 0.736. has the lowest accuracy.
Performance Analysis of STBC 4x4 MIMO using Ray Tracing Channel Modelling in WLAN Technology
Authors: Wisudawan Hasbi Nur Prasetyo , Tjondronegoro Suhartono
Published: February 2023

IEEE 802.11n technology comes with many advantages such as high data rate and reliability. In 2,4 GHz and 20 MHz bandwidth, it gives data rate up to 300 Mbps. In order to improve reliability without complexity, it uses STBC (Space Time Block Coding) using Alamouti algorithm. This algorithm can be implemented with many STBC scheme, i.e., 2x1, 2x2, 3x1, 3x2, 3x3, 4x1, 4x2, 4x3 and 4x4 using BPSK, QPSK, 16-QAM and 64-QAM modulation. Impulse respons of (Laboratorium Telekomunikasi Radio dan Gelombang Mikro) LTRGM indoor channel can be modeled by using ray tracing method. This simulation also investigates the effect of MIMO channel corelation caused by channel fading and physical antenna factor. The results, LTRGM indoor channel give delay spread and rms delay of 71.94 ns and 1.5 ns respectively. The ergodic channel capacity declines steadily as the channel correlation becomes worse. This problem also cause a decrease in SNR performance to achieve SER of 10-3 with various modulation. However, this does not have significant influence on WLAN system that uses STBC with four both transmit and receive antenna
Classification of the IDR-USD Exchange Rate with Multilayer Perceptron Based on Detection Rate
Authors: Al-Khowarizmi Al-Khowarizmi , Ramadhani Fanny , Hutagalung Fatma Sari
Published: February 2023

Artificial neural network (ANN) is a set of units in processing a model based on the habits of human neural networks. ANN has one of its duties, namely classification with the concept of supervised learning. ANN also has various methods in performing its duties such as Multilayer perceptron (MLP). Where MLP is one of the ANN methods that can classify based on data as conceptualized in data mining. Very useful classifications and trends in the field of research because of the review of data that will generate knowledge. Nominal Exchange Rate is one of the datasets tested in this study. The exchange rate of the Indonesian Rupiah (IDR) against the United States Dollar (USD) is very necessary both in terms of stock movements and other businesses. So that, it is necessary to use classification to predict future exchange rates. In this study, the MLP method was carried out by obtaining a validation test using MAPE based on the detection rate ofÂ sebesar 0.500079879%.
Temperature Control System for Heating-Holding Heater Based Arduino With Monitoring Via Webserver
Authors: Gultom Golfrid , Rahmansyah Abdul Azis , Situngkir Dejoi , Ginting Manan
Published: February 2023

Heat and hold method is a method with temperature containment techniques in accordance with desired temperature and time functions. This technique aims in adjusting the characteristics of microbial resistance to temperature and saving energy consumption. In this study, a tank with temperature control system was designed for heat and hold the temperature according to the system requirements. Control of the temperature in the heating tank can be done based on the Arduino microcontroller. Arduino reads data from the temperature sensor and activate the heater according to temperature set on the Arduino. Arduino Ethernet Shield acts as Arduino data communication with a database connected to the internet network. The results of this study are in the form of a prototype that shows an IoT-based temperature monitoring tool that can be accessed anywhere via Web-based monitoring system interface. The test was carried out in 2 stages, namely testing by determining target of heater and testing with Holding and Heating with a delay of 10 minutes and 20 minutes. The heating tank temperature control system maintain a temperature of 40oC, 50oC, 60oC for 10 minutes. The temperature holding condition at a certain time is called holding. Henceforth the system temperature is at 70oC.
Implementation Of Data Mining On Sales At Resto D'sdl Lembang Using Aprioric Algorithm Method
Authors: Carolina Irmawati , Janti Suhar , Supriyatna Adi , Putri Intan Sarwono
Published: February 2023

