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Benazir Imam Arif Muttaqin
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INDONESIA
Journal of Advanced in Information and Industrial Technology (JAIIT)
Published by Universitas Telkom
ISSN : 27161935     EISSN : 27161927     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Journal of Advances in Information and Industrial Technology publishes peer-reviewed papers on all fields of information and industrial technology.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 90 Documents
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Application of the Combination of SMART and TOPSIS Methods in the Decision Support System for the Selection of KIP-K Recipients in Students of the Islamic University of Balitar Alwan Fauzaan; Haris Yuana; Udkhiati Mawaddah
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.603

Abstract

This research aims to develop a decision support system that combines the Simple Multi-Attribute Rating Technique (SMART) method and the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) in the selection process for recipients of the Indonesia Smart Lecture Card (KIP-K) at the Islamic University of Balitar. The KIP-K program is an initiative of the Indonesian government to provide financial assistance to students with economic limitations but high academic potential, aiming to increase access to higher education for the underprivileged. However, in the implementation at the Islamic University of Balitar, there was an obstacle when several students who should have met the requirements and were entitled to receive the KIP-Lecture did not get it. The process without a structured calculation method and the calculation of data that is carried out individually are the main problems. This study collected and analyzed data on prospective KIP-K recipients with a decision support system developed. The research stages include data collection, normalization of criterion weights using the SMART method, and calculating priority scores using the TOPSIS method. The results of this system are measured using confusion matrix to evaluate the recommendation's accuracy. Using a confusion matrix shows that the resulting recommendation system has an accuracy rate of around 94.92%, precision of around 93.75%, recall of around 93.75%, and F1-score of 93.75, which is included in the excellent classification. This proves that combining methods can provide results based on the selection needs of KIP-K recipients at the Islamic University of Balitar.
Application of Item-Based Collaborative Filtering Method for Skincare Recommendation System Hidayat, Almaranda Aisyanissa; Joni Maulindar; Indah, Ratna Puspita
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.588

Abstract

Skincare refers to skin care products. These products have different purposes depending on the user's skin type. Over time, public awareness and interest in skincare will increase, leading to a rapid growth of skincare products. Therefore, an Item-Based Collaborative Filtering (CF) method is used to develop a skincare recommendation system. This method will provide personalised recommendations by leveraging the behaviour data of other users with similar preferences and characteristics. This study uses user ratings and preferences for skincare products as data. This data is then used to build a CF model, which will be analysed to calculate user similarity patterns using the cosine similarity matrix. The application of the CF method demonstrates its effectiveness in matching user preferences, resulting in the most relevant product recommendations. This system not only increases the accuracy of recommendations but also helps users find products that meet their skin care needs, as the error rate in the system is 0.245.
Comparison of Text Representation Methods for Sentiment Analysis Using Support Vector Machine Heri Suroyo; Pratama, Eric Juanda
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.610

Abstract

This study aims to analyse the sentiment of text from hashtags on TikTok regarding public services in Lampung Province, categorised into three groups: positive, negative, and neutral. Data is obtained from comments on TikTok. TikTok is a social media platform that offers users unique and engaging special effects. Recently, netizens were stirred by a viral TikTok video criticising Lampung's poor road conditions, titled 'Alasan Lampung Tidak Maju-maju' (Reasons Lampung is Not Progressing). This video sparked a range of comments from netizens, including supportive, critical, and neutral responses. The study employs the KDD (Knowledge Discovery in Database) method to extract insights from the existing database. The collected data will be manually labelled using the Support Vector Machine algorithm and Python programming software before being classified. The findings show that the classification model's accuracy differs based on the text representation technique. Of the three word-to-vector techniques, the Bag of Words method reached 48% accuracy, TF-IDF achieved 71%, and FastText achieved 50%. In summary, the sentiment classification model for public service content in Lampung Province on TikTok reveals that the Support Vector Machine combined with the TF-IDF method delivers the highest accuracy.
Diagnosis of Tobacco Plant Pests and Diseases Using the Forward Chaining Method Mauladi, Kemal Farouq; Laksono, Arief Budi; Marjudi, Suziyanti Binti
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.629

