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All Journal Jurnal Teknologi Terpadu Jurnal Informatika Terpadu Indonesian Journal Computer Science (ijcs) Malcom: Indonesian Journal of Machine Learning and Computer Science The Indonesian Journal of Computer Science DBESTI: Journal of Digital Business and Technology Innovation
Nabarian, Tifanny
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Library & Information Science

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Pemanfaatan Google Sheets dan Google Form untuk Layanan Administrasi Mahasiswa Menggunakan Konsep Electronic Service Quality Asqia, Misna; Nabarian , Tifanny
Jurnal Teknologi Terpadu Vol. 7 No. 1: Juli, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i1.339

Abstract

The COVID-19 pandemic has impacted higher education activities, including the student administration service process at the Nurul Fikri STT Terpadu BAAK. The problem faced is that the process of submitting letter requirements is still manual. As a result of this manual submission, students who need letters cannot come face-to-face to campus. Of course, this will impact BAAK's performance in serving the administrative needs of students. Because of this, this article then provides a solution in the form of using Google Sheets and Google Forms for the student administration submission process. Google Sheets and Google Forms are choices because they are cloud-based storage systems and can use by anyone without being limited by place and time. This study used electronic Service Quality (E-SQ) and User Acceptance Test (UAT) as the test and questionnaires as a data collection tool. The dimensions used in E-SQ are efficiency, fulfillment, and system availability. The study results obtained two categories, namely the results of processing student data and BAAK staff data. The percentage of student results is as follows. The efficiency dimension is 86%. Fulfillment is 82.5%, and the system available is 82.5%. The percentage of results of BAAK staff is as follows. Efficiency is 86.67%, fulfillment is 90%, and the system available is 100%.
Implementasi Metode Hibrid Fuzzy C-Means dan Fuzzy Swarm untuk Pengelompokkan Data Benang Perusahaan Tekstil Nabarian, Tifanny; Aris Ganiardi, Muhammad; Firsandaya Malik, Reza
Jurnal Teknologi Terpadu Vol 6 No 1: Juli, 2020
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v6i1.247

Abstract

Thread is one of the main raw materials in the production process of textile companies. The availability of thread consumption data in textile companies can be used to determine the pattern of thread consumption in a certain period. Data mining clustering method is one technique that can be used to form patterns from the data thread. In this study, hybrid Fuzzy C-Means (FCM) and Fuzzy Particle Swarm Optimization (FPSO) clustering algorithms are used, which are the combination of algorithms FCM and FPSO. This hybrid algorithm is able to overcome the weaknesses of the original algorithm, namely FCM. The purpose of this study is to test the performance of the FCM-FPSO hybrid method by implementing the clustering of the thread data from PT. Batam Bersatu Apparel (PT. BBA) into an application. The application implemented Unified Process for software engineering method. In this application, the performance of three methods was compared, those methods are FCM, FPSO and Hybrid FCM-FPSO. The result of the implementation is the lowest average objective function is 3441.00 achieved by the Hybrid FCM-FPSO algorithm, then followed by the FCM algorithm with value of 3540.33 and the highest is achieved by the FPSO algorithm with value of 4485.40. This result showed that the application was successfully proved that the FCM-FPSO Hybrid algorithm can produce the best thread clusters compared to the original method, FCM and FPSO.
Perancangan Prototype Aplikasi Olahraga FitenRun Menggunakan Metode User Centered Design Putri, Dea Amelia; Nabarian, Tifanny
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1113

