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All Journal Teknik dan Ilmu Komputer Prosiding Semnastek JOURNAL INFORMATICS, SCIENCE & TECHNOLOGY Infotekmesin Jurnal Pengabdian Teknologi, Ekonomi dan Humaniora Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Journal Technology Information and Data Analytic
Adam Arif Budiman
Universitas Darma Persada
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Other

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 1 
Perbandingan Akurasi Double Exponential Smoothing dan ARIMA dalam Memprediksi Penjualan di E-Commerce Nibans Cake Bobby Syakir, Raden Achmad; Budiman, Adam Arif
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 1 (2024): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i1.8

Abstract

Penelitian ini bertujuan untuk membandingkan keakuratan metode Autoregressive Integrated Moving Average (ARIMA) dan Double Exponential Smoothing pada peramalan penjualan kue di Toko Nibans Cake, sehingga toko dapat melakukan prediksi untuk periode selanjutnya dengan metode yang lebih akurat diantara kedua metode tersebut. Aplikasi penjualan menggunakan metode ARIMA dan Double Exponential Smoothing dapat digunakan untuk memprediksi jumlah penjualan di masa depan. Metode ARIMA lebih cocok digunakan untuk data yang memiliki pola musiman (seasonal) sedangkan metode Double Exponential Smoothing lebih cocok digunakan untuk data yang tidak memiliki pola musiman.
Implementasi Data Mining Analisa Pola Belanja Customer Dengan menggunakan FP-Growth pada Produk Fashion Agustin, Ririn; Budiman, Adam Arif
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 1 (2024): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i1.28

Abstract

This study applies data mining to analyze customer patterns and fashion product predictions. The FP-Growth method is used to identify frequently occurring itemset patterns,The dataset contains customer purchase history and fashion product attributes. The results of customer pattern analysis and fashion product predictions can help fashion companies in making strategic decisions. This study contributes to the use of data mining to understand customer preferences and improve business decisions for fashion companies. The use of datasets consisting of customer purchase history and fashion product attributes. First, using the FP-Growth algorithm, an analysis is carried out to identify frequently occurring itemset patterns in customer data. The results of the analysis are used to understand customer preferences and shopping habits.
Analisis Sentimen Kepuasan Pelanggan Parfum Scentplus dan Moris di Platform Tik Tok menggunakan Metode Regresi Logistik Alwi, Rivaldi; Budiman, Adam Arif
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 2 (2024): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i2.45

Abstract

Parfum Scentplus dan Moris, dua merek parfum lokal yang tengah meroket ketenaran nya melalui platform Tik Tok, menjadi fokus penelitian ini. Penelitian ini bertujuan untuk melakukan analisis sentimen terhadap kepuasan pelanggan terhadap kedua merek parfum ini. Metode Regresi Logistik digunakan sebagai alat utama untuk merinci dan mengeksplorasi sentimen yang terkandung dalam komentar-komentar pelanggan, Pengumpulan data dilakukan dengan memanfaatkan teknik Scraping untuk mengakses dan mengumpulkan komentar-komentar pelanggan dari platform Tik Tok, Data latih yang digunakan sebanyak 1000 data yang telah dilabel dengan masing-masing data sentimen positif 420, sentimen netral 149, dan sentimen negatif 431 untuk parfum moris dan data sentimen positif 456, sentimen netral 146, dan sentimen negatif 398 untuk parfum scentplus yang dilatih menggunakan algoritma regresi logistik, Pada penelitian ini menunjukan model untuk parfum Moris memiliki performa terbaik dengan akurasi sebesar 93%, presisi sebesar 93%, dan recall sebesar 93%. Sedangkan model untuk parfum Scentplus memiliki akurasi sebesar 91%, presisi sebesar 91%, dan recall sebesar 91%.
Steganography on MP3 Audio files to secure messages using the Least Significant Bit (LSB) and Advanced Encryption Standard (AES) methods Blanco, Steven; Budiman, Adam Arif
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025): Journal Technology Information and Data Analytic (TIFDA)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.80

Abstract

The E-budgeting file code delivery system is one of the right choices for a company to send and store large amounts of data neatly and properly. Currently, Bank XYZ has not yet implemented an Android-based file delivery and storage system, resulting in difficulties in locating previously sent files. To address this issue, Bank XYZ has developed an E-budgeting file code delivery system. This system is Android-based and operates using Android smartphones online. It is also designed to securely store files using AES (Advanced Encryption Standard) encryption and LSB (Least Significant Bit) steganography methods. The purpose of the E-budgeting file code delivery system is to facilitate the secure transmission of these codes to the relevant parties
Perbandingan Akurasi Double Exponential Smoothing dan ARIMA dalam Memprediksi Penjualan di E-Commerce Nibans Cake Raden Achmad Bobby Syakir; Adam Arif Budiman
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 1 (2024)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i1.8

Abstract

Penelitian ini bertujuan untuk membandingkan keakuratan metode Autoregressive Integrated Moving Average (ARIMA) dan Double Exponential Smoothing pada peramalan penjualan kue di Toko Nibans Cake, sehingga toko dapat melakukan prediksi untuk periode selanjutnya dengan metode yang lebih akurat diantara kedua metode tersebut. Aplikasi penjualan menggunakan metode ARIMA dan Double Exponential Smoothing dapat digunakan untuk memprediksi jumlah penjualan di masa depan. Metode ARIMA lebih cocok digunakan untuk data yang memiliki pola musiman (seasonal) sedangkan metode Double Exponential Smoothing lebih cocok digunakan untuk data yang tidak memiliki pola musiman.
Implementasi Data Mining Analisa Pola Belanja Customer Dengan menggunakan FP-Growth pada Produk Fashion Ririn Agustin; Adam Arif Budiman
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 1 (2024)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i1.28

