Jurnal Komputer Terapan

Rancang Bangun Sistem Monitoring Penggunaan Air PDAM Berbasis IoT

2021-11-11T03:25:47+00:00

Water is one of the most important sources of life. One way to save water is by monitoring the flow of water consumed per month. The flow rate measurement is applied to every household that uses the PDAM, so that each house is installed a water meter, which is used to measure or record the volume of water that has been used for each household’s needs. The measurement of the volume of water contained in the water meter is used to determine the number of tariffs that must be paid by each household to the PDAM every month of use. In this research, a system is made that can monitor the quality and use of PDAM water. In this system, a turbidity sensor is used which will measure the level of water turbidity in NTU units. This NTU value will show the quality of PDAM water whether it is suitable for use in daily needs or not. The water flow sensor will be installed in the middle of the PDAM pipe, the water flow data measured on the sensor will be processed on the Arduino Uno module to be converted into data for the estimated cost of using PDAM water. Furthermore, all data will be displayed on the LCD, namely data on the level of water turbidity, data on the amount of water discharge and the estimated cost to be paid by the customer. All data will be sent to the blynk server via ESP32 Camera. The data stored on the server can be accessed using the blynk application on a smartphone. In addition, the data will also be stored on the SD Card as a data backup. The results of the turbidity sensor readings show a water turbidity value of 5 NTU. The error value of the water flow sensor readings is 1.6%, which means the accuracy rate is 98.4%. While the data from the reading of the PDAM water usage costing system has no errors so that the data accuracy reaches 100%.

Using KNN Algorithms for Determining the Recipient of Smart Indonesia Scholarship Program

2021-11-11T03:18:45+00:00

The Smart Indonesia Card (KIP) scholarship program is a government scholarship program through the Ministry of Religion of the Republic of Indonesia which is given to students who have a good academic level but have a weak economic level. Sultan Syarif Kasim State Islamic University, Riau accepts new students every year, but the quota for the KIP scholarship program is limited. With the limited quota for the KIP program, a system is needed that is able to classify submission data from students who register for the KIP program, so that the selection process can be carried out, quickly, precisely, and in accordance with the required quota. In this study, the K-Modes and K-Nearest Neighbor (KNN) Algorithms were used by using the achievement variables, report cards, and national exam scores when high school, father's income, parental status, and homeownership status. Reprocessing is carried out before the testing stage, testing is carried out by performing the initial stages, namely clustering using the K-Modes algorithm, then validating or testing data by applying the Grid Search Cross-Validation (GSCV) method, and finally predicting using the KNN algorithm. The test resulted in a performance value of 66.79%

Implementasi business intelligence dashboard untuk visualisasi data pasien posbindu ptm binaan uptd puskesmas kecamatan

2021-11-11T03:19:17+00:00

Posbindu PTM (integrated non-communicable disease fostered post) is a form of community participation in early detection, monitoring and early follow-up of PTM risk factors independently and continuously. The target of this program is aimed at all healthy and at-risk communities aged 15 years and over. This PTM Posbindu activity is held once a month. For Rokan IV Koto sub-district there are 10 Posbindu PTMs. After conducting the survey, the management of Puskesmas Rokan IV Koto has managed patient data using excel as a source of annual performance reporting. However, management Puskesmas Rokan IV Koto had difficulty getting information from patient data in accordance with the management's wishes. What the management of Puskesmas Rokan IV Koto wants is to know the distribution pattern of PTM, patients and patients at risk of PTM. The design of this system uses tools including: Framework CodeIgniter, PHP as a programming language and MySQL as a DBMS. This system is tested using black box testing and user acceptance test (UAT). Based on the user acceptance test (UAT) that has been carried out, it shows that 88% of the system that has been built has been accepted by the user and black box testing shows that the function has been running 100%. The benefit of this business intelligence system is that it is able to assist the head of the puskesmas in making decisions.

