Dr. Henderi
@raharja.ac.id
Informatics
University of Raharja
RESEARCH INTERESTS
Information system, Data mining, Data Warehousing, Decision Support System, Artificial Intelligence
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Henderi, Giandari Maulani, Didik Setiyadi, Rita Wahyuni Arifin, and Hadi Wibowo
AIP Publishing
Ignatius Agus Supriyono, Irwan Sembiring, Adi Setiawan, Iwan Setyawan, Theophilus Wellem, Henderi, and Ilham Hizbuloh
Pandawan
Internet access at this time is a daily necessity that cannot be denied. It is certain that most institutions and business entities require internet access in carrying out their activities, including educational institutions. With the development of mobile computer technology in which more users use mobile devices to access the internet, wireless-based network infrastructure is a demand that cannot be postponed any longer. By using a wireless connection to connect to the network, authentication becomes something that must be considered, the use of access to the network by unwanted parties can harm other parties. Changing passwords regularly is important to avoid misuse of access to the network by other parties. This paper presents a problem where when an educational institution implements the Bring Your Own Device (BYOD) program, students and teachers cannot change passwords using the personal device used, this is because the personal device is not registered with the domain controller at the institution. The solution proposed in this article is to move the NPS RADIUS server function on the local site to LDAP in the cloud using a combination of WLC which handles Wi-Fi clients and Fortinet which handles authentication to the cloud. The implementation results show that the WLC-Forti framework functions well.
Henderi Henderi, Ranty Irawatia, Indra Indra, Deshinta Arrova Dewi, and Tri Basuki Kurniawan
Ital Publication
Big data collection involves enormous amounts of raw data. To boost the sustainability of corporate value and support business intelligence and decision-making systems, in-depth data analysis is necessary. The data storage, analysis, and visualization methods, as well as the discovery of patterns and linkages, all depend on extensive data analysis. This study aims to process datasets to learn things like how ratings impact market sales transactions and how much of an impact factor connected to consumers and items have on ratings. Elasticsearch and Kibana were used for the dataset processing. This study evaluated traits related to the test parameters using a variety of test procedures. The product is scored as a representation of the product types involved in the sales transaction, and the name is assessed as a reflection of the customer. Kibana and Elasticsearch, a full-text search engine, were used in this work to do extensive data analysis on data sets. It is a visualization tool that is employed in a controlled environment to evaluate how ratings impact market exchanges for electronic goods, and it offers suggestions. The study found a substantial relationship between electronic product sales on the Amazon marketplace from 2012 to 2018. It suggested the importance of buyer constituents as users and how different product categories relate to ratings in business transactions. Doi: 10.28991/HIJ-2023-04-03-09 Full Text: PDF
Henderi Henderi
Bright Publisher
Henderi, Qurotul Aini, Danny Manongga, Irwan Sembiring, and Dwi Apriliasari
Pandawan
Significant changes in the financial system are prompted by the growth of the national economy, particularly as a form of payment. The means evolved from barter to things or commodities to metal and paper as the base materials for money before arriving at barter. With such significant changes, there is also a need for a transformation in the world of education in order to welcome technological advancements and one way to survive the changes in the increasingly rapid digital era. As the economic need increases, trade transaction methods shift from traditional to internet-based. One of the necessary international online payment options is bitcoin. For many applications where payments are modest and instantaneous approval is required, Bitcoin is inappropriate because of the high transaction fees and long confirmation periods. As a result, despite the introduction of numerous rival cryptocurrencies to address these problems, the Bitcoin network continues to be the most extensively used payment method. Unquestionably, new finding of this research that effectively address the problems of high transaction costs and transaction verification times are needed if the company is to benefit from its user network. The Lightning Network (LN), which makes use of off-chain bidirectional payment channels between participants, is one of the most recent payment network concepts to be proposed.
