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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Register: Jurnal Ilmiah Teknologi Sistem Informasi METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi International Journal of New Media Technology Jurnal ULTIMATICS JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Indonesian Journal of Electrical Engineering and Computer Science International Journal Of Science, Technology & Management (IJSTM) Jurnal Mandiri IT Ceddi Journal of Information System and Technology (JST)
kusnadi, adhi
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Public Health Transportation

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Implementation of AHP Algorithm for Design and Development Halal Food Recommendation System at Cirebon Regional Geneva, Erick Abraham; kusnadi, adhi; Tobing, Fenina Adline Twince
IJNMT (International Journal of New Media Technology) Vol 10 No 2 (2023): IJNMT
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v10i2.3491

Abstract

Cirebon is one of the cities in Indonesia that has a variety of unique culinary delights. One of the most famous Cirebonese halal culinary delights is nasi jamblang. However, the many choices of halal Cirebonese food can make tourists struggle to choose food that suits their taste and preferences. This research aims to design and build a halal Cirebonese food recommendation system using the Analytical Hierarchy Process (AHP) method. The AHP method is used to determine the weights of the factors that influence the selection of halal Cirebonese food. This recommendation system is built using PHP and JavaScript programming languages, as well as Laravel, React, and MySQL frameworks. This recommendation system has been tested by distributing questionnaires using End User Computing Satisfaction method with google form to 35 respondents The test results show that this recommendation system produces a user satisfaction value of 87.92%. This value indicates that this recommendation system has met user expectations.
Implementation Of Fuzzy Multi-Criteria Decision Making To Design An Expert System For Prediction Of Digestive Diseases At Dogs Tisna Kusuma, Irene; Kusnadi, Adhi; Adline Twince Tobing, Fenina
Ceddi Journal of Information System and Technology (JST) Vol. 2 No. 2 (2023): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v2i2.50

Abstract

A dog is a kind of animal that is often looked after at home. Except for being known as a human's friend, a dog is also able to be trained to do many things. The age of the dog depends on the type of race. If it's fed well, exercises, and visits the doctor regularly, a dog can live longer. Dogs are very sensitive to certain diseases; one of them is intestinal disease. An expert system of a dog's digestion is built for the dog's lover so that they know exactly what's disease, which relies on the appearance of the symptoms. The symptoms of the different intestinal diseases look almost similar. For this reason, we need an appropriate method to get a precise result. Fuzzy multiple-criteria decision-making can help make the right decision that has some consideration points. This method is also equipped with optimal ultimate selections, which leads to a very precise result. The goal of this application is to know the right kind of disease and its therapy. This study has been validated by matching the results of the application with the doctor's diagnosis. The compatibility level is 80%.
Implementation of Vikor Algorithm in Web-Based Recommendation System for Obstetrician Selection Andrew, Richard; Adline Twince Tobing, Fenina; Kusnadi, Adhi
International Journal of Science, Technology & Management Vol. 4 No. 5 (2023): September 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i5.915

Abstract

The process of childbirth is a natural event for women; with the increase in birth rates, selecting a suitable obstetrician becomes essential. However, many couples find it challenging to choose the right obstetrician, from consultations to hospital births. This study aims to develop an obstetrician recommendation system to overcome decision-making challenges that involve many criteria. The method used is VIseKriterijumska Optimizacija Kompromisno Resenje (VIKOR), which is one of the best methods in Multiple Criteria Decision Making (MCDM) for ranking and selecting alternatives. This method involves several steps, including determining the weight of the criteria, normalizing the matrix, calculating the Utility Measure and Regret Measure, and calculating the VIKOR index. Testing was carried out through scenario tests and user survey tests using the USE questionnaire. The scenario test results show the successful implementation of VIKOR in this system. The results of the user survey test indicated a high level of satisfaction with a score of 83.34%, which fulfilled the four variables in the USE questionnaire: usability (79.76%), ease of use (84.81%), ease of learning (84.81), and satisfaction (83.31%). The results of this study have important implications for increasing the effectiveness of decision-making in selecting the right obstetrician. By incorporating the VIKOR method into an application, this research provides a valuable contribution to developing a VIKOR-based recommendation system. It emphasizes the importance of applying this method in complex decision-making environments.
Innovations in Software Configuration: Introducing a Data Comparison Tool Based on the Myers Diff Algorithm Augustino, Lorentzo; Kusnadi, Adhi; Vasty Overbeek, Marlinda
International Journal of Science, Technology & Management Vol. 4 No. 6 (2023): November 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i6.974

