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All Journal IKRA-ITH Informatika : Jurnal Komputer dan Informatika IKRA-ITH Teknologi Jurnal Sains dan Teknologi JMM (Jurnal Masyarakat Mandiri) Sebatik Jurnal Sisfokom (Sistem Informasi dan Komputer) IKRA-ITH ABDIMAS Jurnal Mnemonic Unri Conference Series: Community Engagement Buletin Poltanesa Kresna: Jurnal Riset dan Pengabdian Masyarakat IJCOSIN : Indonesian Journal of Community Service and Innovation Jurnal Karya Abdi Masyarakat Jurnal Pengabdian Masyarakat Tekno Proceeding of The International Conference on Management, Entrepreneurship, and Business
Windihastuty, Wiwin
Universitas Budi Luhur
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Journal : Jurnal Sisfokom (Sistem Informasi dan Komputer)

 1 
Penentuan Hoax pada Artikel Politik Berbahasa Indonesia di Sosial Media dengan Similarity Jaccard dan Algoritma Stemming Goenawan Brotosaputro; Wiwin Windihastuty; Rezza Anugrah Mutiarawan
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 11, No 1 (2022): MARET
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v11i1.1358

Abstract

Pesatnya perkembangan  teknologi di era globalisasi saat ini membawa pengaruh besar dalam proses pencarian informasi. Kita dapat melihat pertumbuhan yang sangat besar pada volume berita online yang tersedia pada jaringan internet, maupun pada jaringan lainnya. Salah satunya adalah sosial media yang memilik banyak informasi yang mengenai artikel-artikel berita atau artikel-artikel informasi lainnya. Berita merupakan sumber informasi mengenai kejadian terkini yang mana dapat ditemukan pada internet dan media sosial. Saat ini berita-berita yang disebarkan terutama berita mengenai politik yang dapat mengakibatkan salah penafsiran karena berita tersebut belum tentu benar atau salah sehingga dibutuhkan pengklasifikasian artikel politik apakah termasuk dalam kategori hoax atau non hoax. Hoax adalah berita kebohongan yang disebar untuk memperoleh kepercayaan agar masyarakat akan merasa yakin bahwa konten tersebut benar. Dampak lain dari hoax dapat merugikan emosi hingga finansial masyarakat. Proses klasifikasi hoax menggunakan tahap preprossessing yang terdiri dari tokenization dan stemming. Dilanjutkan dengan proses pembobotan kata dan jaccard similarity hingga proses klasifkasi dengan menggunakan metode Vector Space Model (VSM). Hasil evaluasi pada penelitian ini menggunakan confusion matrix, dimana diperoleh hasil precision sebesar 0,92 recall sebesar 0,80 dan akurasi didapatkan sebesar 87 %.
Prediction of Claim Fund Reserves in Insurance Companies Using the ARIMA Method Brotosaputro, Goenawan; Japriadi, Yohanes Setiawan; Windihastuty, Wiwin; Ahsani, Rivai
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Insurance is a financial protection contract between a customer and an insurance company which is stated in the form of an insurance policy. Prediction of insurance claim reserve funds is necessary because the claim amount varies and the claim time can be the same. If at any time there is a claim that is so large that it exceeds the available claim reserve fund plus the claim occurs at the same time, it can cause the company to fail to pay the claim. This will certainly make the company's conduct decline, customer trust will be lost, and can cause the company to go bankrupt. The problem can be solved if the insurance company has sufficient claim fund reserves. Claim fund reserves are an important issue in insurance companies. This study aims to predict the claim fund reserves in insurance companies to anticipate varying claim amounts. Historical analysis of the value of claims with the ARIMA model approach is used to predict future claim values. We use claim value data that has been scaled in millions. 2020 to 2022 as training data and 2023 as test data. The Root Mean Square Error (RMSE) metric obtained is IDR 25,780.71; Mean Absolute Deviation (MAD) of IDR 14,421.89, and Mean Absolute Percentage Error (MAPE) of IDR 5,967.27; while the total actual claim value in 2023 is IDR 161,700.51 and the total predicted claim value is IDR 166,227.36; which means that an accuracy of 97% is obtained. The result of claim prediction value in one periodic year can give a favor to the management to make a decision, how much the claim funds should be prepared.
Prediction of Claim Fund Reserves in Insurance Companies Using the ARIMA Method Brotosaputro, Goenawan; Japriadi, Yohanes Setiawan; Windihastuty, Wiwin; Ahsani, Rivai
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i1.2331

Abstract

Insurance is a financial protection contract between a customer and an insurance company which is stated in the form of an insurance policy. Prediction of insurance claim reserve funds is necessary because the claim amount varies and the claim time can be the same. If at any time there is a claim that is so large that it exceeds the available claim reserve fund plus the claim occurs at the same time, it can cause the company to fail to pay the claim. This will certainly make the company's conduct decline, customer trust will be lost, and can cause the company to go bankrupt. The problem can be solved if the insurance company has sufficient claim fund reserves. Claim fund reserves are an important issue in insurance companies. This study aims to predict the claim fund reserves in insurance companies to anticipate varying claim amounts. Historical analysis of the value of claims with the ARIMA model approach is used to predict future claim values. We use claim value data that has been scaled in millions. 2020 to 2022 as training data and 2023 as test data. The Root Mean Square Error (RMSE) metric obtained is IDR 25,780.71; Mean Absolute Deviation (MAD) of IDR 14,421.89, and Mean Absolute Percentage Error (MAPE) of IDR 5,967.27; while the total actual claim value in 2023 is IDR 161,700.51 and the total predicted claim value is IDR 166,227.36; which means that an accuracy of 97% is obtained. The result of claim prediction value in one periodic year can give a favor to the management to make a decision, how much the claim funds should be prepared.
Co-Authors Ahsani, Rivai Bambang Pujiyono Broto, Suwasti Brotosaputro, Goenawan Bullion Dragon Dwi Kristanto Fika Fadlul Maulaya Gerry Bagus Sadewo Goenawan Brotosaputro Japriadi, Yohanes Setiawan Joko Sutrisno Keysha Salma Hanun Anzani Krisna Adiyarta Krisna Adiyarta M.N. Farid Thoha MARTINI Mulyati Mulyati Musafa, Akhmad Peby Wahyu Purnawan R, Jan Everhart Rahayu, Sri Retno Wulandari Rezza Anugrah Mutiarawan Samsinar Samsinar Samsinar Samsinar Suwasti Broto Suwasti Broto Swasti Broto Thoha, M. Nuur Farid Titin Fatimah Titin Fatimah Wendi Usino Wendy Usino Wildan Harya Khairi Windarto Windarto Yani Prabowo