Keywords: Puskesmas Rokan IV Koto, Patient Data, Business Intelligence, MySQL, PHP

Technology Utilization to Simplify Administrative Management and Communication in Residential Estate

2021-10-14T06:56:43+00:00

The increasing crime rate during Covid-19 pandemic has impact in the administration of entering and exiting residential estate on the one gate system to be complicated so it takes time and results in queues. On the other hand, under government recommendations to reduce mobility outside the home has disrupted the residential administration. Various housing applications that have been developed are still conducting administration in and out at residential gate conventionally and limiting access rights to applications only by residential members. Such an application has not overcome the problem of the length of the licensing administration process at the residential gate. In this paper, an android application with QR code technology is offered to assist residential administration while simplifying the administration of permits in and out of residential gate. The research was conducted using Waterfall method while to generate a QR code was used QRCodeWriter. Based on the interview, all parties involved stated that the application helped housing administration continued to run well despite restrictions on activities outside the home and simplified administration at the residential gate. But, at the user's point of view as resident, the application was considered inconvenient because they should to learn something new.

Aplikasi uji kepribadian berdasarkan multiple intelligences Berbasis web menggunakan metode prototyping

2021-11-11T03:18:13+00:00

Multiple intelligences (MI) was developed by Howard Gardner, a developmental psychologist and professor of Harvard University, United States. His theory of Multiple Intelligences (MI) was published in 1993. Gardner believes that as his name implies, multiple intelligences, human cognitive competencies are better described in terms of multiple intelligences such as abilities, talents, or mental skills, which are called intelligences. Everyone has their own abilities and has a certain level in each of these intelligences. From this research resulted in a web-based application that can identify the type of personality and suggestions for each personality then interesting info about each personality. Built using the Laravel framework, PHP and MYSQL programming languages, and using the prototyping method in two iteration, to make the requirements of user for the system can be fulfilled. The results of usability testing through 30 respondents stated that the system was very feasible to use, then using a validation test the results obtained on the system and manual calculations obtained accurate results from the ten samples used and finally the results of the user acceptance test, it was found that all functional systems were running according to which are expected.

Teknik Audio Forensik untuk Analisis Rekaman Suara sebagai Barang Bukti Digital

2021-11-11T03:19:02+00:00

Technology plays an important role in everyday life for many people. Then, the problem that arises is the use of technology that is not appropriate and misuses it for personal interests, giving rise to cyber crimes such as drug transactions. The existence of digital evidence can assist in uncovering cases of cyber crimes using digital evidence of sound recordings. Therefore, this research is expected to reveal these cyber crimes. Efforts to analyze sound recordings are carried out using audio forensic techniques to show ownership of voices so that they can be used as evidence. A minimum of 20 words are required that have similarities between the voice of the evidence and the voice of the subject. From the results of the study, it was found that sample A had identical words with evidence of more than 20 words. Sample A has 21 identical words in pitch analysis, 5 words in ANOVA statistical analysis, 26 words in graphical distribution analysis and 24 words in spectrogram analysis of the 30 words analyzed. It can be concluded that audio forensic techniques can show ownership of sound recordings with the results of voice recordings of sample A being identical to the evidence

Application of LightGBM Method for Abnormal Driving Behavior Classification on Motorcycle Driver Based on Smartphone Sensor

2021-11-27T06:26:12+00:00

Traffic accident is one of the most significant contributors which makes the death number is increasing around the world. With the demographic condition from Indonesia, motorcycle driver is the types of the driver that dominated the traffic, therefore increasing the probability of caught in a traffic accident The existing Vehicle Activity Detection System (VADS) mainly focused on the car driver, with the main problem is that the computational time from the system is too high to be implemented on a real-time condition. To solve this problem, in this research, a classification system for abnormal driving behavior from motorcycle drivers is created, using Light Gradient Boosting Machine (LightGBM) model. The system is designed to be lightweight in computation and very fast in response to the changes of the activities with a high velocity. To train the LightGBM model, the data from Accelerometer and Gyroscope sensor, that has been integrated into a smartphone, will be used to detect the movement from a driver. The accuracy rate from the proposed model is reaching 82% on the test dataset and shows a promising result of around 70% on the real-time detection process. With a computational time of around 10ms, the proposed system is able to work 5 times faster than the existing system.