This research was conducted to help determine the menu or package that is often purchased simultaneously. The priori algorithm is used to produce data mining regarding the determination of association rules which is carried out by calculating support and confidence in the sales of food menu mechanisms in a restaurant with a case study of the restaurant d'DSL Lembang. The resulting a priori algorithm will be implemented and tested with the Tanagra application. From the results of the discussion and data analysis carried out, it was found that with the application of the a priori algorithm in determining the combination between itemset with a minimum support of 60% and a minimum confidence of 90%, it was found in the initial calculation of the combination of one itemset, a combination of 2 itemset, a combination of 3 itemset and a final association rule with The highest value of support and confidence is if the consumer orders the Hot Sweet Tea menu, Chicken Driver Package and Liwet Rice at the same time with a support value of 58% and a confidence value of 100%.
Comparison of C4.5 and NaÃ¯ve Bayes Algorithms for Assessment of Public Complaints Services
Authors: Martin Martin , Nilawati Lala
Published: February 2023

Public service is one type of service provided by the government. The National Commission on Human Rights as a state institution, one of its functions is to provide services for complaints of cases of human rights violations. The purpose of this study was to find the most appropriate algorithm method by looking at the results of the accuracy and the Area Under Curve (AUC) value. The data used is data from questionnaires regarding assessments related to complaints of cases of human rights violations by the public in 2018, totaling 1750 records. The data is processed using the C4.5 algorithm and NaÃ¯ve Bayes with the Rapid Miner tools. The results showed that the C4.5 Algorithm has a better accuracy of 99.49% compared to NaÃ¯ve Bayes of 95.66%. The AUC value produced by the C4.5 algorithm is better at 0.998 and NaÃ¯ve Bayes by 0.996. In this study, the rule generated by C4.5 will be the basis for making a questionnaire assessment application in the form of visual programming, to help provide an assessment of the satisfaction of complaint services at Komnas HAM. The system is built based on web, using PHP framework, database using MySQL and editor tools using notepad ++.
Moodle Web-Based Learning Constraints toward Student Learning Interest Using C4.5 Algorithm during Covid-19 Pandemic
Authors: DHARSHINNI N. PRIYA , Sitepu Aisyah Hikmasari , Syuhada Rezza Youan , Barasa Damanik , Wijaya Andy Christanto
Published: February 2023

The Learning System during the Covid-19 pandemic shifted from offline learning to online learning which made many campuses use various E-Learning platforms. However, most campuses use Moodle Web-Based Learning because it provides many features that can support lecturers and students in the online learning process and can be accessed via a laptop or smartphone. The problem is, some students experience constraints in following this learning model that affects the ups and downs of student interest in learning, so it is necessary to find the obstacle factors that hinder students during Moodle Web-Based Learning. The C4.5 algorithm generates a decision tree that can be used to predict good results and provide accurate information. The purpose of this study was to find the relationship between the contraints experienced by students while following the Moodle Web-Based Learning model toward students' interest in learning using the C4.5 algorithm. The results showed the main contraint that affects the decrease in student learning interest is influenced by the learning features used by lecturers at a time when online learning is incomplete, network quality is not good, students consider Moodle Web-Based Learning less interesting while the increasing interest in student learning is influenced by the learning features used by lecturers at the time of online learning is very complete , good network quality, students use laptops or computers in following moodle Web-Based Learning and students find Moodle Web-Based Learning interesting.
Clustering Of Students Into A Specialization Of Expertise Using Genetic Algorithms
Authors: Sahputra Ilham -
Published: February 2023