Abstract

In the realm of software project development, it's not uncommon for changes to emerge at various stages of a project's lifecycle. Such alterations can manifest in virtually every facet of the software development process, from conceptual design decisions down to the minutiae of the source code. To proficiently manage and track these dynamic changes, professionals turn to a specialized toolset known as Software Configuration Management (SCM). One of the standout features that SCM tools bring to the table is the 'diff' capability. This functionality allows developers to identify and review the disparities between two versions of source code. Recognizing the importance and utility of this feature, the primary objective of this research is to create an advanced diff application. This application, by leveraging the Myers Diff algorithm, is meticulously designed to pinpoint and showcase differences in characters between two sets of text-based data. Moreover, it accentuates these differences by visually highlighting the contrasting characters between the two datasets. To ensure the reliability and accuracy of this newly developed tool, we undertook a series of validation tests. We juxtaposed the results from our application against those from a comparable existing tool. Impressively, the discrepancies in results were minimal, with a marginal difference of just 1%. This suggests not only the utility but also the precision of our application in real-world software development scenarios.
Men's Perfume Recommendation System Using Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Method Adline Twince Tobing, Fenina; Kusnadi, Adhi; Endariahna Surbakti, Eunike; Rayhan Harsono, William; Ivan Wijaya, Aurelius; Dinarta, Farrel; Irelynn, Maecyntha; Paskah, Richard
International Journal of Science, Technology & Management Vol. 4 No. 6 (2023): November 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i6.1002

Abstract

Perfume has been a product used for thousands of years by human civilization. Rapid growth of perfume products creates a problem especially for men to choose the best perfume to fit their personality. This research aims to help men find out which perfume suits each individual's personality by inputting a comparison of four main criteria, namely quality, price, aroma and durability. In this research, the research team built a perfume recommendation system specifically for men using the application of the Analytic Hierarchy Process (AHP) & Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The research resulted in an 89.17% usefulness score, 89.34% ease of use, 89.34% ease of learning, and 91.61% satisfaction, resulting in an overall score of 90.07%. The research results demonstrate that the AHP and TOPSIS algorithm can assist men in choosing appropriate perfume through its implementation in the system built by the research team, which was tested using a questionnaire
Implementation of Naïve Bayes Algorithm in Sentiment Analysis of Twitter Social Media Users Regarding Their Interest to Pay the Tax Wahyu Andrian, Bagas; Adline Twince Tobing, Fenina; Zuhdi Pane, Ivransa; Kusnadi, Adhi
International Journal of Science, Technology & Management Vol. 4 No. 6 (2023): November 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i6.1015