Abstract

Tobacco is a plantation commodity that is susceptible to pests and diseases, such as Phytophthora nicotianae (lanas disease), Myzus persicae (aphids), or Cercospora nicotianae (leaf spots). Lack of farmer knowledge in identifying early symptoms often leads to inappropriate handling and economic losses. This study aims to develop an expert system based on the Forward Chaining method to diagnose tobacco plant pests and diseases quickly and accurately. Symptom data are collected through field observations and literature and then represented as rule-based knowledge (for example, "IF leaves with yellow spots AND brown spots in the middle THEN Cercospora nicotianae"). The Forward Chaining method makes inferences by matching user input facts (symptoms) to existing rules to reach conclusions. The system was tested using 50 field cases with an accuracy of 85% compared to manual diagnosis by experts.
Framework for Digital Transformation in Industry 4.0: Insights Data Driven Analysis in the Indonesia Manufacture Sector Fesa Kristianto; Ulfia, Yessi Nasia; Galih Prakoso
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.630

Abstract

This study presents a structured grey literature review to develop a digital transformation framework for Industry 4.0 in Indonesia’s manufacturing sector. The analysis draws from national policy documents such as Making Indonesia 4.0, the Indonesia Industry 4.0 Readiness Index (INDI), and the Performance Accountability Report (LAKIP), complemented by qualitative insights from Focus Group Discussions with stakeholders from Digital Industry 4.0 Center (PIDI 4.0) and Badan Standardisasi dan Kebijakan Jasa Industri (BKSJI). Using grounded theory techniques—open, axial, and selective coding—relevant themes were extracted from these non-academic sources and organized into four perspectives: Adaptation, Technologies for Transformation, Key Success Factors, and Implementation Steps. These were operationalized into 25 dimensions and four detailed activity tables. A gap analysis with PIDI 4.0 partner industries was conducted to validate the framework and reveal implementation challenges such as fragmented strategies, limited technical skills, and a lack of performance monitoring. The review method integrates institutional evidence and stakeholder knowledge into a practical model for digital transformation, offering transferability to other developing countries. This research highlights the methodological value of grey literature in constructing context-sensitive frameworks for complex industrial innovation.
Design of a Website-Based Goods Inventory Information System at the Grocery Store Aldo Nicholas; Haris Yuana; Rahmat, Mohammad Faried
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.632

Abstract

This research aims to design and build a website-based inventory information system at the Dewi Grocery Store. The problem currently faced by stores is that capturing and managing inventory data is still manual, causing problems such as difficulty monitoring stock, recording errors and making old reports. The research method used is Agile Methods, consisting of requirements, design, implementation, verification and maintenance. System design using Laravel, Visual Studio Code, MySQL, XAMPP, Draw.io, and Whimsical. The research result is a website-based inventory information system application that can help the Dewi Grocery Store manage inventory data effectively and efficiently. The sales inventory system is functional and user-friendly, making it a valuable tool for Dewi Grocery Store to effectively manage sales inventory and provide accurate reports. The application has category management features, item data, sales, and report creation, as well as prediction features to help shop owners make decisions. The results of black box, expert, and user testing show the application is worthy of use with scores of 94%, 76%, and 83 %, respectively.
Prediction of Higher Education Student Academic Achievement Using Mamdani Fuzzy Logic Izzati, Afifah Nurul; Latif, Ummi Khaira; Sintiya, Endah Septa
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.682

Abstract

Student academic performance assessment is not only determined by exam scores, assignments, and attendance but also influenced by other factors such as attitude. However, evaluating this factor tends to be subjective. Additionally, the absence of an early prediction system to estimate students' academic performance can hinder timely study finish for at-risk students. The purpose of this study is to use the Mamdani fuzzy logic method to develop a system for predicting student academic performance. The input variables used in this system include attendance, assignments, midterm exams, final exams, and attitude. The system is modeled using fuzzy membership functions and assessed based on appropriate weightings. The inference process is conducted based on a set of fuzzy rules and is determined by the combination of input values. The next stage is defuzzification, which is the process of generating a final value used to classify academic performance into categories of "poor," "fair," or "good." This system is developed using the Python programming language with the scikit-fuzzy library and tested using the Mean Absolute Percentage Error (MAPE) method. The test results show an error rate of 1.35%. These results indicate that the Mamdani fuzzy logic approach is considered effective in assisting the assessment of student academic performance.
Spatial Autocorrelation Analysis of East Java Stunting Prevalence Cases in 2023 Trimono; Amri Muhaimin; Ekacitta, Puti Cresti; Ardiani, Ardia Eva
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.689