Abstract

This study applies data mining to analyze customer patterns and fashion product predictions. The FP-Growth method is used to identify frequently occurring itemset patterns,The dataset contains customer purchase history and fashion product attributes. The results of customer pattern analysis and fashion product predictions can help fashion companies in making strategic decisions. This study contributes to the use of data mining to understand customer preferences and improve business decisions for fashion companies. The use of datasets consisting of customer purchase history and fashion product attributes. First, using the FP-Growth algorithm, an analysis is carried out to identify frequently occurring itemset patterns in customer data. The results of the analysis are used to understand customer preferences and shopping habits.
Development of Augmented Reality (AR) to Support Learning in The Introduction to Information Technology (PTI) Course: A Case Study at Darma Persada University Ferdi Maulana Akbar; Adam Arif Budiman
Journal TIFDA (Technology Information and Data Analytic) Vol 3 No 1 (2026): Journal Technology Information and Data Analytic
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v3i1.144

Abstract

Advances in Augmented Reality (AR) technology offer significant potential for enhancing learning in the Introduction to Information Technology (PTI) course at Darma Persada University, particularly regarding computer hardware concepts that are difficult to comprehend abstractly through conventional textbooks and slides. This study developed a marker-based AR application aligned with the Cisco IT Essentials curriculum, employing the Multimedia Development Life Cycle (MDLC) methodology. The application was built using Unity3D, Vuforia, Blender, and Visual Studio, presenting interactive 3D models, instructional videos, graded quizzes, volume controls, and marker guides distributed via Google Drive. Black-box testing confirmed successful operation on Android devices, and user testing involving 13 respondents demonstrated positive responses regarding ease of use and improved comprehension of the subject matter. The overall average rating was 3.63 out of 5. This application serves as an effective alternative interactive learning medium for the PTI course.
Analisis Sentimen Kepuasan Pelanggan Parfum Scentplus dan Moris di Platform Tik Tok menggunakan Metode Regresi Logistik Rivaldi Alwi; Adam Arif Budiman
Journal TIFDA (Technology Information and Data Analytic) Vol 1 No 2 (2024)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v1i2.45

Abstract

Parfum Scentplus dan Moris, dua merek parfum lokal yang tengah meroket ketenaran nya melalui platform Tik Tok, menjadi fokus penelitian ini. Penelitian ini bertujuan untuk melakukan analisis sentimen terhadap kepuasan pelanggan terhadap kedua merek parfum ini. Metode Regresi Logistik digunakan sebagai alat utama untuk merinci dan mengeksplorasi sentimen yang terkandung dalam komentar-komentar pelanggan, Pengumpulan data dilakukan dengan memanfaatkan teknik Scraping untuk mengakses dan mengumpulkan komentar-komentar pelanggan dari platform Tik Tok, Data latih yang digunakan sebanyak 1000 data yang telah dilabel dengan masing-masing data sentimen positif 420, sentimen netral 149, dan sentimen negatif 431 untuk parfum moris dan data sentimen positif 456, sentimen netral 146, dan sentimen negatif 398 untuk parfum scentplus yang dilatih menggunakan algoritma regresi logistik, Pada penelitian ini menunjukan model untuk parfum Moris memiliki performa terbaik dengan akurasi sebesar 93%, presisi sebesar 93%, dan recall sebesar 93%. Sedangkan model untuk parfum Scentplus memiliki akurasi sebesar 91%, presisi sebesar 91%, dan recall sebesar 91%.
Steganography on MP3 Audio files to secure messages using the Least Significant Bit (LSB) and Advanced Encryption Standard (AES) methods Steven Blanco; Adam Arif Budiman
Journal TIFDA (Technology Information and Data Analytic) Vol 2 No 1 (2025)
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v2i1.80

Abstract

The E-budgeting file code delivery system is one of the right choices for a company to send and store large amounts of data neatly and properly. Currently, Bank XYZ has not yet implemented an Android-based file delivery and storage system, resulting in difficulties in locating previously sent files. To address this issue, Bank XYZ has developed an E-budgeting file code delivery system. This system is Android-based and operates using Android smartphones online. It is also designed to securely store files using AES (Advanced Encryption Standard) encryption and LSB (Least Significant Bit) steganography methods. The purpose of the E-budgeting file code delivery system is to facilitate the secure transmission of these codes to the relevant parties
Co-Authors ADE SUPRIATNA Afri Yudha Agustin, Ririn Aji Setiawan Aji Setiawan Alwi, Rivaldi Andi Susilo Andi Susilo Andriansyah Zakaria Astuti, Eka Yuni Bagus Tri Mahardhika Blanco, Steven Bobby Syakir, Raden Achmad Chandra Pratama, Dian Dariyus, Asyari Dwikky Mardianto Eka Yuni Astuti Eka Yuni Astuty Eri Suherman Ferdi Maulana Ferdi Maulana Akbar Herianto Kevin Andreas Surbakti Linda Nur Afifah Nur Hasanah NUR HASANAH Raden Achmad Bobby Syakir Rimba Sianturi Ririn Agustin Rivaldi Alwi Setyaningsih, Timor Sianturi, Rimba Steven Blanco Suzuki Syofian Suzuki Syofian Timor Setiyaningsih Timor Setiyaningsih Timor Setyaningsih Tri Mahardhika, Bagus Widiksono, Susilo Widiksono, Susilo Yan Sofyan Andhana Saputra Zakaria, Andriansyah