Abstract

Since 2008, tax revenue has failed to reach the target set in the State Budget each year. Until 2021, tax revenue managed to reach the target that had been targeted in the 2021 state budget. In the midst of improving tax revenue, towards the end of February 2023, a case involving the son of a Directorate General of Taxes (DGT) that made the father called by the Corruption Eradication Commission (CEC) to be asked for an explanation of his assets. After the case, there were many calls in the community to stop paying taxes, which was assessed by Tauhid Ahmad as Executive Director of Indef as a form of decreased trust in tax collecting institutions. This can affect the amount of revenue from taxes because trust in the government is one of the factors that tend to affect public compliance in paying taxes. Which can affect the amount of revenue from taxes because trust in the government is one of the factors that tend to affect public compliance in paying taxes. One of the crowded calls is the pros and cons of the tax boycott movement on Twitter. With the pros and cWith the pros and cons of the movement that can affect tax revenues on Twitter social media, an assessment based on sentiment analysis is needed which is divided into positive, neutral, or negative categories. Sentiment analysis in this research is carried out using three variations of Naïve Bayes assisted by the TF-IDF word weighting model, namely Gaussian Naïve Bayes, Multinomial Naïve Bayes, and Bernoulli Naïve Bayes. Then Confussion Matrix is used to evaluate the model by obtaining the accuracy, precission, recall, and f1-score values and the use of Synthetic Minority Oversampling Technique (SMOTE) to handle unbalanced data. The results of this study on unbalanced data, the implementation of Bernoulli Naïve Bayes using the SMOTE technique on a dataset comparison of 80:20 resulted in better performance than the variations of Gaussian and Multinomial Naïve Bayes with accuracy results of 91.03%, precision, 71.11%, recall 71.43%, and f1-score of 71.18%.
Implementation of SAW Method for Design and Development Apartment Recommendation System in Tangerang Using Mobile-Based Nugraha, Achmad Ilyasa; Kusnadi, Adhi; Tobing, Fenina Adline Twince
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3492

Abstract

The house is no longer the sole type of residence available while looking for a place to live. Apartments are a solution for those who need a place to live in locations with limited land, such as Tangerang, in today’s period. However, criteria are needed to choose an apartment based on a person’s needs, thus in this project, we will develop and create an apartment recommendation system in Tangerang using the SAW approach to make it easy for people to choose the best apartment. The user’s choice will be determined by the recommendation system based on their interests, activity, and other data. To put the recommendation system into action, the FMADM method must be employed. A Simple Additive Weighing (SAW) approach is required to complete this FMADM, which is a mechanism for computing the number of performance appraisals for each alternative based on all criteria. This recommendation system is called APARTKU, and it was created with HTML5, CSS, and AngularJS, as well as the Ionic Framework and the Firebase Database. The system was then put to the test by administering questionnaires to 32 respondents using the DeLone and McLean methodologies, and the results were tallied using the Likert Scale method, yielding a score of 90.64 percent, based on the interval on the Likert Scale technique, these results imply that the application has been constructed and designed very well.
Sistem Identifikasi Titik Kritis Halal Menggunakan Algoritma Forward Chaining Hin, Alexander Moya; Kusnadi, Adhi; Overbeek, Marlinda Vasty; Prawira, Oqke; Khaeruzzaman, Yaman; Prasetya, Syarief Gerald
JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vol 8, No 1 (2023): Januari 2023
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/sst.v8i1.1285

Abstract

Halal products are obligatory to be used by people who are Muslim. When viewed in terms of the number of the Muslim population in the world and Indonesia, halal products have very potential economic opportunities. However, halal products have the risk of becoming non-halal if the accompanying process and storage do not follow halal rules. Therefore, it is necessary to identify the critical halal point, the point where the potential for such change occurs. So far, identification is made manually, of course there will be opportunities for identification errors to happen and it will take a relatively long time. To overcome these problems, identification can use a computer-based system. Forward chaining is an algorithm that is suitable for identifying halal points, because in SJH LPPOM MUI there is a decision tree for identifying halal critical points which is carried out in the same forward sequence as the forward chaining algorithm process flow. The development of a halal critical point identification system is carried out using the Software Development Life Cycle V-model method, the PHP programming language and the MySQL Database Management System. The system was successfully tested using Whitebox testing, including unit testing, integration testing, and overall system testing. Then testing using Blackbox testing techniques by comparing the results of identifying critical points using the system with the results of identifying critical points manually producing the same results. User satisfaction testing was also carried out using the End User Computing Satisfaction method and obtained an average satisfaction score of 86.53%Keywords – halal products, critical halal point, AI, forward chaining
Enhancing facial recognition accuracy through feature extractions and artificial neural networks Kusnadi, Adhi; Pane, Ivranza Zuhdi; Tobing, Fenina Adline Twince
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i2.pp1056-1066

