Article Per Year (5 Year)
p-Index From 2021 - 2026
3.891
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Computing, Engineering, and Design Journal of Applied Data Sciences Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Community Services: Sustainability and Empowerment CSRID Journal of Intelligent Systems for Community Development (JISCoDe)
Teddy Mantoro
Unknown Affiliation
Arts Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

Published : 29 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 29 Documents
Search

 1   2   3 
Enhancing Coffee Marketing Strategies through Multi-Criteria Decision-Making Andryana, Septi; Wahyuddin, Mohammad Iwan; Rahman, Ben; Putra, Abdul Rahman Wijaya; Mantoro, Teddy
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3282

Abstract

Coffee is a globally preferred beverage, and Indonesia, as a major supplier, provides a wide variety of high-quality coffee varieties with unique characteristics from each region. East Manggarai, East Nusa Tenggara, Indonesia, produces Colol coffee, a high-quality variety with unexplored market potential. The marketing of Colol coffee faces significant challenges, including limited accessibility, lack of market information, and inadequate logistics infrastructure. A comprehensive marketing strategy necessitates the consideration of numerous criteria, which generate a range of alternative decisions to identify the marketing area. This study proposes a framework to optimize the marketing strategy of Colol coffee using the MCDM (Multi-Criteria Decision-making) approach, which integrates AHP, SMARTER, and TOPSIS methods. This framework is applied to rank marketing areas in 38 provinces in Indonesia based on five criteria, namely, accessibility, market potential, logistics, environmental conditions, and safety. The results show that the MCDM method can increase the effectiveness of marketing strategies. The top three alternative coffee marketing regions are Papua, East Kalimantan, and South Papua, with eigenvalues of 0.0569, 0.0424, and 0.0421. With incomplete data, in some marketing areas, it is a challenge to integrate multiple MCDM methods to have a better ranking that represents the real world of marketing strategy. This study supports the enhancement of the digital economy in the agricultural sector. It provides a meaningful understanding of the application of MCDM in marketing agricultural products, with far-reaching implications for marketing strategies in similar sectors.
Sentiment Analysis for the Brazilian Anesthesiologist Using Multi-Layer Perceptron Classifier and Random Forest Methods Asian, Jelita; Dholah Rosita, Moneyta; Mantoro, Teddy
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.900

Abstract

Sexual harassment is defined as giving sexual attention both verbally, either in speech or writing, and physically to victims who are predominantly women, On July 13, 2022, there was a tweet featuring a video of sexual harassment that made it trend in various countries. The video irritated Twitter users and made various comments resulting in various sentiments that can be analyzed using sentiment analysis. The purpose of this study is to see what the public thinks about the sexual harassment case of Brazilian anesthesiologist. Besides the sentiment analysis, another aim of this study is to see how objective are those sentiments based on their polarity. This study uses a comparison of two methods in sentiment analysis, namely Multi-Layer Perceptron Classifier and Random Forest, and labeling automatically using TextBlob.  This results in 94.44% accuracy, 94.44% precision, 92% recall and 93% f1_score. For MLP Classifier and accuracy 96.42%, precision 94.44%, recall 96.66% and f1_score 95.56% for Random Forest. Sentiment polarity score from the TextBlob is -0.5 and subjectivity is 0.4 which indicates that most statements are negative and subjective score is 0.4, which means those sentiments are subjective in nature.
Social Network Analysis: Identification of Communication and Information Dissemination (Case Study of Holywings) Aditiawarman, Umar; Lumbia, Mega; Mantoro, Teddy; Ibrahim, Adamu Abubakar
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.911

Abstract

Social media especially Twitter has been used by corporation or organization as an effective tool to interact and communicate with the consumers. Holywings is one of the popular restaurants in Indonesia that use social media as a tool to promote and disseminate information regarding their products and services. However, one of their promotional items has gone viral and invited public protests which turned into a trending topic on Twitter for a couple of weeks. Holywings allegedly improperly promoted their products by using the most honorable names, “Muhammad” and “Maria”. Social network analysis of Twitter data is conducted to identify and examine information circulating among the users, which leads to wider public attention and law enforcement. In this study, we focused on the conversation about Holywings on Twitter from 24 June to 31 July 2022. The analysis was carried out using Python to retrieve data and Gephi software to visualize the interactions and the intensity of the network group in viewing the spread of information. The findings reveal the centrality account that caused the news to go viral are the CNN Indonesia (@CNNIndonesia) news media account and Haris Pertama (@knpiharis), with a centrality of 0.161 and 0.282, respectively. There are also 121 groups involved in the conversation with modularity of 0.821.
ENHANCING COFFEE PRODUCTION FACTOR ASSESSMENT USING LINEAR REGRESSION AND AHP FOR RELIABLE WEIGHT CONSISTENCY Aris Gunaryati; Teddy Mantoro; Septi Andryana; Benrahman; Mohammad Iwan Wahyuddin
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.6788