Abstract

Sport is a simple way to improve physical fitness. However, there are several problems with these activities, such as a busy schedule of activities, confusion when starting to exercise due to a lack of information, and queues for using places or tools that interfere with comfort. The UI/UX design of a sports application called FitenRun employs User-Centered Design (UCD). In the UCD stage, there are four key processes: understanding the user's context, specifying user requirements, designing solutions, and evaluating them against those requirements. The application testing stage uses the System Usability Scale (SUS) and Single Ease Question (SEQ) methods. The results of the application design were identified based on user needs through the distribution of questionnaires, with 57 respondents participating. The features produced in the FitenRun application, namely FitRent, are presented as the main feature, with additional supporting features such as FitEvent, FitTrainer, FitChallenge, FitModule, and FitClass. The results of the tests carried out yielded an average score of 85, obtained using six-user testing for SUS, and the average SEQ score was 6.2. Indicating that the system falls into the excellent category, which suggests that the system is suitable for users and shows that potential users can interact easily with the application.
Pengembangan Backend Aplikasi Geoproperty dengan Golang di PT. Nerdvana Solusi Teknologi Ramdani, Muhammad Asnur; Nabarian, Tifanny; Maulana, Reza
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 1 (2025): Mei, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i1.1636

Abstract

This research discusses the backend design of the Golang-based GeoProperty application at PT Nerdvana Solusi Teknologi, which is designed to improve the property search experience with the integration of Geographic Information System (GIS) technology. This research focuses on developing the backend using the Agile Scrum method to ensure optimal functionality in managing spatial and property data. The backend supports key features such as interactive map-based property search, polygon input for search area boundaries, and Point of Interest (POI) visualization around the property. Testing was conducted using the blackbox testing method to evaluate API functionality. The results show that the backend system can meet user needs with reliable performance, provide accurate visualization of property locations, and comprehensive information that supports prospective buyers' decisions.
Analisis Faktor yang Memengaruhi Adopsi Aplikasi No Thanks dalam Mendukung Gerakan BDS terhadap Israel Nurmuhsina, St.; Nuranisah, Nuranisah; Syamila, Maryam Hasnaa'; Ramadhan, Muhammad Sayyid; Nabarian, Tifanny
Jurnal Informatika Terpadu Vol 11 No 1 (2025): Maret, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i1.1560

Abstract

This study analyzes the factors influencing the adoption of the No Thanks application in Indonesia to support the BDS movement. The research aims to understand how technology aids social movements, particularly in advocating Palestinian rights. Using the Technology Acceptance Model (TAM), this study employs qualitative and quantitative methods, including hypothesis testing, statistical analysis, validity, and reliability tests. A survey was conducted on 108 respondents, primarily female (60.2%), aged 17-25 years (98.1%), students (92.6%), with monthly expenses ranging from Rp 100,000 to Rp 300,000 (40.7%), and mostly residing in West Java (69.4%). The findings reveal significant relationships among research variables. Social Awareness, Social Norms, Value Compatibility, Technology Self-Efficacy, Information Availability, and application features influence Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), which subsequently affect Attitude (A) and Behavioral Intention (BI). The study concludes that intuitive interface design, accessible information, and social relevance are key to enhancing adoption and strengthening the role of technology in social movements.
Analisis Faktor Keberlanjutan Pemanfaatan Chatbot Akademik pada Perguruan Tinggi Nabarian, Tifanny; Ali Akbar
The Indonesian Journal of Computer Science Vol. 14 No. 5 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i5.5033

Abstract

This study examines the factors influencing the continued use of chatbot use as an academic information platform and identifies key factors contributing to its utilization. Data were collected through interviews and questionnaires, then analyse using the PLS-SEM method with Adanco software. The results show that System Quality has the strongest influence on Perceived Ease of Use (0.5326), which subsequently has a positive impact on Continued Use (0.4816). E-Service Quality also significantly affects User Satisfaction (0.3516). However, Information Quality and Perceived Usefulness show low influence on *User Satisfaction (0.2234) and Continued Use (0.1354), respectively. In terms of reliability, the constructs Continued Use (0.9147), E-Service Quality (0.9203), and Perceived Usefulness (0.8866) demonstrate strong measurement consistency, while System Quality (0.6363) requires improvement. The Q² analysis indicates that the model has good predictive relevance, with Continued Use (0.4349) emerging as the dominant variable
Perancangan Prototype Aplikasi Mobile Ridesolve untuk Memperbaiki Akses Transportasi Mahasiswa Menggunakan Metode Design Sprint Afifah, Raihana Cindy; Nabarian, Tifanny; Munir, Sirojul
DBESTI: Journal of Digital Business and Technology Innovation Vol 1 No 2 (2024): November, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v1i2.1370