Clustering mahasiswa kedalam keminatan keahlian merupakan salah satu upaya yang perlu dilakukan oleh pihak jurusan untuk menjamin mahasiswa memperoleh pendidikan yang sesuai dengan keahliannya. Saat ini, terdapat banyak metode clustering yang sudah dikembangkan oleh pakar. Umumnya metode clustering mampu mengelompokkan objek-objek yang memiliki tingkat kesamaan ciri yang tinggi, tetapi tidak mampu membatasi jumlah objek yang boleh masuk kedalam suatu kelompok. Kasus klasterisasi mahasiswa kedalam keminatan keahlian merupakan kasus clustering yang membatasi jumlah objek yang boleh masuk kedalam suatu kelompok. Dengan kondisi tersebut, metode clustering yang ada tidak dapat digunakan untuk kasus ini. Peneliti mencoba melihat kasus ini dari sudut pandang optimasi, yaitu bagaimana mengoptimalkan pembentukan kelompok keminatan mahasiswa dengan tingkat ketidaksesuaian bakat yang rendah. Untuk penyelesaian kasus ini, peneliti menggunakan algoritma genetika sebagai metode untuk penyelesaian masalah. Algoritma genetika dibagi kedalam beberapa jenis, yaitu: algoritma genetika dengan prinsip elitisme dan non elitisme, algoritma genetika dengan persentase mutasi 0.01, 0.03 dan 0.05. Berdasarkan penelitian yang dilakukan, diperoleh bahwa algoritma genetika mampu melakukan clustering mahasiswa kedalam keminatan keahlian yang disediakan oleh jurusan. Algoritma genetika dengan prinsip elitisme mampu menemukan solusi optimum yang lebih baik sebesar 39% dibandingkan dengan algoritma genetika non elitisme. Algoritma genetika dengan persentase mutasi 0.05 menghasilkan solusi optimum terbaik, namum memiliki konsumsi waktu yang paling besar dibandingkan dengan persentase 0.01 dan 0.03.
Minang and Indonesian Pharase-Based Statistical Machine Translation
Authors: Alam Muhammad Sandika , Suryani Arie Ardiyanti
Published: February 2023

This research focuses on making a phrase based statistical machine translation for Minang â€“ Indonesian language as well as seeing how well the machine translation results. The source of training and test data in the form of parallel corpus and monolingual corpus that taken from Minang Wikipedia language and Indonesian news website. Two test case scenario were tested in this research that based on the language model and translation model. To see how well the translation will be seen by using Bilingual Evaluation Understudy (BLEU). The result showed that the testing for the first scenario have a significant impact compare to the second scenario in terms of translation. The lack of corpus resources is a problem in building phrase-based statistical machine translation.
Data Mining Optimization Based on Particle Swarm Optimization For Diagnosis of Inflammatory Liver Disease
Authors: Amrin Amrin , Pahlevi Omar
Published: February 2023

Inflammation of the liver is a contagious disease that is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Early diagnosis of this disease is very important so that it can be quickly treated and treated. In this study the researchers will apply and compare several data mining and optimization classification methods with particle swarm optimization (pso), including the C4.5 algorithm, k-Nearest Neighbor, C4.5 with PSO, and k-Nearest Neighbor with PSO to diagnose inflammatory diseases. carefully, then compare which of the several of these methods is the most accurate. Based on the results of measuring the performance of the three models using the Cross Validation, Confusion Matrix and ROC Curve methods. Based on the research results, it is known that the C4.5 method with PSO is the best method with an accuracy of 79.51% and an under the curva (AUC) value of 0.950, then the k-Nearest Neighbor method with PSO has an accuracy of 75.59% and an AUC value of 0.909, then the C4.5 method with an accuracy rate of 70.99% and an AUC value of 0.950, then the k-Nearest Neighbor method with an accuracy rate of 67.19%, and an AUC value of 0.873. This proves that particle swarm optimization can improve the performance of the classification method used.
Integration Face Recognition and Body Temperature
Authors: Panjaitan Christin Erniati , Hagayna Dara , Prandi David , Wiranto Remancus
Published: February 2023

Commonly, absence is done manually on the prepared paper. This thing is less effective because wasting time and distract student's focus in the classroom. To solve that problem, this research is using Face Recognition. Face Recognition is a face detection technology. This technology is using Artificial Intelligence (AI) to indetify faces. Face Recognition also can reduce the way that student pretend present but in fact is not. This tecnology is better than convetional method. In application, camera is used to record and detect faces. We used Raspberry Pi 3b as a main part. Moreover, in this research, we integrate face recognition with temperature sensors and buzzer Testing in each component is on average successful and some fail. But it is in accordance with the rules of the system made.
High Precision 3D Printed Syringe Pump for Contact Angle Goniometer
Authors: Sentosa Vito , Ginting Riski Titian , Azmi Fadhillah , Despaleri Perangin-Angin Despaleri
Published: February 2023

