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All Journal Jurnal Pseudocode Al Ishlah Jurnal Pendidikan Prosiding Seminar Nasional Teknoka Jurnal Sisfokom (Sistem Informasi dan Komputer) Journal Technology and Implementation Bussines Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi dan Terapan Bisnis Bulletin of Information Technology (BIT) Jurnal Teknologi dan Terapan Bisnis JURNAL TEKNIK INFORMATIKA DAN KOMPUTER
Isa Faqihuddin Hanif
Universitas Muhammadiyah Prof. Dr. HAMKA
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Other

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Perbandingan Algoritma NBC dan SVM dalam Analisis Sentimen Terhadap Dampak Kesehatan Rokok Elektrik Hani Rahmawati; Isa Faqihuddin Hanif
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2903

Abstract

There is no optimal method for accurately classifying public opinion, so an analytical approach is needed that is able to capture the nuances of public sentiment regarding the health impacts of e-cigarettes. This study examines public perception of the health impacts of electronic cigarettes using two classification algorithms: NBC and SVM. Data sourced from social media X (formerly Twitter) underwent stages of data cleaning, sentiment labeling, TF-IDF weighting, and data balancing through the SMOTE technique. Performance evaluation was conducted using four key metrics: accuracy, precision, recall, and f1-score. NBC achieved 80.5% accuracy with high recall despite low precision. In contrast, SVM recorded superior performance with 95.2% accuracy and more consistent balance between precision and recall. Therefore, the Support Vector Machine (SVM) algorithm is recommended as a more effective method for analyzing public sentiment regarding electronic cigarettes.Keywords: Electronic Cigarette; Entiment Analysis; Naïve Bayes Classifier; Support Vector Machine.AbstrakBelum adanya metode yang optimal untuk mengklasifikasikan opini publik secara akurat, sehingga diperlukan pendekatan analitik yang mampu menangkap nuansa sentimen masyarakat terhadap dampak kesehatan rokok elektrik. Studi ini mengkaji persepsi publik terhadap dampak kesehatan rokok elektrik dengan menerapkan dua algoritma klasifikasi: NBC dan SVM. Data yang bersumber dari media sosial X (eks Twitter) diproses melalui tahapan pembersihan data, pelabelan sentimen, pembobotan menggunakan TF-IDF, serta penyeimbangan data menggunakan teknik SMOTE. Evaluasi performa dilakukan menggunakan empat metrik utama: accuracy, precision, recall, dan f1-score. NBC memperoleh akurasi sebesar 80,5% dengan recall tinggi meskipun precision-nya rendah. Sebaliknya, SVM mencatat performa superior dengan akurasi 95,2% serta keseimbangan precision dan recall yang lebih konsisten. Oleh karena itu, algoritma Support Vector Machine (SVM) direkomendasikan sebagai metode yang lebih efektif dalam menganalisis sentimen publik terhadap rokok elektrik.Kata kunci: Analisis Sentimen; Rokok Elektrik; Naïve Bayes Classifier; Support Vector Machine.
Perceptions of Education and Non-Education Students towards the Campus Teaching Program: A Rasch Model Analysis Isnaini Handayani; Tri Wintolo Apoko; Arum Fatayan; Benny Hendriana; Irdalisa Irdalisa; Isa Faqihuddin Hanif
AL-ISHLAH: Jurnal Pendidikan Vol 18, No 1 (2026): MARCH 2026
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v18i1.7894

Abstract

The Teaching Campus Program, as part of the Merdeka Belajar–Kampus Merdeka (MBKM) initiative, aims to enhance students’ competencies through direct engagement in school environments. However, differences in academic backgrounds may influence how students perceive the program’s contribution to their learning outcomes. This study examines the perceptions of education and non-education students toward the program.This study employed a cross-sectional survey design involving 235 university students who completed the Teaching Campus Program (Batches 2–8) at a private university in Jakarta. Data were collected באמצעות closed- and open-ended questionnaires using a five-point Likert scale. The instrument’s validity and reliability were analyzed using the Rasch Model with Winsteps software, including item fit, person fit, and reliability indices. Descriptive statistics were used to interpret students’ perceptions.The findings indicate that students from education majors reported strong agreement that the program enhances pedagogical, professional, social, and personal competencies relevant to their future careers as teachers. Non-education students also expressed positive perceptions, particularly regarding the development of soft skills such as communication, collaboration, adaptability, and leadership, although the perceived relevance to their academic discipline was lower. Overall, most participants acknowledged the program’s contribution to skill development and professional readiness.These results suggest that the Teaching Campus Program is positively perceived by both groups, with varying degrees of relevance depending on academic background. The program supports competency development and experiential learning, although improvements in implementation and alignment with students’ fields of study are needed.
Perancangan Desain UI/UX Berbasis Scan Barcode Dengan Metode Design Thinking Untuk Pemesanan Makanan Ahmad Rayhaan Yusri; Isa Faqihuddin Hanif; Muhammad Daffa Al-farel; Muhammad Naufalrio Zaandami; Muhammad Yasin
Bulletin of Information Technology (BIT) Vol 5 No 2 (2024): Juni 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i2.1340

Abstract

For those who want an authentic taste of the typical Tegal cuisine, Warkop Bu Haji is the top choice theme. They can enjoy gourmet gourmets as well as traditional drinks such as coffee, tea, and fresh drinks with naturally produced fruits. Warkop Mother Haji wants to use new technology to improve service for operations and customer experience. Warp owners are looking for creative solutions in this digital age, when the demand for ease and speed of ordering food is rising. The focus of the research is a food ordering system that uses barcode scanning and the latest technology to improve the user experience. By using a mobile device to scan the barcode on the table, customers can easily order food. We work hard to ensure that our customers have a satisfactory and effective experience. Due to technological developments and changing consumer preferences, digital food ordering apps are becoming increasingly popular. This research is important because it allows customers to order food easily and quickly. User/User Interface (UI/UX) design and technical functionality are crucial. The research uses the Design thinking Method, which prioritizes users in innovative solutions. Prototype research involved 15 customer respondents and 1 partner respondent. The prototype design value for the customer was 86.6%, and the customer questionnaire score was 97.1%. The prototipe design score for the partner was 90%, and partner questionnary value was 91.6%. The research is expected to be beneficial to Warkop Mother Haji and industry. With a better customer experience, it is expected to improve the reputation and expand the customer base.
Co-Authors Ahmad Rayhaan Yusri Arum Fatayan Aulia Rachman Benny Hendriana Dede Ismail Ghifar Marhaban Sinambela Hani Rahmawati Hasan Dhiaulhaq Thalib Hermawan, Ahmad Rijal Hermawan Hisyam Humaidi Irdalisa Irfan Ricky Afandi Isnaini Handayani Muhammad Daffa Al-farel Muhammad Naufalrio Zaandami Muhammad Yasin Tri Wintolo Apoko Yusuf Handika