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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Ilmu Komputer Jurnal Teknik ITS Jurnal Sains dan Seni ITS JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Mikrotek Jurnal Simantec Jurnal Teknobisnis Jurnas Nasional Teknologi dan Sistem Informasi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI SISFO SPIRIT Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII Sewagati
Arif Djunaidy
Departemen Sisitem Informasi Institut Teknologi Sepuluh Nopember
Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI

 1 
Pembuatan Model Pemeringkatan Ulasan Menggunakan Metode Random Forest Regression Nisrina Fadhilah Fano; Arif Djunaidy
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 8 No 2 (2021): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v8i2.777

Abstract

In the midst of rapid technological developments, the internet has changed people’s lifestyles, such as in terms of shopping. When shopping via the internet, one thing that needs to be considered is customer reviews. The problem arises when the number of existing customer reviews is very large, so the amount of information available is too much. To solve this problem, some online shopping platforms rank customer reviews from most helpful to least helpful. However, this system has several drawbacks, one of which is that it can be manipulated. So another way is needed to determine whether a review can help a potential customer decide to purchase a product. This study aims to create a review ranking model based on the review helpfulness from the regression review results. The method used in this study is the Random Forest Regression. There are six primary stages in this methodology, starting from collecting customer review data, preprocessing data, extracting aspects and analyzing aspect sentiment to determine the polarity of aspects, creating regression models and ranking, and analyzing the results. The results showed that the ranking model made based on the regression results had a superior performance compared to the model made based on the value of the helpfulness ratio alone. This is evidenced by the model being superior in testing the matching score which was carried out with an increase in performance of 6%.
Klasifikasi Status Kinerja Perusahaan Menggunakan Ensemble Learning dan SMOTE dengan Mempertimbangkan CGI Affindi Mario Bagaskara; Arif Djunaidy; Retno Aulia Vinarti
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 1 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i1.3521

Abstract

The global financial crisis that occurred in 2008 made most companies disturbed and unstable. In Indonesia, the impact of the global financial crisis can be felt continuously at the end of 2008. Indonesia's economic growth began from 2008-2009, the lowest percentage in 2009. This shows that the Indonesian economy is very important by the global financial crisis in 2009. Important for company to measure and know the status of the company's financial condition. A predictive model is needed to assist in analyzing the company's performance status for risk management. Therefore, building an effective Financial Distress Prediction (FDP) model has become an important research topic. This study aims to develop the FDP model by combining the ensemble learning method with the Synthetic Minority Oversampling Technique (SMOTE) method in state-owned companies in Indonesia listed on the Indonesia Stock Exchange. Then, in addition to using Financial Ratios (FR), this study also considers Corporate Governance Indicators (CGI). The experimental results of the FDP model development fell on the SMOTE-Stacking with an Accuracy result of 0.99 using FRs and CGIs data. This proves that the use of SMOTE and CGI methods is able to provide maximum prediction results. The result of this study is the FDP model which includes the company's performance status which is expected to increase the accuracy of the FDP model's performance.
Co-Authors Absari, Dhiani Achmad Holil Noor Ali Adhita Pratiwi Affindi Mario Bagaskara Ahmad Mukhlason Ahmad Mukhlason Ahmad Mukhlason Ahmad Muklason Akbar, Izzat Aulia Akhmad Tajuddin Tholaby MS Amalia Utamima Amalinda Jayanty Aulia Sidharta, Hanugra Barry Nuqoba, Barry Devie Rosa Anamisa Dewi Septina Br Pelawi Diah Risqiwati Dio Afriansyah Putra Pradana Divka, Princessa Sissy Faizal Mahananto Gede Aditra Pradnyana Ghinarosa Fitrinanda Hanif Mitsal Mahatta Hardhika Propitadewa Imamah h Jeremy Diaz Prasetyo Jihaan Harvi Habibah Kusumawardhani, Renny Pradina Lailatul Husniah Laily Rahmadhani Laura Wilhelmina Theresia M. Fiqri Ananda Mardiyanto Mardiyanto Meilani, Maulidiya Mochamad Zidan Aqila Kamil Muchammad Husni Muhamad Arief Hidayat Muhammad Ali Fikri Muhammad Arif Nuriman Muhammad Daffa Maulana Muhammad David Rahman Muhammad Hisyam Nabihah Hanun Atikah Nafitra, Hasna Dhiya Naufal Rafiawan Basara Nazriyah Deni Tsaniyah Nisa Dwi Angresti Nisrina Fadhilah Fano Nova Eka Budiyanta Nur Khofifah Nur Laila Nur Nindya Risnina Purnama, I Putu Adhitya Pratama Mangku Rahma Fauzia Rahmanisa, Fathia Rahmi, Mery Yulinda Raras Tyas Nurita Raras Tyasnurita Retno Aulia Vinarti Rico Bayu Wiranata Rifki Fahrial Zainal Rikasakomara, Edwin Riksakomara, Edwin Rully Soelaiman Septica Tiara Indah Permatasari Sidharta, Hanugra Aulia Sri Herawati SUGIYANTO Sugiyanto - Tony Dwi Susanto Tri Achmadi Untung B Santoso Wiga Ayu Puspaningrum Wiwik Anggraeni Wiwik Anggraeni Wiwik Anggraeni Yoga Yuniadi