Mukti Budiarto, Hindriyanto Dwi Purnomo, Budhi Kristianto, Henderi, Sendy Zul Friandi, and Ananda Alifia Putri
IEEE
Utilization of CCTV cameras to identify upside down or downed chicken images equipped with Artificial Intelligence technology as an early effort to monitor the behavior of chickens due to toxic or dangerous gases in the broiler business is the application of technology used to reduce the problem of adult chicken mortality due to poisoning from accumulation. Ammonia gas produced from ready-to-harvest chicken manure is an air condition that is considered unsanitary. The purpose of the application of the use of PTZ type CCTV to reduce the number of deaths of chickens exposed to toxic gases is applied to farms with a cage area of $720 m^{2}$ consisting of 1 floor with a closed house (close house) and has a capacity of ± 11000 chickens. CCTV cameras will capture visual images of chickens in unnatural conditions where their movements are not as active as chickens in healthy conditions. The research method used is to design an Artificial intelligence-based system that is designed to consist of CCTV cameras with motion sensor technology, thermal imaging cameras to study the behavior of mature chickens ready to harvest that inhale harmful gases such as ammonia and methane from the feces in the husks, which then trapped and unable to turn around because of his body weight and position when he inhaled the gas. Another effort that has been made is to operate other devices in the form of a blower fan (Exhoustfan) which works automatically and the system is also equipped with manual operations contained in the panel box in the enclosure. Normal conditions are ready to harvest at the age of 28-30 days, the average body weight is achieved with a weight of 2000-2500 grams per head. The parameters set in this system, to ensure that the chickens remain healthy, are for the temperature value between $30^{\\circ}{\\mathrm{C}}$ to $33^{\\circ}{\\mathrm{C}}$ while the ammonia level is between 20 ppm to 40 ppm. The benefit of this research is that the results obtained from the application of CCTV with this AI method are framing images of chickens experiencing respiratory problems so that they are easily read by cage officers using a monitor screen. The test results show that the tool works well and can reduce the mortality rate of chickens to below 10%. So the conclusion is that CCTV equipment equipped with AI can function to provide images of objects that are considered potential problems.
Mochamad Wahyudi, Mochamad Heru Riza Chakim, Henderi, Sudaryono, Muhamad Viktor A Si, Dimas Bagus Saputra, and Reymund Rahardja
IEEE
Research on measuring digital talent competencies using explainable artificial intelligence is lacking in depth. The study aimed to address this gap by developing a reliable and valid measurement instrument for digital talent. SmartPLS 4.0 was employed for calculations and quality assessment. The measurement model was assessed from both reflective and formative perspectives, using Google Forms to gather responses from 600 participants. The 60 questionnaire items exhibited high validity and reliability, as evidenced by loading factors and composite reliability exceeding 0.70. Direct effects were found in various competencies: adaptability and flexibility had a 0.744 effect on learning dexterity, achievement orientation showed a 0.782 effect on innovative creation skills, customer service orientation had a 0.810 effect on digital networking, and digital communication skills exhibited a 0.824 effect on continual improvement. The measurement model met various criteria for reliability and validity, including loading factors, composite reliability, average variance extracted, cross loadings, Fornell Lacker Criterion, and Heterotrait Monotrait Ratio. These findings supported the acceptance of the measurement model’s quality and validity. SmartPLS analysis yielded an average communality of 0.624 and an average R Square of 0.592, resulting in a GoF index of 0.608. This GoF index, according to Wetzel et al. (2018), falls in the high fit category, indicating the model’s appropriateness for measuring digital talent competencies. In summary, the study successfully developed a robust measurement model for digital talent competencies using explainable artificial intelligence and demonstrated its high fit and reliability for assessing digital talent in various contexts.
Hamdani Hamdani, Heliza Rahmania Hatta, Novianti Puspitasari, Anindita Septiarini, and Henderi Henderi
Institute of Advanced Engineering and Science
Dengue is a dangerous disease that can lead to death if the diagnosis and treatment are inappropriate. The common symptoms that occur, including headache, muscle aches, fever, and rash. Dengue is a disease that causes endemics in several countries in South Asia and Southeast Asia. There are three varieties of dengue, such as dengue fever (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS). This disease can currently be classified using a machine learning approach with the input data being the dengue symptoms. This study aims to classify dengue types consisting of three classes: DF, DHF, and DSS using five classification methods including C.45, decision tree (DT), k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). The dataset used consists of 21 attributes, which are the dengue symptoms. It was collected from 110 patients. The evaluation method was conducted using cross-validation with k-folds of 3, 5, and 10. The dengue classification method was evaluated using three parameters: precision, recall, and accuracy, which were most optimally achieved. The most optimal evaluation results were obtained using SVM with k-fold 3 and 10 with precision, recall, and accuracy values reaching 99.1%, 99.1%, and 99.1%, respectively.