Abstract

The agricultural sector, particularly coffee production, plays a crucial role in Indonesia’s economy as both a domestic commodity and an export product. However, efforts to optimize coffee production are often constrained by traditional Multi-Criteria Decision-Making (MCDM) methods that rely heavily on subjective judgments, leading to potential inconsistencies—especially in the presence of multicollinearity among variables. This study addresses that challenge by proposing a data-driven and consistent weighting method that integrates Multiple Linear Regression (MLR) with the Analytic Hierarchy Process (AHP). Regression coefficients derived from MLR—based on variables such as the area of immature (-0.2419), mature (0.8357), and damaged (0.5119) coffee plantations—are normalized and incorporated into the AHP pairwise comparison matrix. The resulting Consistency Ratio (CR) values are all below 0.1, indicating high internal consistency and statistical reliability of the derived weights. This integrated approach offers an objective and systematic foundation for MCDM in coffee production analysis, enhances the accuracy of agricultural planning, and supports evidence-based policymaking, while also providing a replicable model for addressing similar challenges in other sectors
Evading Antivirus Software Detection Using Python and PowerShell Obfuscation Framework Umar Aditiawarman; Alfian Dody; Teddy Mantoro; Haris Al Qodri Maarif; Anggy Pradiftha
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 3 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i3.3088

Abstract

Avoiding antivirus detection in penetration testing activities is tricky. The simplest, most effective, and most efficient way is to disguise malicious code. However, the obfuscation process will also be very complex and time-consuming if done manually. To solve this problem, many tools or frameworks on the internet can automate the obfuscation process, but how effective are obfuscation tools to avoid antivirus detection are. This study aimed to provide an overview of the effectiveness of the obfus- cation framework in avoiding antivirus detection. This study used experimental design to test and determine the effectiveness of the payload obfuscation process. The first step was generating Python and PowerShell payloads, followed by the obfuscation process. The results showed that by using the right method of obfuscation, malware could become completely undetectable. The automatic obfus- cation process also did not deteriorate the malware’s function. It was proven that the malware could run and open a connection on the server. These findings required more Python obfuscator techniques to determine the effectiveness of the obfuscated payload on the target machines using both static and dynamic analysis
Detecting Hidden Illegal Online Gambling on .go.id Domains Using Web Scraping Algorithms Muchlis Nurseno; Umar Aditiawarman; Haris Al Qodri Maarif; Teddy Mantoro
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3824

Abstract

The profitable gambling business has encouraged operators to promote online gambling using black hat SEO by targeting official sites such as government sites. Operators have used various techniques to prevent search engines from distinguishing between genuine and illegal content. This research aims to determine whether websites with the go.id domain have been compromised with hidden URLs affiliated with online gambling sites. The method used in this research is an experiment using a FOFA.info dataset containing a complete list of 450,000 .go.id domains. A web scraping algorithm developed in Python was used to identify potentially compromised websites from the targeted listby analyzing gambling-related keywords in local languages, such as ’slot,’ ’judi,’ ’gacor,’ and ’togel'. The results showed that 958 of the 1,482 suspected.go.id sites had been compromised with an accuracy rate of 99.1%. This implies that security gaps have been exploited by illegal online gambling sites, posing a reputational risk to the government. Lastly, the scrapping algorithm tool developed in this research can detect illegal online gambling hidden in domains such as .ac.id, .or.id, .sch.id, and help authorities take necessary action.
Crime index based on text mining on social media using multi classifier neural-net algorithm Teddy Mantoro; Muhammad Anton Permana; Media Anugerah Ayu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 3: June 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i3.23321

Abstract

Everyday criminal issues appear on social media, even some crime news is often disturbing to the public but it gives a warning to the public to remain careful and alert to the surrounding environment. However, following large amounts of crime information on social media is not effective, especially for busy people. Therefore, there is a need to efficiently and effectively summarize information in a way that is meaningful and easy to see, attracts people’s attention, and can be used by law enforcement officials. The purpose of this study is to present the index crime based on social media by looking for patterns of crime. This study proposes the projected index crime based on crime trends by using text mining to classify tweet texts and post contents into 10 crime classes. The classification method uses the neural-net multi classifier algorithm which has several classifiers namely logistic regression, naïve bayes, support vector machine (SVM), and decision tree in parallel. In this approach, the classifier that provides the best accuracy will be the winning classifier and will be used in the next learning process. In this experiment, in using the multi classifier neural-net, the logistics regression classifier often provides the best accuracy.
A hierarchical scholar expertise information system based on publication profiles and research records: a case in Universitas Diponegoro Eko Didik Widianto; Hadiyanto Hadiyanto; Teddy Mantoro; Raka Sindu Wardoyo; Muhamad Irham Maulana
Indonesian Journal of Electrical Engineering and Computer Science Vol 43, No 1: July 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v43.i1.pp250-258