Abstract

Students at Sekolah Tinggi Teknologi Terpadu Nurul Fikri (STT-NF) encounter challenges in accessing affordable and reliable transportation to and from campus, which complicates their search for convenient and cost-effective transport options. This study aims to develop a mobile application with an intuitive and user-friendly interface to enhance the overall transportation experience for students. Employing the Design Sprint methodology, the research follows a structured process involving understanding, diverging, deciding, prototyping, and validating phases. User requirements were gathered through surveys and interviews, and the prototype was created and tested using Figma. Usability testing utilized the System Usability Scale (SUS). The outcome of this study is RideSolve, a mobile app prototype featuring functionalities such as ride booking, driver selection, and ride history viewing. Usability testing revealed a high SUS score of 82, indicating positive user reception and effective fulfillment of their needs. Ultimately, the RideSolve prototype is anticipated to notably enhance transportation convenience for STT-NF students by offering a dependable and user-friendly solution.
Pengembangan Sistem Backend Rekomendasi Produk dengan Collaborative Filtering Berbasis Singular Value Decomposition Waluyo, Ahmad; Nabarian, Tifanny; Rosyidi, Lukman
DBESTI: Journal of Digital Business and Technology Innovation Vol 2 No 2 (2025): November, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/dbesti.v2i2.2003

Abstract

Recommendation systems have become a crucial component in enhancing user experience on e-commerce platforms, including PT Renos Marketplace Indonesia. However, the existing recommendation system was still random and unable to adapt to user preferences. This study aims to develop a product recommendation backend system based on Collaborative Filtering using the Singular Value Decomposition (SVD) algorithm. The methodology employed is Research and Development (R&D) with an Agile Scrum approach, along with performance evaluation using RMSE, MSE, and MAE metrics. The system was developed using FastAPI, PostgreSQL, and Python, and its functionality was tested using black-box testing methods. The implementation results show an RMSE of 0.1886, MSE of 0.0366, and MAE of 0.1242, indicating excellent prediction accuracy. Additionally, a user perception survey involving 11 internal respondents showed an average satisfaction score above 80%, with the highest score of 90.91% for the statement indicating that the system increases purchase likelihood. These findings demonstrate that the SVD algorithm is effective in generating relevant and personalized recommendations. The study concludes that the developed backend recommendation system successfully improves the efficiency and relevance of product recommendations and opens opportunities for further development through the integration of more complex user behavior data.
Penerapan Kerangka CRISP-DM dalam Evaluasi Performa Logistic Regression dan Decision Tree untuk Prediksi Kelulusan Mahasiswa Nabarian, Tifanny; Wahyuni, Imelda; Farisi, Salman El
Indonesian Journal Computer Science Vol. 5 No. 1 (2026): April 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijcs.v5i1.12502