Henderi, Sudaryono, Tubagus Mochamad Isnaeni, Euis Sitinur Aisyah, Mukti Budiarto, and Hamdani Hamdani
IEEE
Covid-19 emerged as a pandemic outbreak that spread almost worldwide at the end of December 2019. While this research was carried out, the Covid-19 pandemic was still ongoing. Many countries have made various attempts to overcome Covid-19. In Indonesia, the government and stakeholders, including researchers, have made many activities to reduce the number of positive patients. One of many activities that the government made is the vaccination program. The vaccination program is believed to be the most effective in reducing the number of positive cases of Covid-19. But nobody knows when the Covid-19 pandemic will end. Stakeholder has to know how the trend of Covid-19 cases in Indonesia to make a better decision for facing Covid-19 cases. This study aims to predict the number of positive Covid-19 cases in Indonesia by conducting a comparative analysis performance of Support Vector Regression (SVR) method and Long Short-Term Memory (LSTM) method in machine learning to the prediction of the number of Covid-19 cases. This study was conducted using the dataset Covid-19 in Indonesia from Control Team from 13 January 2021 until 08 November 2021 and with 300 records. The evaluation has been conducted to know the performance of the model prediction number of Covid-19 with Support Vector Regression method and Long Short-Term Memory method based on values of R-Square (R2), the value of Mean Absolute Error (MAE) and Mean Square Error (MSE). The research found that the method Support Vector Regression has better performance than Long Short-Term Memory method for making a prediction of the number Covid-19 using Machine Learning model based on the value of accuracy and error rate based with the value of R-Squared, MAE, and MSE are consecutively 0.902, 0.163, and 0.072.
Henderi Henderi, Qurotul Aini, Irwan Sembiring, Po Abas Sunarya, Viola Tashya Devana, and Fitra Putri Oganda
IEEE
A variety of information with high research value is produced as an educational asset as a result of the use of various emerging technologies in education. Traditional methods of handling educational resources have emerged. Considering the shortcomings of conventional system centralization methods, people are starting to use decentralized blockchain technology for innovation. The research objective of blockchain 3.0 technology is to support the architecture of the educational digital asset management system also suggested in this article, which also uses bitcoin. Apart from performing essential blockchain validation and storage, it transforms the disparate data that students generate across their classroom and extracurricular learning activities into educational digital assets. To study the growth of school users and achieve educational goals of educating students according to their individual talents and peculiarities, the system can use a variety of heterogeneous data from digital assets.
Henderi, Muhamad Yusup, Po Abas Sunarya, Ninda Lutfiani, and Efa Ayu Nabila
IEEE
In the life of Education 4.0, information is very vulnerable to security. Assessment is an integral part of learning. In addition to attendance, assignments are the main point in determining the graduation of a course. However, there are some safeguards for student activity assessment input platforms, which are dangerous, and data leaks can occur. Taking advantage of its open-source, transparent, and immutable or immutable nature can help secure the various platforms used. The University's need for various information makes the application of Blockchain technology a very appropriate thing to use. With the use of Blockchain, the security of student activities is more guaranteed, and it is easier to control by the Lecturer Board. This study aims to secure student activities from forgery and fraud when inputting activities using blockchain technology. The framework created also uses gamification as something that motivates learning activities. The author has analyzed the security needed for activity verification in the form of levels on several applications, one of which is a platform-based application used for the Merdeka Learning-Independence Campus platform. The method used in this research is descriptive research in the form of a literature study that prioritizes gamification in a platform framework. The urgency of this research is to secure the Merdeka Learning-Independence Campus platform for students who need more security in their data storage. If security is increased, student confidence and learning motivation towards the activities carried out will increase so that learning motivation will be better so that the quality of learning will be better.