Contact angle goniometer is a tool used to measure the contact angle of a surface which is usually coated with nanomaterial. Contact angle goniometer has an important part, that is syringe pump as a tool for dripping a number of liquids with high precision and accurate flowrate. The function of the syringe pump is to control amount and feedrate ofÂ  liquid on a milliliter to microliter scale per minute using a simple microcontroller. In this study, this syringe pump used an arduino as a controllerÂ  and a stepper motor as a syringe driver. Casing and the syringe pump mechanism were designed with AutoCAD Fusion360 software and printed using a 3D printer. This syringe pump has an accuracy value of 99.5%, a precision value of 99.7% and a deviation value 0.4 ÂµL which is based on the solution measured using Mettler Toledo 204 analytical balance. From the result, it is obtained that the syringe pump has been used for the contact angle goniometer with an experiment of water being dripped onto the ABS plastic surface with flowrate 100 ÂµL/minute and the surface contact angle was analyzed using imageJ software and the result of the contact angle was 179Â°. Therefore, based on the result of this study, it can be concluded that the syringe pump can be used as a contact angle goniometer
Distributed Denial of Service (DDoS) Analysis on Virtual Network and Real Network Traffic
Authors: Yudhana Anton , Riadi Imam , Suharti Sri
Published: February 2023

Data communication, computers and computer networks increase the needs and facilitation offered by a variety of server services that are owned by individuals and companies. Servers are the core of continuous communication on the internet and the main factor in the life, development and death of individual businesses or companies that rely on the internet. The other side is also developing rapidly targeting server attacks from starting to weaken performance to crippled, the most popular in the hacker world, namely attacks by bombarding servers with many requests from one computer or more, with one machine to thousands of machines. This study implements several DDoS attack techniques targeted at virtual servers and real servers to determine the type of protocol used and its accuracy and reliability. The research method uses the concept of Robert Maribe Branch (2009) or ADDIE which consists of Analysis, Design, Development, Implementation and Evaluation with the results of successful attacks on the HTTP header on the virtual network and on the real network 85.68%, while the TCP has an accuracy value. 87.75% and the real network produces 90.02%. In addition, the attack using the ping of death on the virtual server was successfully carried out and the real server had an accuracy value of 41.45% so that the attack on the TCP protocol was declared very effective in crippling the target PC or server.Â Â
An Analysis of Contract Employee Performance Assessment Using Machine Learning
Authors: Siahaan Mangapul
Published: February 2023

Sumber daya manusia menjadi salah satu perhatian utama bagi pengelola semua jenis bisnis baik perusahaan negara maupun perusahaan swasta. Organisasi usaha sangat tertarik dalam menyusun rencana dan eksekusi untuk mempertahankan karyawan kontrak yang berkinerja baik. Dilain pihak banyak nya perpanjangan karyawan kontrak berdasarkan hubungan kedekatan keluarga maupuan kedekatan kerabat. Untuk mendapatkan pekerja yang berkinerja baik, dibutuhkan aplikasi assesment kinerja karyawan kontrak. Dengan menggunakan pendekatan algoritma machine learning seperti Random Forest, Decision Tree, K-Nearest Neighbors, NaÃ¯ve Bayes, dan Logistic Regression. Penelitian ini mencoba mencari algoritma yang tepat untuk aplikasi assesment kinerja karyawan kontrak dengan nilai input skill, attidude, responsibility, absent dan membandingkan nilai akurasi, presisi, recall dan F1 score. Berdasarkan penelitian, model algoritma Random Forest yang terbaik digunakan dalam mengklasifikasi dan prediksi assement kinerja karyawan kontrak dengan mencapai nilai akurasi 90.62 %, presisi 72.22 %, recall 75% dan nilai F1 score 71.11 %
APPLICATION OF MACHINE LEARNING WITH THE BINARY DECISION TREE MODEL IN DETERMINING THE CLASSIFICATION OF DENTAL DISEASE
Authors: Ula Mutammimul , Anjani Fajar Tri Tri , Ulva Ananda Faridhatul , Sahputra Ilham , Pratama Angga
Published: February 2023

