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TIN: TERAPAN INFORMATIKA NUSANTARA
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27227987     DOI : -
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Jurnal TIN: TERAPAN INFORMATIKA NUSANTARA memuat tentang Kajian Bunga Rampai dari berbagai ide dan hasil penelitian para peneliti, mahasiswa, dan dosen yang berkompeten di bidangnya dari berbagai disiplin ilmu seperti: Komputer, Informatika, Industri, Elektro, Telekomunikasi, Kesehatan, Agama, Pertanian, Pembelajaran, Pendidikan, Teknologi Pendidikan, Ekonomi dan Bisnis, Manajemen, Akuntansi, dan Hukum
Arjuna Subject : Umum - Umum
Articles 756 Documents
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Sistem Pengambilan Keputusan Penerimaan Beasiswa KIP Menggunakan Algoritma Fuzzy Mamdani Ilham Arifin; RG. Guntur Alam
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10155

Abstract

The selection process for KIP Scholarship recipients at UINFAS Bengkulu is still conducted using conventional procedures, resulting in a relatively time-consuming process and potential subjectivity in decision-making. This study aims to develop a web-based Decision Support System using the Fuzzy Mamdani method to assist in selecting scholarship recipients in a more objective and systematic manner. The system was developed using the Waterfall model, which consists of requirements analysis, system design, implementation, testing, and maintenance. Eligibility assessment was based on four criteria: parents' income, number of family dependents, cumulative grade point average (GPA), and academic achievement, which were processed through fuzzification, IF–THEN rule-based inference, and centroid defuzzification. The main contribution of this study lies in the integration of the Fuzzy Mamdani computational model, which specifically combines financial criteria and student academic information to reduce ambiguity in scholarship selection parameters. The implementation results showed that the system produced a defuzzification value of 80 for the test data, indicating that the applicant was categorized as Eligible for the KIP Scholarship. Functional testing using the black-box testing method on seven test scenarios achieved a 100% success rate, indicating that all system functions operated as expected. The results demonstrate that the proposed system is capable of supporting the KIP Scholarship selection process in a more objective, transparent, efficient, and systematic manner compared with the previous manual process.
Analisis Probabilitas Aroma Sugar browning Kopi Robusta pada Proses Roasting Tradisional Menggunakan Naive Bayes Zuriah Anggun Nur Hikmah; Muhammad Imanullah
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10158

Abstract

The roasting process is one of the key stages in coffee processing because it greatly influences aroma and final flavor development. In Pasemah Air Keruh District, Robusta coffee is still roasted manually, and no clear guidelines exist for roasting conditions that consistently produce a sugar browning aroma. This study aimed to analyze the probability of sugar browning aroma formation in Robusta coffee and identify the dominant roasting category using the Naive Bayes algorithm. Data were collected from 150 Robusta coffee processors in Pasemah Air Keruh District. The observed variables included heat intensity, roasting duration, stirring, and cooling. Aroma classes were determined by baristas as the ground truth and categorized into Medium Roast, Medium Dark Roast, and Dark Roast. The data were cleaned, validated, converted into numerical form, and divided into 120 training and 30 testing samples. The results showed that the Naive Bayes algorithm achieved an accuracy of 76.67% and identified the relationship between roasting variables and sugar browning aroma. The Medium Dark Roast category had the highest probability of producing sugar browning aroma. This study provides an overview of the relationship between traditional roasting parameters and the probability of sugar browning aroma formation, which may serve as a reference for developing a more consistent coffee roasting process.
Pengembangan Kalkulator HPP Penentu Harga Jual Berbasis Generative AI Menggunakan Agile dan Cost-Plus Pricing Nuraeni Herlinawati; Ratnawati Ratnawati; Surtika Ayumida; Lukmanul Hakim
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10175