Henderi, Mumammad Hudzaifah Nasrullah, Laura Belani Nudiyah, Po Abas Sunarya, Sofa Sofiana, and Didik Setiyadi
IEEE
River pollution has become a severe problem in Indonesia. Industrial waste causes water pollution because the waste is not filtered before being discharged into the river. Illegal waste dumping cannot be prosecuted due to insufficient data and unknown disposal times. Therefore, a tool is needed to measure river water waste to measure polluted water waste data. Studies on river water monitoring devices have shown that there are no portable monitoring tools based on the internet of things for river water waste that follows regulatory standards from the Minister of Health. This study aims to produce a portable monitoring tool based on the internet of things for water waste. The system was developed using TDS sensors, turbidity, pH, MQ-135 sensors, and the system is equipped with a GPS module to indicate the location's latitude. The monitoring system is developed through the stages of system design, testing water samples, setting water quality standards and required hardware and components, setting river water quality parameters, and conducting system testing. The test results show that the system can send the data obtained to dashboard things via an internet connection, the TDS sensor error rate is 2.17%, the pH sensor error rate is 1.87%, the turbidity sensor error rate is 1.66%, the MQ135 sensor value is at the quality limit. The internet of things-based portable river waste monitoring system produced through this research helps related parties to identify and handle polluted rivers. Water according to the standards of the Ministry of Health, and the GPS module shows location measurements and information according to the location's latitude on google maps.
Fransiskus Panca Juniawan, Dwi Yuny Sylfania, Rendy Rian Chrisna Putra, and Henderi
IEEE
The pandemic has brought many negative impacts on human life. One of the negative impacts is economic downturn of Micro, Small, and Medium Enterprise (MSME) actors in Bangka Belitung Province. To solve this problem, a website-based marketplace platform called Yobagi was created. As we know, a new software product must have a good user experience. By having a good user experience means that the product has met the needs of its users. For this reason, an evaluation of the user experience is necessary. This study aims to measure the user experience of using Yobagi. The evaluation uses the User Experience Questionnaire (UEQ) tool, which consists of six scales: Attractiveness, Efficiency, Perspicuity, Dependability, Stimulation, and Novelty. There were 40 respondents who were taken from the top of MSME actors. As the UX evaluation results, it is known that the final score of the six scales is above 0.8 and at the excellent level. This means that Yobagi users have a very good user experience in using Yobagi. In addition, Yobagi has met the criteria for good software by having an excellent user experience value.
Anindita Septiarini, Hamdani Hamdani, Eko Junirianto, Mohammad Sofyan S. Thayf, Gandung Triyono, and Henderi
IEEE
Oil palm plant diseases typically manifest themselves on the leaves, resulting in reduced crop quality. It is necessary to solve this issue as the need for premium-quality palm oil keeps growing. Despite the fact that various automatic detection models for oil palm leaf disease have been developed, their performance was frequently inadequate due to the similarity of class characteristics. This work proposes a method that automatically detects the oil palm leaf disease on a natural background to distinguish between infected and healthy leaf classes. The method was developed using deep learning based on Convolution Neural Network (CNN) model. The private dataset consists of 600 oil palm leaf images (300 healthy and 300 infected) on a natural background. In order to decrease the computation time, pre-processing was carried out, which consists of resizing and normalizing the image, followed by augmentation. Augmentation was applied by rotation, flip, shear, and zooming techniques. Furthermore, the CNN model was employed to detect oil palm leaf disease using Tensorflow 2.5.0 framework with $224\\ \\times\\ 224$ input data. The proposed method successfully achieved the highest performance, revealed by the accuracy value of 1.
Muhamad Yusup, Yusuf Durachman, Henderi, Dedeh Supriyanti, Marviola Hardini, and Delfi Martika Sari
IEEE
In the era of the Industrial Revolution 4.0, technological advances are very important in two areas of publishing educational journals. In science, scientific research is the most important symptom of scientific publications. Today, scientific publications undergo very significant changes. Journal publishing platform or commonly called journal publishing is a journal service system container that is used to disseminate information about scientific research data through the Open Journal System (OJS). One application of gamification techniques in journal publications can be applied to the display board. Due to gamification, users or researchers become more motivated because of the points collected. Display becomes more informative and attractive so that research indicators increase. Users or researchers can also find out information or journals that are often read by other users.