Pengembangan Aplikasi Pengelolaan Tugas dan Fungsi Balai Monitor (Studi Kasus: Sarana dan Pelayanan)

2021-11-26T04:51:11+00:00

Facilities and Services at the Balai Monitor Radio Kelas I Pekanbaru is one of the fields of service to the community.Currently, facilities and services have not implemented and utilized the existence of integrated information technology to support daily work activities so that most service operational activities are still carried out manually.Some activities are still carried out manually, automatically making it difficult and slow for officers to serve the community and make reports.The Management System for Duties and Functions of the Facilities and Services Section is expected to help overcome problems in providing services to the community and managing data services. The system was built using the prototyping method 3 times iteration. Testing of this application is done by UAT through questionnaires and Blackbox Testing to test functional suitability. Based on the results of the questionnaire found that the application meets the criteria of UAT where 100% of respondents agreed that the application display design was easy to remember.95% of respondents agree that the application is easy to reach. and 98.3% of respondents agreed to have an efficient function. Based on the results of Blackbox testing,the application can run smoothly according to existing needs

Perancangan Sistem Informasi Geografis Pariwisata Pasaman Barat Berbasis Android Menggunakan Metode Haversine

2021-11-27T07:20:19+00:00

Tourism is an activity that is mostly carried out by the community today which aims to find a new atmosphere outside of daily routine activities. There are quite a lot of tourist destinations in Sumatra and one of them is a tourist location in West Pasaman Regency. However, many tourist objects are not known by visiting tourists, due to the lack of available tourist attraction information. Geographic Information System (GIS) can provide location information of a place, which can be used to display the location of tourist objects needed by tourists. The design of this system provides distance estimation calculations and recommendations for the closest distance locations using the Haversine method which functions to calculate the distance between two points. The system is designed on the android platform, MySQL database and PHP programming language. Tests using White Box, Black Box, and comparison testing with Google Maps Distance. In the White Box testing on the Haversine Formula program code and the tourist display program code, the results obtained are Cyclomatic Complexity 1 and 2 values, it is concluded that the program code has a simple risk level and without much risk so that it is easy to maintain and test the program flow. Black Box testing concluded that the functionality of the system is running well, in the analysis of the comparison test obtained an accuracy value of 100% and it is concluded that the calculation results are the same as Google Maps Distance

The Use of Mobile Assistant Application to Identify the Crowds in Covid 19 New Normal

2021-11-02T08:18:00+00:00

The new normal life post COVID 19 pandemic can utilize the technology to support the implementation of social distancing, particularly in finding out the number of crowds or people gathering in an event or a location accurately. The process so far is done by manual counting which requires a lot of efforts. This information is demanded to suppress the number of COVID 19 cases. Therefore, the mobile application that can be used anywhere and can support high mobility is currently needed. This study tries to create a Mobile Assistant Application based on the Android Operating System, by incorporating a tracking function from the location using GPS (Global Positioning System) or a method commonly called Location Based Services (LBS) to inform the people’s presences in public places that can be accessed such as market, office, hospital, praying building, school and others. Software development method will apply the Extreme Programming method cosisting of four stages namely planning, design, coding and testing. This application can support the Government's performance in carrying out the new normal life and finding out the number of crowds, so that the social distancing can run optimally and reduce the virus spread.

Pengujian Kualitas Website E-Commerce Produk Daur Ulang Sampah Menggunakan WebQual4.0