Abstract

Facial recognition is a biometric system used to identify individuals through faces. Although this technology has many advantages, it still faces several challenges. One of the main challenges is that the level of accuracy has yet to reach its maximum potential. This research aims to improve facial recognition performance by applying the discrete cosine transform (DCT) and Gaussian mixture model (GMM), which are then trained with backward propagation of errors (backpropagation) and convolutional neural networks (CNN). The research results show low DCT and GMM feature extraction accuracy with backpropagation of 4.88%. However, the combination of DCT, GMM, and CNN feature extraction produces an accuracy of up to 98.2% and a training time of 360 seconds on the Olivetti Research Laboratory (ORL) dataset, an accuracy of 98.9% and a training time of 1210 seconds on the Yale dataset, and 100% accuracy and training time 1749 seconds on the Japanese female facial expression (JAFFE) dataset. This improvement is due to the combination of DCT, GMM, and CNN's ability to remove noise and study images accurately. This research is expected to significantly contribute to overcoming accuracy challenges and increasing the flexibility of facial recognition systems in various practical situations, as well as the potential to improve security and reliability in security and biometrics.
Implementation of Scrum Method in ERP-Based Employee Performance Evaluation System Chandra, Darren Denisson; Tobing, Fenina Adline Twince; Kusnadi, Adhi; Nainggolan, Rena; Hassolthine, Cian Ramadhona
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp201-209

Abstract

Human capital is a key factor in realizing an organization’s vision and mission. To ensure optimal performance, employee output must be evaluated consistently through a well-organized appraisal process. Although PT Kompas Media Nusantara has adopted such evaluations, they are still carried out using traditional methods, such as distributing physical documents. To address these inefficiencies, an ERP-based Employee Performance Evaluation System has been designed to streamline workflows, enhance accessibility, and support a more standardized and systematic assessment process. This system utilizes Key Performance Indicators (KPIs) aligned with individual job responsibilities to measure performance. The development process adopts the Scrum methodology, while system validation is carried out through Black Box Testing. The test results reveal that the system performs reliably, achieving a 100% accuracy rate in matching inputs and expected outputs. To assess user satisfaction, the End User Computing Satisfaction (EUCS) framework combined with a Likert scale was employed. The evaluation produced high satisfaction scores across various dimensions: content (89.12%), accuracy (87.02%), layout and design (88.07%), user-friendliness (89.12%), and timeliness (86.84%). These findings indicate strong user acceptance of the ERP-based system, reinforced by consistently positive user feedback regarding its effectiveness and ease of use
Co-Authors Adline Twice Tobing, Fenina Adline Twince Tobing, Fenina Augustino, Lorentzo Chandra, Darren Denisson Cian Ramadhona Hassolthine Dinarta, Farrel Endariahna Surbakti, Eunike Geneva, Erick Abraham Harjono, Marco Keegan Shandry Hin, Alexander Moya Irelynn, Maecyntha Ivan Wijaya, Aurelius Khaeruzzaman, Yaman Khaswar Syamsu Nainggolan, Rena Natapura, Septaria Dwi Nugraha, Achmad Ilyasa Overbeek, Marlinda Vasty Pane, Ivransa Zuhdi Pane, Ivranza Zuhdi Paskah, Richard Prasetya, Syarief Gerald Prawira, Oqke Rangga Winantyo, Rangga Rayhan Harsono, William Richard Andrew Sony Hartono Wijaya Syamsu , Khaswar Tisna Kusuma, Irene Tjoang, Stephen Tobing, Fenina Adline Twince Twince Tobing, Fenina Adline Twince, Fenina Adline Vasty Overbeek, Marlinda Wahyu Andrian, Bagas Yandra Arkeman Zuhdi Pane, Ivransa