Abstract

Ketepatan waktu kelulusan mahasiswa sering digunakan sebagai salah satu indikator dalam menilai efektivitas penyelenggaraan pendidikan di perguruan tinggi. Pemanfaatan data akademik melalui pendekatan machine learning dapat membantu mengidentifikasi mahasiswa yang berpotensi mengalami keterlambatan kelulusan secara lebih terukur. Penelitian ini bertujuan untuk membandingkan kinerja algoritma Logistic Regression dan Decision Tree dalam memprediksi kelulusan mahasiswa berdasarkan faktor akademik. Dataset yang digunakan terdiri dari 351 mahasiswa Program Studi Teknik Informatika di STT Terpadu Nurul Fikri, angkatan 2021, dengan variabel input Indeks Prestasi Kumulatif (IPK) serta Indeks Prestasi Semester (IPS) untuk setiap semester. Penelitian ini menggunakan metodologi CRISP-DM dengan pembagian data pelatihan serta pengujian 80:20. Evaluasi model dilakukan menggunakan confusion matrix dengan metrik accuracy, precision, recall, serta F1-score. Hasil pengujian menunjukkan bahwa Logistic Regression memperoleh accuracy 92,96%, precision 90,91%, recall 97,56%, dan F1-score 94,12%, sedangkan Decision Tree memperoleh accuracy 88,73%, precision 88,37%, recall 92,68%, serta F1-score 90,48%. Hasil tersebut menunjukkan bahwa Logistic Regression menunjukkan performa yang lebih optimal dan lebih sesuai dalam memodelkan hubungan antara variabel akademik dan ketepatan kelulusan mahasiswa. Sebagai kontribusi utama, penelitian ini mengintegrasikan model Logistic Regression terbaik ke dalam purwarupa sistem deteksi dini (early warning system) berbasis web menggunakan Streamlit. Pendekatan ini memberikan keunggulan praktis bagi pemangku kepentingan program studi untuk memitigasi risiko keterlambatan kelulusan secara real-time dan mendukung pengambilan keputusan intervensi akademik yang sepenuhnya digerakkan oleh data (data-drive decision making).
Analisis Perbandingan Kinerja IndoBERT dan TF-IDF dalam Mengklasifikasikan Sentimen EDOM Menggunakan Algoritma K-Nearest Neighbor: Comparative Analysis of IndoBERT and TF-IDF Performance in Classifying EDOM Sentiments Using the K-Nearest Neighbor Algorithm Nabarian, Tifanny; Nurhalizah, Siti; Farisi, Salman El
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 2 (2026): MALCOM April 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i2.2614

Abstract

Dalam konteks pendidikan tinggi, dosen berkontribusi besar terhadap peningkatan kualitas pembelajaran. Di Sekolah Tinggi Teknologi Terpadu Nurul Fikri (STT NF), Evaluasi Dosen oleh Mahasiswa (EDOM) dilaksanakan setiap akhir semester dan menghasilkan data komentar mahasiswa. Namun, analisis masih dilakukan secara manual sehingga kurang efisien dan berpotensi subjektif. Selain itu, belum terdapat kajian komparatif mengenai metode representasi yang sesuai untuk digunakan bersama algoritma K-Nearest Neighbor (KNN) khususnya pada data EDOM. Tujuan dari penelitian ini adalah menganalisis dan membandingkan kinerja IndoBERT dan TF-IDF dalam merepresentasikan teks untuk klasifikasi sentimen komentar EDOM menggunakan KNN. Metode penelitian mengacu pada tahapan CRISP-DM dengan dataset komentar EDOM tahun 2024. Hasil penelitian menunjukkan bahwa IndoBERT+KNN menghasilkan accuracy sebesar 0,903 serta menunjukkan nilai precision, recall, dan F1-score yang lebih seimbang antarkelas dibandingkan TF-IDF+KNN yang memperoleh accuracy sebesar 0,820 dengan performa metrik evaluasi yang cenderung kurang seimbang antarkelas. Hasil ini menunjukkan representasi kontekstual IndoBERT lebih efektif dalam menangani kompleksitas komentar EDOM dan algoritma KNN yang berbasis jarak dibandingkan dengan pendekatan berbasis frekuensi kata pada TF-IDF. Berdasarkan temuan tersebut, penelitian ini memberikan pemilihan metode representasi teks yang lebih optimal untuk pengembangan analisis sentimen secara lebih objektif dan efisien
Co-Authors Afifah, Raihana Cindy Ali Akbar Aris Ganiardi, Muhammad Asqia, Misna Firsandaya Malik, Reza Imelda Wahyuni, Imelda Lukman Rosyidi Nuranisah, Nuranisah Nurhalizah, Siti Nurmuhsina, St. Putri, Dea Amelia Ramadhan, Muhammad Sayyid Ramdani, Muhammad Asnur Reza Maulana Salman Al Farisi Sirojul Munir Syamila, Maryam Hasnaa' Waluyo, Ahmad