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All Journal JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Progresif: Jurnal Ilmiah Komputer INFOKUM Journal of Computer Networks, Architecture and High Performance Computing Jurnal Abdimas Bina Bangsa Jurnal Informatika Teknologi dan Sains (Jinteks) Innovative: Journal Of Social Science Research JURNAL EKONOMI BISNIS DAN MANAJEMEN Jurnal Ekonomi Bisnis dan Manajemen INOVTEK Polbeng - Seri Informatika JRTI (Jurnal Riset Tindakan Indonesia)
Muhammad Ikhsan
Universitas Islam Negeri Sumatera Utara
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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PENGARUH HARGA, BRAND AWARENESS, DAN KUALITAS PRODUK TERHADAP MINAT BELI TEH GAMBIR (STUDI KASUS KABUPATEN PAKPAK BHARAT) Nurita Maha; Nurbaiti; Muhammad Ikhsan
JURNAL EKONOMI BISNIS DAN MANAJEMEN Vol. 2 No. 2 (2024): April : JURNAL EKONOMI BISNIS DAN MANAJEMEN
Publisher : CV. ALIM'SPUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/jise.v2i2.689

Abstract

This research aims to determine the influence of price, brand awareness and product quality on interest in buying Gambir tea (Pakpak Bharat Regency case study) either partially or simultaneously. The discussion in this research is related to marketing management. In this regard, the method used in this research is a quantitative method. The number of samples in this study was 97 people using the Chocran formula. The data collection techniques used are observation, documentation and questionnaires. The results of the partial research show that there is a negative and significant influence of price on interest in buying Gambir Tea with a calculated price t value of -8,530 > t table 1.666 with a significant value of 0.000 <0.05, so Ho1 is rejected and Ha1 is accepted. There is no influence of Brand Awareness on interest in buying Gambir Tea, with the calculated t value for the Brand Awareness variable 650 t table 1.666 with a significant value of 0.517 above 0.05, so Ho2 is accepted and Ha2 is rejected. There is a positive and significant influence of Product Quality on interest in buying Gambir Tea with a t value of 6.343 and an r table of 1.666, so Ho3 is rejected and Ha3 is accepted. So it can be concluded simultaneously that Price, Brand Awareness and Product Quality influence buying interest in Gambir Tea.
DETEKSI TINGKAT KECEMASAN MAHASISWA AKIBAT PENGGUNAAN APLIKASI TIKTOK MENGGUNAKAN METODE LOGIKA FUZZY MAMDANI Andhika Fisryansah Ahlief Putra; Muhammad Ikhsan
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 1 (2026): EDISI 27
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i1.7266

Abstract

Penggunaan aplikasi TikTok yang semakin intens di kalangan mahasiswa berpotensi menimbulkan dampak psikologis berupa kecemasan. Permasalahan dalam mengidentifikasi kecemasan terletak pada sifatnya yang subjektif dan tidak memiliki batas yang tegas, sehingga diperlukan pendekatan komputasional yang mampu merepresentasikan ketidakpastian. Penelitian ini bertujuan mendeteksi tingkat kecemasan mahasiswa akibat penggunaan TikTok menggunakan metode logika fuzzy Mamdani. Penelitian menggunakan pendekatan kuantitatif deskriptif dengan melibatkan 155 mahasiswa Program Studi Ilmu Komputer Universitas Islam Negeri Sumatera Utara. Data dikumpulkan melalui kuesioner intensitas penggunaan TikTok dan instrumen DASS-21 subskala anxiety. Proses analisis dilakukan melalui tahapan fuzzifikasi, inferensi, agregasi, dan defuzzifikasi metode centroid. Hasil penelitian menunjukkan bahwa mayoritas mahasiswa berada pada tingkat kecemasan sedang, dengan kecenderungan adanya kontribusi penggunaan TikTok terhadap peningkatan kecemasan pada level moderat. Evaluasi sistem menunjukkan bahwa metode fuzzy Mamdani mampu mengklasifikasikan tingkat kecemasan secara fleksibel dan konsisten dengan kondisi empiris responden. Dengan demikian, model yang dibangun dapat digunakan sebagai alat bantu skrining awal dalam mendeteksi kecemasan mahasiswa akibat penggunaan media sosial.
The Comparison Between The Apriori Algorithm And The FP-Growth Algorithm In Determining Frequent Pattern Farid Syah Zikri; Muhammad Ikhsan
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/s1yanj03

Abstract

This study aims to compare the efficiency and accuracy of the Apriori and FP-Growth algorithms in determining frequent patterns from sales transaction data. In addition to evaluating execution time and the quality of the generated association rules, the study also examines the algorithm's advantages on small to large-scale datasets. The data used were collected from G Coffee’s sales transactions during the period from September 1 to November 30, 2024. After undergoing preprocessing stages, both algorithms were tested using three dataset variations to identify common association patterns, such as the relationship between “Mineral 660ml” and “Kopi Susu Aren,” along with other product combinations with high confidence and significant lift values. The results show that FP-Growth had a faster execution time (0.3008) compared to Apriori (0.5833), without compromising the accuracy of the results. Although both algorithms generated identical association rules, FP-Growth was superior in computational efficiency due to its ability to avoid explicit candidate itemset generation. These findings offer strategic benefits for companies, particularly in enhancing product promotion through bundling, cross-selling, and product grouping based on consumer purchasing patterns. Results, a hybrid approach is recommended to combine the processing speed of FP growth with Apriori’s flexible parameter adjustment, enabling more optimal analysis of purchasing patterns in large and complex datasets.
Co-Authors Abdul Halim Hasugian Aidil Halim Lubis Andhika Fisryansah Ahlief Putra Andry Wiranda Hakiki Armansyah Armansyah As’Ary Sahlul Irsyad Ayu Amaliah Daffa Fadila Diah Ayu Anggraini Endah Avilia Chandra Farid Syah Zikri Gustina Permatasari Ritonga Lisma Autia Mhd Furqan Muhammad Chairul Azmi Muhammad Ridzki Hasibuan Nanda Qurrota Annisa Limbong Nurbaiti Nurita Maha Suhardi, Suhardi Supiyandi Supiyandi