Abstract

One factor that boosts the reputation of higher education institutions (HEIs) in gaining competitive advantage is the research productivity of their scholars, including at Diponegoro University (Undip). However, existing studies focus on metrics and their measurement but lack discussion of systems for leveraging these metrics to promote these scholars’ expertise. This study proposes a scholars’ expertise information system at Undip based on their publications and research track records to bridge information between the campus and outside parties, namely industry, government, and society. It provides expertise searching and browsing facilities in Dewey’s hierarchy of subjects and the institutional structure hierarchy. Scholar publications and research data are retrieved using the science and technology index application program interface (SINTA API). The collected data included lecturer profiles, study programs, SINTA subjects, articles, research, community service, intellectual property rights (IPR), and books. It has been fully deployed and adopted online, presenting the expertise of Undip scholars based on their publications and research records. The finding shows that all pages perform well, with an average GTmetrix B grade and a performance score of 91%, a structure score of 88%, and a 1.8s loading time. With all the functionalities and performances of the system, this study contributes to developing an information system model to promote the expertise of university scholars, primarily based on their publications and research.
Affordable Housing, Urban Analytics, and Inclusive Infrastructure Planning Herlawati Herlawati; rahmadya trias handayanto; Teddy Mantoro; Media Anugerah Ayu; Nitin Kumar Tripathi; Pramod Kumar
Journal of Intelligent Systems for Community Development Vol. 1 No. 1 (2026): 2026: JISCoDe Volume 1 Issue 1 Year 2026
Publisher : Indonesian Artificial Neural Network Society

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Affordable housing, particularly in developing countries such as Indonesia, has become a major government priority through the Ministry of Housing and Residential Areas of the Republic of Indonesia. Adequate housing does not function in isolation but must be supported by complementary infrastructure such as commercial areas, roads, transportation networks, healthcare facilities, and other public service centers. Housing development should therefore be inclusive by adopting a mixed-use development approach and avoiding overly rigid zoning systems, since each land-use category is interconnected with and dependent on other land-use types. To address this challenge, urban analytics is required. This study applies land-use optimization based on four key objectives: compactness, compatibility, dependency, and suitability. By implementing clustering techniques, several potential central nodes were identified as suitable hubs for specific land-use types, including commercial centers, vertical residential districts, and industrial zones.
Co-Authors Abdul Rahman Wijaya Putra Abdullah Alkalbani Achmad Farid Wadjdi Adamu Abubakar Ibrahim Adi Putra Andriyandi Agung Nugroho Akeem Olowolayemo Alfian Dody Andri Zakariya Andri Zakariya Anggy Pradiftha Anggy Pradiftha Junfithrana Aris Gunaryati Aris Gunaryati Aris Gunaryati, Aris Arisantoso Arisantoso Ben Rahman Benrahman Dimas Erlangga Edi Irawan Effendi, Nicholas Lasca Eko Didik Widianto H Hadiyanto Hamdan Sugilar Haris Al Qodri Maarif Haris Al Qodri Maarif Herlawati Herlawati I Made Alan Priyatna Ibrahim, Adamu Abubakar Jelita Asean Jelita Asian Lumbia, Mega Lutfil Khakim Maylawati, Dian Sa'adillah Media A. Ayu Media Anugerah Ayu, Media Anugerah Mega Lumbia Mohammad Iwan Wahyuddin Moneyta Dholah Rosita Muchlis Nurseno Muhamad Irham Maulana Muhamad Rausyan Fikri Muhammad Agni Catur Bhakti Muhammad Ali Ramdhani Muhammad Anton Permana Nitin Kumar Tripathi Pramod Kumar Putra, Abdul Rahman Wijaya Raffliansyah, Alfarizky Esah rahmadya trias handayanto Rahman, Ben Raka Sindu Wardoyo Septi Andryana Septya Egho Pratama Sony Surya Wijaya Tarigan, William Hazkel Umar Aditiawarman Wahyuddin, Mohammad Iwan Wahyudin Darmalaksana Wandy Wandy