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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JITK (Jurnal Ilmu Pengetahuan dan Komputer) ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JURTEKSI Majalah Ilmiah Warta Dharmawangsa Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmu Komunikasi Network Media Syntax: Journal of Software Engineering, Computer Science and Information Technology Djtechno: Jurnal Teknologi Informasi DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Dharmawangsa: International Journal of the Social Sciences, Education and Humanitis Innovative: Journal Of Social Science Research Journal of Citizen Research and Development ABDI DALEM: Jurnal Pengabdian Kepada Masyarakat
J. Prayoga, J. Prayoga
Universitas Darmawangsa
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AUDIT SISTEM INFORMASI TERHADAP PERHITUNGAN WEIGHTED PRODUCT (WP) DI EXCEL Prayoga, J.; Gifary, Muhammad; Wiranata, Aldi; Maulana, Maulana; Nafriwan, Naufal; Nst, Rizqa Azahra; Kalista, Reva Nurul
Syntax : Journal of Software Engineering, Computer Science and Information Technology Vol 6, No 2 (2025): Desember 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/syntax.v6i2.8065

Abstract

 Penggunaan Microsoft Excel sebagai alat bantu perhitungan dalam Sistem Pendukung Keputusan (SPK) dengan metode Weighted Product (WP) semakin umum digunakan. Namun, perhitungan manual di Excel rentan terhadap kesalahan input, ketidaktepatan formula, dan inkonsistensi normalisasi bobot yang dapat menyebabkan hasil perankingan tidak valid. Penelitian ini bertujuan untuk melakukan audit sistem informasi terhadap file Excel yang digunakan dalam perhitungan metode WP guna memastikan integritas, akurasi, dan reliabilitas hasil.Audit dilakukan pada tiga komponen utama, yaitu input data, proses perhitungan (normalisasi bobot serta perhitungan nilai S dan V), dan output perankingan. Proses audit meliputi verifikasi kesesuaian rumus WP dengan teori, pengecekan konsistensi formula Excel, serta analisis kebenaran hasil perhitungan menggunakan data smartphone Xiaomi sebagai studi kasus.Hasil audit menunjukkan bahwa Excel dapat digunakan sebagai alat SPK sederhana apabila formula diterapkan secara benar dan konsisten sesuai aturan WP. Beberapa area kritis yang perlu diperhatikan meliputi penggunaan referensi absolut dan konsistensi formula antar baris. Penelitian ini menunjukkan bahwa audit sistem informasi berperan penting dalam menjaga integritas, akurasi, dan reliabilitas perhitungan WP di Excel serta memberikan rekomendasi untuk meminimalkan risiko kesalahan perhitungan. Kata Kunci: Audit Sistem Informasi, Weighted Product, Microsoft Excel, Verifikasi Formula, Sistem Pendukung Keputusan. ABSTRACTThe use of Microsoft Excel as a computational support tool in Decision Support Systems (DSS) applying the Weighted Product (WP) method has become increasingly common. However, manual calculations in Excel are prone to input errors, formula inaccuracies, and inconsistencies in weight normalization that may lead to invalid ranking results. This study aims to conduct an information system audit of an Excel file used to calculate the WP method to ensure the integrity, accuracy, and reliability of the calculations. The audit focuses on three main components: data input, calculation processes (weight normalization and S and V calculations), and ranking output. The audit includes verification of WP formulas against theoretical principles, consistency checks of Excel formulas, and validation of calculation results using Xiaomi smartphone data as a case study. The results show that Excel can function as a simple DSS tool if formulas are correctly and consistently applied according to WP rules. Critical issues identified include the use of absolute cell references and consistency of formulas across rows. This study demonstrates the role of information system audits in ensuring reliable WP calculations in Excel and provides recommendations to minimize calculation errors.Keywords: Information System Audit, Weighted Product, Microsoft Excel, Formula Verification, Decision Support System.
SENTIMENT CLASSIFICATION MODEL BASED ON COMPARATIVE STUDIES USING MACHINE LEARNING TECHNOLOGY PRAYOGA, J; Fajri, T. Irfan; Dristyan, Febri
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7105

Abstract

The development of social media has generated large amounts of text data, which is a valuable source for sentiment analysis. This study aims to conduct a comparative study of sentiment classification models on Indonesian-language YouTube comments, specifically comparing lexicon-based approaches, traditional machine learning models (Naive Bayes), and deep learning models (LSTM). Data was collected from YouTube videos themed around the youth generation and demographic bonuses, totaling 9,162 comments that underwent comprehensive text preprocessing. Model performance evaluation was conducted using accuracy, precision, recall, and F1-score metrics. The results show that the LSTM model outperforms Naive Bayes with an accuracy of 78.78% and an average F1-score of 0.79, compared to Naive Bayes, which only achieves an accuracy of 62.08% and an F1-score of 0.54. Although LSTM offers higher performance, the Naive Bayes model remains relevant due to its simplicity and efficiency. This study makes an important contribution to the selection of sentiment classification models for the Indonesian language and suggests the development of hybrid models and the use of contextual features for more optimal results. The LSTM model outperforms Naive Bayes with an accuracy of 82.15% (improved from 78.78% through enhanced regularization) and an average F1-score of 0.84. Comprehensive hyperparameter tuning via grid search and expanded manual annotation (40% of the dataset with κ=0.83) ensures robust model evaluation and reduces labeling bias. The study provides methodologically sound benchmarks for Indonesian sentiment analysis
Co-Authors Adam Haris Al Firah Al Firah Al Hafiz, Reyva Ryo Alfarezy, Salman Ananda Hadi Elyas Ananda Hadi Elyas Ananda, Keysha Nabila Anisma, Tiara Apridonal M, Yori Ardiata Ardiata Ari Nugroho Arini, Indah Aris Gunawan As’ari, Nabila Pramudita Ayu Nuriana br Ginting, Feby Ria Syahpitri Buyung Solihin Hasugian Desfriyanti, Diva Kusuma Dimas Fahreza Dores, Endri Dwi Tika Afriani Elyas, Ananda Hadi Emmy Syafitri Fahreza, Dimas Febri Dristyan Florida, Shinta Gifary, Muhammad Hafizh Abdillah Hutabarat, Emma Clodia Ibnu Rusydi Kalista, Reva Nurul Khairunisa, Dwi Latiffani, Chitra Lirinzha, Shifa Dwi Maharani, Dewi Mardiah Nasution Maulana Maulana, Maulana Muhammad Luthfi Nafriwan, Naufal Nasution, Mardiah Nst, Rizqa Azahra Nuriana, Ayu Permana, Ega Fitra Putri, Mashayu Aulia Rahma, Anisa Sri Ramadani, Cut Niaa Ramadani, Nisa Ridho, Mhd Fahrul Ritonga, Nurul Izza Putri Rizky Maulana Ruyani Ruyani Sabrina Aulia Rahmah Salamah Salamah Saragi, Mutiara Gladies Satria, Welnof Sa’adah, Nur Siddik, Mohd. Siregar, Khairul Sri Fitria Jayusman Sri Wahyuni Sri Wahyuni Sry Handayani Sry Handayani, Sry Syaiful Amri Tiara Anisma Ummi Aminah Hasibuan Virdyra Tasril Virdyra Tasril Wiranata, Aldi Yasir, Amru Yori Apridonal M Zaman, Syakban Zelvi Gustiana Zhafar, Raihan Zulham Zulham