The dangers of health problems in dental disease are common for children and adults. Many dental problems get priority treatment based on data from Riskesdas, about 67.6% of the Indonesian population suffers from dental and oral problems. This affects other parts of the organ that are interrelated. Therefore, this study formulates how to solve the determination of dental disease, by applying the UDB model in machine learning. The purpose of this study was to determine the application of machine learning Binary Decision Tree (BDT) in the classification of classified dental diseases identified by decision trees in determining the results of dental disease predictions including groups and how to solve them. The research methodology in the first stage of data collection was carried out directly with the dental clinic at Cut Meutia Lhokseumawe Hospital. Then input the dental disease data along with the dental disease symptom data. The final stage is dividing the attribute values in viewing the value at a predetermined branch which is then in the form of a decision tree as a reference for the final prediction. The results of the assessment have each value indicating a high level of accuracy, with an accuracy of 92 percent and an inaccuracy of 8 percent of the 40 data points tested. Furthermore, the conclusion of this study can produce an appropriate classification of dental disease and is able to produce accurate results seen from a small error rate
Application of Artificial Intelligence Chi-Square Model and Classification Of KNN in Heart Disease Detection
Authors: Rosdiana Rosdiana , Novalia Vera , Saputra Ilham , Ula Mutammimul , Danil Muhammad
Published: February 2023

Cardiovascular disease is a problem in the blood vessels that do not run smoothly into the heart. This is fatal in patients with a history of heart disease. This problem often occurs in the flow of blood pumps into the heart. The problem examined in this study is how to complete the level of accuracy of each data set and the reduction of each attribute in heart disease. The purpose of this study is to analyze heart disease and classify heart disease using the chi-square and K-Nearest Neighbor algorithms. The results of the study with patient age 57, gender LK, cp 3, trestbps 200, chol 564, fbs 1, restecg 2, thalach 202, oldpeak 6.2, slope 2, ca 4, and the value of thal 3 for the target is there is disease heart 0 or 1 is detected without heart disease when the max-min data is normalized. while to measure the performance of the algorithm with the value of the confusion matrix with the actual class value of 1, prediction class 1 value 44, actual class 0 and prediction class value 6. while the actual class value 0-1, prediction class 1 value 5 and 0-0 value 36. the final stage value of the accuracy measure is 0.87912, the recall value is 0.89797 and the precision value is 0.85714. The implication of the application of the test has an optimal test, the accuracy value with data K = 303 then it can be concluded that based on the test the calculation of the KNN model obtained an accuracy of 91%
Implementasi Program Rumah Tidak Layak Huni di Kabupaten Asahan Pada Tahun 2019
Authors: Hamdy Achmad , Badaruddin & Humaizi Badaruddin & Humaizi , Humaizi Humaizi
Published: February 2023

AbstractAsahan District is one of the many districts in Indonesia that has implemented a rehabilitation program for unfit for habitation because there are still some Asahan people who are unable to meet their basic needs, namely a livable house. The purpose of this study is to determine the implementation, obstacles and responses of the community to the uninhabitable house rehabilitation program in Asahan Regency in 2019. The theories used in this study consist of phenomenological development paradigms, development definitions, public policies, public policy implementation. (policy implementation) with George Edwards' approach, consisting of communication, human resources, the tendency of the implementer, and the position of the implementer. Qualitative analysis was used with each informant as a source of information, consisting of 1 key informant, 1 main informant and 6 additional informants. The results showed that the implementation of the Rehabilitation Program for Unworthy Houses (RTLH) in Asahan Regency was good, through communication, human resources, disposition and bureaucratic structures, implemented as an integral part of achieving the effectiveness of social development programs for the feasibility of roofs, floors and walls. Implemented social development is defined as the achievement of social welfare with the principles of development that is not centralized and not top down; Human resource constraints with limited staff and community delays in completing the program can be handled properly. The response of the community who benefited from the RTLH Rehabilitation program was good, indicated by the support for program achievements and their acceptance of the requirements that had to be met both administratively and the criteria for the use of assistance.Â