Abstract

Determining the cost of production is an important aspect of business because it directly affects the setting of product selling prices. Errors in production cost calculation often arise due to users’ limited understanding, inconsistent cost recording, and manual calculations that are prone to mistakes. The implementation of an information system provides an effective solution to reduce these risks. This study aims to design and develop a web-based production cost calculator application (HPP) that enables users to calculate production costs and determine product selling prices using the Cost-Plus Pricing method. The system development follows the Agile model, which includes planning, design, development, testing, and evaluation phases. The use of Artificial Intelligence (AI) in the development phase enables the creation of a more efficient and economical digital system with almost no additional cost. Generative AI is utilized during the development phase to assist in preparing the product backlog, creating the initial program code design, and accelerating the process of identifying and fixing errors through debugging. The results show that the developed HPP application can be used directly by the public without requiring software installation or additional database configuration, and can be accessed free of charge through the provided link. The contribution of this study is to provide a practical, economical, and easily accessible HPP calculator application that can be used by various types of businesses as a tool for determining selling prices based on production costs and target profit, while also demonstrating the use of Generative AI in accelerating the application development process efficiently. The black-box testing results show a success rate of 100%, indicating that all main application functions operate according to the specified requirements.
Pengembangan Multimedia Interaktif Berbasis Visual Tiga Dimensi untuk Pembelajaran Numerasi Anak Tunagrahita Ayu Kristin Natalia Sinaga; I Ketut Purnamawan; Putu Hendra Suputra
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10227

Abstract

This study aims to develop three-dimensional visual-based interactive multimedia to be used as a learning aid for numeracy among children with intellectual disabilities. The study was conducted at the Cahaya Impian Masa Depan (CIMD) Foundation. The research method employed the Multimedia Development Life Cycle (MDLC), which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. The developed multimedia is capable of displaying three-dimensional animal visualizations, interactive audio, numeracy quizzes, adn a reward system,which are designed to help students understand numerical concept more concretely. Testing was conducted through three evaluations: a content expert review, a media expert review, and a user responses evaluation using the Usability Metric for User Experince (UMUX) method. The study participants consisted of two teachers and 15 students with intellectual disabilities as users of the learning media. The content expert review yielded a validity percentage of 92,86%, classified as highly valid, and the media expert review yielded a validity percentage of 90%, classified as highly valid. Additionally, the user response evaluation yielded a UMUX score of 84,16% which falls into the Excellent category and Grade A. The research findings indicate that three-dimensional visual-based interactive multimedia possesses excellent usability, is easy to use, and is suitable as an alternative learning medium for numeracy education for children with intellectual disabilities. This study contributes by providing a learning medium designed based on the characteristics of children with intellectual disabilities and the learning needs identified at the Cahaya Impian Masa Depan (CIMD). The developed multimedia is expected to serve as a reference for the development of interactive learning media in inclusive education as well as special education institutions.
Strategi Influencer TikTok untuk Peningkatan Omzet UMKM Berbasis Etika Bisnis Islam Izzatin Nabila; Romzatul Widad
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10330

Abstract

Information technology developments have driven social media adoption as a marketing tool for MSMEs. TikTok has proven effective in increasing sales, but its practices need to be examined from Islamic business ethics which prohibit gharar and tadlis and require honesty (shiddiq) and transparency (tabligh). Research integrating TikTok Influencer marketing effectiveness with Islamic business ethics remains limited. This study aims to analyze the effect of TikTok Influencer promotions on MSME Risoles Endul Kraksaan's revenue and review it based on Islamic business ethics. A mixed methods explanatory sequential design was used with 20 respondents (Spearman correlation) and in-depth interviews. Results showed a correlation coefficient of 0.676 (p=0.001), indicating a significant positive relationship between TikTok Influencer promotions and increased revenue. Daily revenue increased from IDR 1-1.7 million to IDR 2.5-3.5 million, equivalent to a monthly increase from IDR 30-51 million to IDR 75-105 million. Promotional practices have fulfilled the principles of shiddiq, tabligh, and are free from gharar and tadlis. The contribution of this research is an integrative model of Influencer marketing effectiveness with Islamic business ethics and an applicable framework for Muslim MSMEs in effective and sharia-compliant digital marketing strategies. This study is limited to one MSME and one platform. TikTok Influencer promotions significantly affect MSME revenue and align with Islamic business ethics.
Rancang Bangun Sistem Monitoring Sentimen Berita Media Online Menggunakan IndoBERT Berbasis Web Alexander Rikky; Muhammad Iqbal; Mia Rosmiati
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10335