Henderi, Nur Azizah, Allya Nissa Daswar, Muchlishina Madani, and Agung Rizky
IEEE
There has been a developing interest in solving the different technical problems that Emitting Passive Silicon Solar cell contact (EPSc) through process optimization including chemical polishing, dielectric passivation and contact geometry etc. In this contribution, a detailed investigation on recombination and resistive losses at rear surface of EPSc solar cells using advanced imaging techniques for spatial distribution and allied characterization approaches are performed for better understanding of loss mechanisms and possible routes for their mitigation. Our investigation that spreading resistance $(\\mathrm{R}_{spr})$ and the converse immersion current thickness through the principal diode $(\\mathrm{J}_{01})$ are the two primary boundaries when estimating the effectiveness increment of EPSc sun based cells. For the back dielectric with a gap of $45\\mu M$, the improved round contact calculation shows a lower $\\mathrm{R}_{spr}$ and $\\mathrm{J}_{01}$ contrasted with the direct plan. Our estimations additionally show the chance of a further expansion in outright energy transformation productivity of 1.29 $\\mathrm{m}$ through the right decision of beginning wafer obstruction and further developed passivation consistency on the sun powered cell surface.
Tri wahyuningsih
Bright Publisher
This study aims to find correlation assessment of Automatic Short Answer Grading (ASAG) by comparing three methods of Cosine Similarity, Jaccard Similarity and Dice Coefficient by providing one reference answer. From the results of computing using Python programming language and data processing using spreadsheets, it was obtained that the Dice Coefficient method had the highest correlation average value of 0.76, followed by Cosine Similarity with an average correlation value of 0.76, and the lowest correlation average value was the Jaccard method with a value of 0.69. The contribution to this study is the use of three methods in one data, whereas the previous research only used 1 method for 1 data or 2 methods for 1 data. So, the value in this study resulted in a more complete comparison and accuracy of data.
Amitkumar Dudhat, Nuke Puji Lestari Santoso, Henderi, Sugeng Santoso, and Riri Setiawati
Pandawan
The challenge that has often occurred in recent years is making access to education using a different learning process path. The presence of technology now provides solutions to problems that often occur such as communication, accessing information, and business or cooperation. Blockchain is a technology that develops an evaluation model for itineraries in the learning process, both individually and in bulk. Currently the Edublocs project has been designed and implemented, which combines elements of peer-to-peer learning and the teaching team. The aim of the Edublocs project is to simplify the process of designing and implementing a system for recording activity results through blockchain technology. This ongoing project is in the process of evaluation. Conforming to some design elements as well as experimental implementation in the context of higher education enables us to further indicate the sustainability and relevance of the application of blockchain technology in education.
Hamdani Hamdani, Tara Nita Setiawinata, Anindita Septiarini, Henderi, Zaenal Abidin, and Hartatik
IEEE
Amidst the ascension of more advanced technology in the digital era, information could easily be obtained at the fingertips. Despite risking being obsolete, libraries have remained essential as primary sources of information, research, and educational tools, especially for students and educators alike. As one of the public institutions, libraries strive to provide high-quality and optimal service to their customers. This research is conducted to amount the customer satisfaction and the service quality of the library users and determine if the quality of service is as perceived. An observation period was performed at which 100 data were collected and calculated using Fuzzy Service Quality (Servqual) at East Kalimantan Regional Library. The conclusion could be drawn that customer satisfaction was indeed low. Overall, this was suggested by the vast GAP value for the Tangibles dimension, which read −10.67. Customers were also left disappointed in particular by the quality of free Wi-Fi service, which read −14.92. This means that improvements are needed in those aforementioned areas.
Taqwa Hariguna, Athapol Ruangkanjanases, and Henderi Henderi
Faculty of Engineering, University of Kragujevac
D Silahudin, Henderi, and A Holidin
IOP Publishing
Abstract This paper offers an expert system model for COVID-19 diagnosis as an effort to overcome the spread of COVID-19 in Indonesia. The expert system model was built using the Naive Bayes Classifier method. Model development is carried out with preliminary research stages, data collection, analysis, model design, implementation, and testing. The data used to build and test the model comes from the health department and the acceleration of the Covid- 19 countermeasure group in Indonesia. The model was developed with a unified modeling language and a prototyping approach. Tests show that the developed COVID-19 diagnosis system expert model can diagnose COVID-19 based on the symptoms inputted by the user into the system. The application of the model produced in this study helps assist doctors in diagnosing COVID-19.