Abstract

Stunting is one of the chronic nutritional problems occur in East Java. In 2022, the percentage of stunting in East Java reached 19.2% and decreased to 17.7% in 2023. The less significant decrease occurred due to various factors, including malnutrition, poor sanitation, and environmental influences. This study will analyze the spatial influence on the prevalence of stunting in East Java, especially in 2023. The methods used include the Morans Index and the Local Indicator of Spatial Association (LISA). Spatial correlation analysis will help in determining the pattern of regional grouping based on stunting cases. This model works by testing whether the values of a variable at a location are related to the values of the same variable at neighboring locations, with the nature of the relationship being positive (clustering) or negative (dispersion). Using stunting prevalence data in 2023, the Moran Index = 0.3233 was obtained with a Zvalue = -1.0776. This value indicates that there is positive spatial autocorrelation, but is not significant enough. Then, through the Moran Scatterplot analysis, there are indications of regional grouping in four spatial quadrants. The results of the LISA analysis show that there are five cities/regencies included in the High-High cluster (Jember, Probolinggo City, Lumajang, Malang, and Probolinggo), one area in the Low-High cluster (Situbondo), and one area in the Low-Low cluster (Gresik). These findings indicate the existence of a spatial concentration of stunting problems that can be used as a basis for developing appropriate handling strategies by the provincial government based on regions.
The Model of Sharing Public IP Address Using Tunneling Protocol Tomi Defisa; Thomas Budiman; Sianipar, Anton Zulkarnain
Journal of Advances in Information and Industrial Technology Vol. 7 No. 1 (2025): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i1.691

Abstract

Digital Transformation cannot be separated from the support of Internet connections. The Global Internet Network only recognizes Public IP Address. The Internet Service Provider (ISP) will provide a Public IP Address to customers who subscribe to a business or Enterprise service. Companies with branch offices that subscribe to broadband internet services typically receive private IP addresses, which limits the availability of public IP addresses for systems or other purposes. This paper aims to utilize the Point-to-Point Tunneling Protocol (PPTP) and Ethernet over IP (EoIP) tunnel protocol features on MikroTik Routers for sharing a Public IP address, with a special focus on public IP Address version 4 (IPv4). Point-to-Point Tunneling Protocol (PPTP) is used to establish a Virtual Private Network (VPN) between the Head Office and Branch Office. Then, Ethernet over Internet Protocol (EoIP) is utilized to create a bridge network. Based on the test results, the Public IP Address was successfully detected on the internet network during bandwidth testing, and the route to the internet network was seen passing through the gateway from the Public IP address prefix of the Head Office. To demonstrate that Public IP Addresses can be used in Branch Offices. This model can be a solution for companies to share Public IP addresses between the head office and the Branch Office.
Prototype Development of a Real-Time Monitoring System Based on Android and Cloud Database for Textile Non-Thermal Plasma Treatment Fadil Abdullah; Putra, Valentinus Galih Vidia; Hamidah, Siti Nur; Hafizah Aprilia
Journal of Advances in Information and Industrial Technology Vol. 7 No. 2 (2025): Nov
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i2.686

Abstract

The textile modification process using plasma treatment requires accurate monitoring of gas species generated during operation; however, no system is currently available to measure these gas concentrations in real time. To address this gap, this study develops a plasma gas monitoring system for textile material modification, using experimental data obtained from laboratory tests conducted in 2024. The research employs a practical prototyping approach consisting of four stages: requirement identification, system design, prototype construction, and performance validation. The system is designed to continuously record plasma-generated gas concentrations and store the data in an internet-based database. The prototype consists of two main components: (1) a sensing unit built on an Arduino Uno microcontroller integrated with DHT-11 and MQ-131 sensors for measuring temperature, humidity, and ozone concentration, and (2) a data management platform using Google Spreadsheet connected to a mobile application to enable real-time monitoring and control. Evaluation results show that the monitoring tool achieved a Mean Absolute Error (MAE) of 0.6625 ppm, indicating that the system provides reasonably accurate measurements for initial validation. As this assessment is preliminary, future studies should employ a larger dataset to increase statistical robustness and further verify system performance. Overall, the findings contribute to the development of an accessible, Android-based plasma treatment monitoring system capable of supporting real-time monitoring in textile material modification applications.   

Page 8 of 9 | Total Record : 90

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