Abstract

Online news media has become a primary channel shaping public opinion toward government performance, making the ability to monitor news coverage a strategic necessity for institutions such as the Department of Communication and Information (Diskominfo) of West Kalimantan Province. However, the large volume of news coverage renders manual monitoring inefficient and prone to subjectivity. This study aims to design and build a web-based online news sentiment monitoring system named SentimenIQ, which integrates automatic news collection through RSS Feed, sentiment classification using the IndoBERT model, and presentation of analysis results within a single service flow. The system was developed using the Waterfall method with a microservice architecture separating the main Laravel application from the Python FastAPI inference service. Functional testing was conducted using the black box testing method, while classification performance was measured using accuracy, precision, recall, and F1-score derived from a confusion matrix on 120 labeled news articles. The functional testing results show that all system features operated according to requirement specifications, while the classification testing produced an accuracy of 89.17% with a weighted average F1-score of 89.13%. These results prove that the IndoBERT model can be integrated into a web-based operational system and relied upon to monitor news coverage in near real-time, thus serving as a reference for developing similar systems in other government institutions.
Pengembangan Aplikasi Berbasis Android untuk Sistem Irigasi pada Sistem Pertanian Cerdas Menggunakan Flutter Wahyu Nur Laeli Septi Ningrum; Kurniawan Dwi Irianto
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10336

Abstract

The agricultural sector plays a crucial role in supporting national food security. However, irrigation management that is still carried out manually often gives rise to various problems, such as water wastage, suboptimal watering, and the high time and labor demands on farmers in monitoring field conditions. Based on field observations, the watering process is still conducted manually, frequently resulting in delayed watering and uncontrolled water usage. The advancement of Internet of Things (IoT) technology provides opportunities to improve irrigation management efficiency through automated monitoring and control systems. This study aims to develop an Android-based smart irrigation system application for agriculture that can assist farmers in monitoring field conditions and controlling the irrigation system remotely. The development method employed is the Prototype model, which is a system development approach consisting of communication, quick planning, design, prototype construction, and testing phases. The application was developed using Flutter and Firebase Realtime Database and integrated with IoT devices to display soil moisture data, control irrigation pumps, display watering history, and provide real-time weather information. System testing was conducted using Black Box Testing to evaluate application functionality and the System Usability Scale (SUS) involving 10 respondents to assess the application's usability level. The Black Box Testing results demonstrated that all application functions operated with a 100% success rate, while the System Usability Scale (SUS) testing yielded an average score of 83, which falls into the Excellent category and Grade A. The findings indicate that the application was successfully developed and is capable of connecting with the IoT system in real-time, thereby facilitating more effective and efficient land monitoring and irrigation management. The contribution of this research is the development of an Android-based smart irrigation system application that integrates soil moisture monitoring, automatic and manual pump control, watering scheduling, notifications, watering history, and real-time weather information within a single platform connected to the Internet of Things (IoT).
Perbandingan Kinerja XGBoost dan Random Forest Menggunakan SMOTE pada Klasifikasi Diabetes Multi-Kelas Java Sika Maulana; Safitri Juanita
TIN: Terapan Informatika Nusantara Vol 7 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i1.10339