Henderi, Rani Putri Merliasari, Harco L.H. S. Warnars, and Sugiyatno
IOP Publishing
Abstract COVID-19 makes the community must carry out activities such as school, work, and worship at home. However, the long-running activities from home make people experience boredom which can lead to stress. On the other side, the entertainment obtained by the public through smartphones by reading articles by their interests can reduce boredom. This paper proposed a rules-based decision support system to help the people to make choices of their activities from home while COVID-19 e rules-based approach for make an application decision support system. Ruled base used in application to selected process through characteristics following the interests of the community. This decision support system is implemented in mobile web applications. The system can display articles based on interests by questions or statements through the front end system. The results showed that most users of the application in a happy condition while working from home.
Henderi, Ageng Setiani Rafika, Harco Leslie Hendric Spits Warnar, and Meldi Anggara Saputra
IOP Publishing
Abstract Coronavirus disease (COVID-19) that has entered Indonesia made the government impose large-scale social restrictions to reduce the spread of the coronavirus. As the increase in patients confirmed positive, the government continues to appeal and ask the Indonesian to use masks. Whether it is a healthy people or those who are sick. This appeal is in line with the recommendations of the World Health Organization (WHO) in preventing the spread of COVID-19. Therefore it is necessary to develop tools for monitor people who have not used masks in public service areas in real-time. We develop an application of mask detection using a camera that functions as photo and video input and connected to Speed Maix Bit microprocessor to process data and display it to the LCD. We purposed the tools to solve the problems regarding people who were not used masks or not immediately to minimize the spread of COVID-19. Our final experiment demonstrates that the application highly detects people using masks or not in the public area. This study contributed to the conception, design system, and rules-based for application of mask detector to prevent Covid-19.
Po Abas Sunarya, Henderi, Sulistiawati, Alfiah Khoirunisa, and Pipit Nursaputri
IEEE
The rapid development of technology has caused some systems to have changed; most of them in the Industrial Revolution 4.0 era using new methods from various aspects of people's lives. Family Deed Certificate is a family identity that contains data about arrangements, relationships, and the number of family members. A family certificate is an essential thing for every citizen to have. However, related problems that occur are still using conventional systems that cause problems such as loss of family deed, and various manipulations of identity data. Thus, from this problem emerged a solution to guarantee all data and information security using blockchain technology. Blockchain technology is a technology for recording transactions with modern technology, which can only be added but cannot be changed or replaced. Blockchain technology can support various fields such as banking, education, health, and priorities for governance. For this research, this is applied in the field of government, which is a blockchain technology family certificate, various problems in terms of a family certificate that is a copy of a lot of family member data, and editing a deed of change, is very inflexible. With the family certificate system, blockchain technology, data security can be guaranteed so that there is no data falsification and can replace any loss on the family deed. This system uses the literature method that contains and how blockchain works. The Certificate of Family Deed on the blockchain is expected to impact the digital world positively.
Henderi, Miftah Maulana, Harco Leslie Hendrie S. Warnars, Didik Setiyadi, and Taufik Qurrohman
IEEE
The government in Indonesia and its staff work together to make tactical steps to prevent the spread of COVID-19 in the community. From the ministerial level to the heads of the provinces, regencies, and even the government. Therefore, this study aims to make a model decision support system to diagnose patients exposed to Covid-19, such as people in control, patients in oversight, and those who are positive for the Covid-19 Virus. Model decision support system development aims to provide information about the development of COVID- 19 and help the community in diagnosing themselves related to COVID-19 infection. In this study, the authors use the forward chaining method in application to get conclusions from the symptoms of the Covid-19. This research resulted in an application that patients exposed to the Covid-19, and it's also provided a solution for healing from patients. And this could be a reference for patients before consulting further with the doctor.