2021-11-30T00:41:36+00:00

E-commerce adalah penyebaran, pembelian, penjualan, pemasaran barang dan jasa yang dilakukan oleh konsumen melalui sistem elektronik seperti internet, WWW (Word Wide Web), atau jaringan komputer lainnya. Pemanfaatan website dan sosial media sebagai mesin penjual sudah mulai berkembang sejalan dengan kemajuan e-commerce. Bank sampah merupakan sumber daya bahan sampah yang dapat didaur ulang dan dijadikan produk layak pakai yang keberadaannya hingga saat ini telah berlangsung namun belum memiliki media promosi online yang sesuai dengan kebutuhan. Oleh karena itu, dengan adanya E-Commerce Produk Daur Ulang Sampah dapat membantu pihak Bank Sampah DLHK Pekanbaru dalam

melakukan penjualan maupun melakukan promosi produk daur ulang sampah. Sistem ini dirancang menggunakan Bahasa pemrograman PHP dan MySQL sebagai database management system, dan Xampp untuk server localhost web. Setelah e-commerce di implementasikan di lingkungan Bank Sampah DLHK Kota Pekanbaru, maka dilakukan pengujian terhadap pemanfaatan e-commerce dengan menggunakan metode webqual 4.0. Pengujian pemanfaatan e-commerce dengan metode webqual4.0 ini melibatkan 27 responden dan 24 butir pernyataan. Berdasarkan data yang didapat, maka diperoleh hasil uji pemanfaatan e-commerce dari faktor kegunaan 84,68%, faktor kualitas informasi 83,91%, faktor kualitas interaksi 84,81% dan faktor kepuasan pengguna 85,03%

Perbandingan Algoritma C4.5 dengan C4.5+Particle Swarm Optimization untuk Klasifikasi Angkatan Kerja

2021-11-11T03:24:54+00:00

In a large dataset, data mining is a solution to arrange new models into useful information. The algorithm is often used in machine learning is C4.5. This algorithm is known to be very strong in classifying, but has several weaknesses, such as overlapping and overfitting of data. To handle this, it is necessary to select an attribute that can identify the relevant attribute without reducing the accuracy of the algorithm itself. The Particle Swarm Optimization (PSO) is an optimization algorithm which one can be used as an attribute selection. The PSO benefit is that to easy to use, efficient and has a simple concept when to compared of data mining algorithms and other optimization techniques. In this study, the precision of C4.5 which is optimized by Particle Swarm Optimization (PSO) algorithm is proven to be higher than using the C4.5 algorithm alone. Where the algorithm C4.5+PSO has an precision of 66.80% while the algorithm of C4.5 has an precision of 76.32%.

Analysis of Public Opinion Sentiment on Covid-19 Vaccine on Twitter Social Media with Robustly Optimized BERT Pretraining Approach

2021-11-02T08:27:52+00:00

On March 11, 2020, the World Health Organization (WHO) officially declared COVID-19 a global pandemic. The spread of this virus already existed in 2019 in the city of Wuhan, China. The government officially stipulates a Presidential Regulation (PERPRES) on Vaccine Procurement and Vaccination Implementation in the Context of Overcoming the Coronavirus Disease Pandemic. The vaccination activity plan must also consider various inputs, among them is by looking at how the response and public opinion to the vaccination discourse. By utilizing data from Twitter social media, this study aims to analyze the public's response to the vaccination discourse by classifying the response into positive and negative responses. Furthermore, public opinion grouping will also be carried out using the pre-trained Indonesian RoBERTa Base Sentiment Classifier model to find out the sentiments of the Covid-19 vaccination topic discussed by the community. The results of the analysis showed that the public gave more negative responses to the discourse (24.7%) compared to positive responses (5.7%) with the remaining neutral responses (69.6%). Sentiment words that occur most often also indicate more words with negative sentiments than words with positive sentiments. The average results of the prediction accuracy of the application of the pre-trainer model on the positive label are 84%, Neutral 97% and Negative 93%.

Design and Build an Organic and Inorganic Waste Detector Using Proximity Sensors and NodeMCU ESP8266

2021-11-26T04:49:44+00:00

Waste products are increasing every day in line with the increasing number of products and people's consumption patterns. Many people do not separate organic and inorganic waste during disposal. One of the reasons is that people cannot distinguish between organic and inorganic waste. Based on these problems, an Internet of Things-based tool was designed that uses NodeMCU ESP8266 as its microcontroller. To distinguish organic and inorganic waste, three sensors are used at once, namely proximity infrared, capacitive and inductive sensors. The data read by this tool then turns on the LED according to the type of trash can. In this study, a trash can was also designed that uses an ultrasonic sensor to detect the height of the garbage. This altitude information is then sent to a website-based monitoring application using a Wi-Fi network and the MQTT protocol. This application is used by cleaners to monitor which trash bins have to be transported. From the test results, the three proximity sensors used succeeded in distinguishing organic and inorganic waste. The recommended distance for the sensor to work optimally is 3 mm. The data obtained by the sorting tool has also been successfully sent to the waste height monitoring application. Officers get notifications on the website, which trash bins must be transported.