Abstract

Type 2 diabetes mellitus is a metabolic disorder that requires an early detection system to support accurate diagnosis identification. One of the major challenges in developing classification models based on clinical medical records is class imbalance, which may cause models to be biased toward the majority class, particularly in multiclass classification involving the Prediabetes class, which represents only 5.3% of the total data. Failure to accurately identify the Prediabetes class may have serious clinical consequences, as this stage still provides an opportunity for early intervention to prevent progression to Diabetes. This study compares the performance of Extreme Gradient Boosting (XGBoost) and Random Forest for multiclass diabetes classification (Normal, Prediabetes, and Diabetes) using clinical data obtained from Medical City Hospital and Al-Kindy Teaching Hospital, Iraq. A Split-First, Resample-Later procedure was employed to prevent data leakage, while Synthetic Minority Over-sampling Technique (SMOTE) was applied to balance the training data, and Grid Search was used for hyperparameter optimization across different train-test split ratios (60:40, 70:30, 80:20, and 90:10). This study provides a comprehensive evaluation of XGBoost and Random Forest on imbalanced multiclass clinical data by comparing their performance before and after SMOTE application across different train–test split ratios using the Split-First, Resample-Later procedure to prevent information leakage between the training and test set. The experimental results demonstrate that Random Forest achieved more stable performance than XGBoost across all evaluation scenarios, both before and after SMOTE application. Both models achieved their best performance with an 80:20 train–test split ratio, whereas SMOTE significantly improved the performance of XGBoost only under the 60:40 split ratio. Furthermore, feature importance analysis identified HbA1c, BMI, and AGE as the most influential clinical attributes for diabetes classification.
Pengembangan dan Evaluasi Usabilitas Gim Edukasi Bahasa Jawa Menggunakan Game Development Life Cycle M. Da’il Falah; Chanifah Indah Ratnasari
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10342

Abstract

Javanese is a regional language that should be introduced from elementary school because it represents cultural values, local identity, and Javanese manners. This study aims to design, develop, and evaluate the usability of an Android-based Javanese learning game using the Game Development Life Cycle (GDLC). The study was conducted at SDN Candirejo by involving the school principal as an interview informant and 15 students from grades III, IV, and V as respondents. The game content was prepared with reference to the Remen Basa Jawi 2013 Curriculum textbooks for grades I to VI and input from the school. The game applies the Drill and Practice method in an adventure puzzle format through area exploration, vocabulary collection, practice questions, a dictionary, inventory, and boss-stage evaluation. The content covers daily vocabulary, the use of Ngoko and Krama, identification of mixed-language sentences, and language selection based on the interlocutor. Alpha testing using Black Box Testing showed that all 16 scenarios worked as expected, with a success rate of 100%. Beta testing using the System Usability Scale (SUS) produced an average score of 72.17, which falls into the Acceptable category with a Good rating. These findings indicate that the game has good usability and can be considered an alternative medium for supporting Javanese language practice in elementary schools. This study contributes an interactive digital learning medium that integrates vocabulary practice, Ngoko-Krama use, and contextual language selection to support Javanese language preservation in elementary schools.
Perbandingan Metode Random Forest dengan Decision Tree pada Sistem Rekomendasi Olahraga Berdasarkan Karakteristik Kepribadian Galih Tri Ardiansyah; Titania Dwiandini
TIN: Terapan Informatika Nusantara Vol 7 No 2 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i2.10343

Abstract

Selecting sports that match individual characteristics is an important factor in increasing motivation, comfort, and consistency in performing physical activities. Each individual has different psychological characteristics, activity preferences, exercise intensity levels, and desired exercise goals. One approach that can be used to provide more personalized sports recommendations is by utilizing personality characteristics based on the Big Five Personality (OCEAN) model. This study aims to compare the performance of the Decision Tree and Random Forest algorithms in classifying sports categories based on personality characteristics, exercise intensity, social preferences, exercise location, and exercise goals. The novelty of this research lies in the implementation and comparative evaluation of these two algorithms in a Big Five Personality-based sports recommendation system, which has not been widely developed. The dataset used was obtained from sports experts, consisting of 603 records containing personality attributes and supporting factors related to sports activities. The dataset was divided using the train-test split method with a proportion of 67% training data and 33% testing data. The research stages included data validation, categorical attribute transformation using Ordinal Encoding, classification model development, and evaluation using accuracy, precision, recall, F1-score, and confusion matrix metrics. The results showed that the Random Forest algorithm achieved better performance than Decision Tree, with an accuracy of 82.91%, precision of 0.89, recall of 0.83, and F1-score of 0.81. Meanwhile, Decision Tree obtained an accuracy of 77.89%, precision of 0.65, recall of 0.78, and F1-score of 0.70. These results indicate that the ensemble approach in Random Forest is capable of capturing more complex data patterns and producing more accurate sports category classifications. This research is expected to serve as a foundation for developing a more adaptive and personalized sports recommendation system based on user characteristics.

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