Systematic Literature Review Penerapan Metodologi Agile Dalam Berbagai Bidang

2021-11-27T06:51:18+00:00

The development of the telephone or cell phone and the internet, its existence has an influence on various aspects of life. Both individual life, social and related to the world of business or business. In addition to simplifying and accelerating the process of communication and information, information technology is also used in business or business activities. Many communication and information tools are used in the activities of the business world, one of which is the application. Applications are generally divided into 3 platforms, namely desktop, web, and mobile. In building an application, it takes a software development methodology that is used for the smooth design or development of an application. Web-based application development has many methods that can be used, one of which is the Agile method. This method is one of the well-known methods because it is considered actual and easy to use. This study uses a systematic literature review method that displays an analysis of agile methods in various fields covering a total of X papers published from 2017 to 2021. This study aims to answer several research questions, namely: 1) Knowing what trend models are used in agile methods, 2) Knowing what fields implement agile methods in their application development, 3) Knowing the application platforms that are most often used in agile methods. The purpose of this research is as a literature study related to the use of Agile and it is hoped that readers will gain knowledge about what Agile methods will be used for their applications.

Keywords: Platform, Agile, Systematic Literature Review.

Pemanfaatan ReactJS dan Protokol MQTT untuk Visualisasi Sinyal Lampu dan Notifikasi secara Waktu Nyata pada Sistem Pemonitor APILL di Kota Pekanbaru

2021-11-27T06:53:44+00:00

The majority of signalized intersections in Pekanbaru city are still regulated by analog controllers. The main problem that occurs with this condition is the occurrence of long traffic jams if there is damage to the traffic light controller. Thus, the Pekanbaru City Transportation Department cannot act immediately once a problem occurs. Related to these problems, an integrated system has been developed that functions to manage and monitor traffic light conditions in real time. This research is focused on discussing the use of ReactJS and MQTT. ReactJS is used to display traffic light light signal data and provide real time notifications into a web browser. Meanwhile, MQTT is used as a medium to manage data communication between the detection module installed on the traffic light controller in the field to the Back-End server. This data is then displayed to the web browser via React JS. With the solution in this research, it is hoped that the Pekanbaru City Transportation Office can find out the problems of traffic light lamps in the field quickly, so that they can immediately take the relevant actions needed.

Implementation of SMOTE and Under Sampling on Imbalanced Datasets for Predicting Company Bankruptcy

2021-11-27T06:56:36+00:00

Company bankruptcy becomes a serious problem because it can cause economic damage and other social consequences. It’s very important to predict bankruptcy as early as possible because prediction can be useful for evaluation and planning to avoid bankruptcy. Bankruptcy prediction is one of the imbalanced classification problems because the data with the bankrupt class is far less than the non-bankrupt class. This study aims to produce a good classification model for predicting bankruptcy. Resampling used a combination of SMOTE and under sampling, is applied to the training data to produce more optimal classification model. The classification method used for prediction is multilayer perceptron and complement naïve bayes. Predictive performance was calculated using recall, ROC AUC, and PR AUC. Based on the test, using SMOTE and under sampling is quite significant in improving the classification model on the multilayer perceptron. Resampling in complement naïve bayes also increased. recall and PR AUC scores The best recall obtained was 95.45% with the complement naïve bayes method. The highest ROC AUC with resampling was also obtained using complement naïve bayes of 87.80%. Therefore, it’s concluded that bankruptcy prediction using resampling with SMOTE and under sampling, can produce good performance for detecting bankruptcy.