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All Journal Seminar Nasional Teknologi Informasi Komunikasi dan Industri Journal of Applied Engineering and Technological Science (JAETS)
Fitra Lestari
Universitas Islam Negeri Sultan Syarif Kasim Riau
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics

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A Web-Based Bitcoin Currency Price Forecasting System Using Multiple Linear Regression Algorithm Ismar Puadi; Rahmad Kurniawan; Benny Sukma Negara; Fadhilah Syafria; Fitra Lestari
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2021: SNTIKI 13
Publisher : UIN Sultan Syarif Kasim Riau

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Abstract

Keberadaan cryptocurrency memberikan kemajuan transaksi dalam bidang ekonomi. Salah satu jenis cryptocurrency adalah Bitcoin (BTC), BTC saat ini banyak digunakan oleh para pebisnis dan investor. BTC dapat diperjualbelikan setiap saat tanpa ada Batasan waktu, namun harga BTC berfluktuasi. Peramalan harga BTC yang cepat diperlukan oleh para investor untuk mencegah kerugian dalam jumlah besar. Peramalan secara manual sulit dilakukan karena harga BTC yang berfluktuasi BTC secara cepat. Oleh karena itu, diperlukan  Teknik yang cepat dan jitu menggunakan Machine Learning. Salah satu algoritma yang sederhana, cepat dan tepat dalam komputasi  untuk memprediksi harga BTC adalah Regresi Linear Berganda. Penelitian ini menggunakan data enam tahun yaitu tahun 2014-2021 sebagai data latih. Berdasarkan hasil eksperimen, diperoleh formula Y=-0,16780543+((-0,41658744)X1 )+((0,84132834)X2) + ((0,57040201)X3). Selanjutnya dari persamaan linear tersebut digunakan untuk pengujian. Berdasarkan hasil eksperimen, didapat bahwa sistem peramalan harga BTC menghasilkan tingkat kesalahan RMSE 405,23 dan MAPE sebesar 1,22. Sistem peramalan berbasis web ini berpotensi digunakan sebagai pertimbangan oleh pengguna dalam meramalkan harga BTC.
Text Classification System Based on Islamic Jurisprudence Using Multinomial Naïve Bayes Classifier Riyan Wibowo Saputra; Benny Sukma Negara; Rahmad Kurniawan; Muhammad Irsyad; Iis Afrianty; Fitra Lestari
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2021: SNTIKI 13
Publisher : UIN Sultan Syarif Kasim Riau

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Abstract

Indonesia merupakan negara dengan populasi umat muslim terbesar di dunia. Islam tidak hanya mengajarkan tentang ibadah tetapi juga masalah kehidupan seorang muslim yang diatur dalam hukum Islam (Fiqih). Ilmu hukum Islam dapat diketahui dengan cara belajar kepada seorang ulama bidang Fiqih atau membaca buku dari ulama tersebut. Namun, tidak semua orang dapat bertemu ulama dan dapat memahami isi buku dari ulama tersebut. Oleh karena itu, diperlukan sebuah sistem klasifikasi teks yang dapat digunakan umat untuk pertimbangan jawaban dari hukum Islam yang ditanyakan. Algoritme Multinomial Naïve Bayes dipilih sebagai metode untuk menyimpulkan jawaban hukum Islam karena ketepatannya sebagai mesin inferensi. Buku yang ditulis oleh pakar Fiqih Asia Tenggara yaitu Ustaz Abdul Somad yang berjudul “37 Masalah Popular, 77 Tanya Jawab Tentang Shalat dan 33 Tanya Jawab Seputar Kurban” telah digunakan sebagai basis pengetahuan dalam aplikasi berbasis web ini. Berdasarkan hasil pengujian  yang dilakukan, didapatkan sistem klasifikasi teks hukum Islam ini menghasilkan akurasi sebesar 75%. Berdasarkan eksperimen dan pengujian tersebut, dapat disimpulkan bahwa sistem klasifikasi teks berdasarkan hukum Islam ini berpotensi digunakan sebagai pertimbangan dalam memahami ilmu Fiqih.
Classification Academic Data using Machine Learning for Decision Making Process Elin Haerani; Fadhilah Syafria; Fitra Lestari; Novriyanto Novriyanto; Ismail Marzuki
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 2 (2023): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v4i2.1983

Abstract

One of the qualities of higher education is determined by the success rate of student learning. Assessment of student success rates is based on student graduation on time. Sultan Syarif Kasim State Islamic University Riau is one of the state universities in Riau, with a total of 30,000 students. Of all the active students, there are some who are not. Students who are not active in this case will affect the timeliness of their graduation. The university always evaluates the performance of its students to find out information related to the factors that cause students to become inactive so that they are more likely to drop out and what data affect students being able to graduate on time. The evaluation results are stored in an academic database so that the data can later be used as supporting data when making decisions by the university. This research used data science concepts to explore and extract data sets from databases to find models or patterns, as well as new insights that can be used as tools for decision-making. After the data was explored, machine learning concepts were used to identify and classify the data. The method used was the Decision Tree Method. The results of the study found that these two concepts can provide the expected results. Based on the test results, it is known that the attribute that influences the success of student studies is the grade point average (GPA), where the accuracy of the maximum recognition rate is 88.19%. Keywords : Data science; Decision Tree; Graduate on Time; Machine Learning;
Identifying Factors for The Success of Halal Management Practices in Leather Industry Tengku Nurainun; Hayati Habibah Abdul Talib; Khairur Rijal Jamaludin; Shari Mohd Yusof; Nilda Tri Putri; Fitra Lestari
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 2 (2023): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v4i2.1989

Abstract

The need to apply halal management practices to non-food industries today is still merely seen as a necessity to meet the requirements of Islamic rules. Meanwhile, this approach has demonstrated that it can improve organizational efficacy in a variety of contexts. This study seeks to investigate the depth of halal principles implementation among leather industries and comes up with strategies for how small and medium-sized enterprises (SMEs) in the leather industry can use halal management practices to move toward halal certification and enhance its performance. An exploratory-descriptive approach was used to get the current state of halal practices among leather industry SMEs through interviews and survey questionnaires. Five stakeholders were interviewed in a semi-structured manner. A survey questionnaire was distributed to 127 SMEs in the leather industry center of Sukaregang, Garut, Indonesia. This paper discusses the key factors of halal implementation and determines which halal practices need more emphasis. The result showed that the current knowledge, awareness, and implementation of halal requirements among leather SMEs in Indonesia are still low. An action plan for the industry, authority, and supplier was provided.  The implication of this research can contribute to the leather industry players that intent to implement halal management system effectively and stakeholders in making decision to accelerate halal certification process.
Co-Authors Benny Sukma Negara Elin Haerani Fadhilah Syafria Hayati Habibah Abdul Talib Iis Afrianty Ismail Marzuki Ismar Puadi Khairur Rijal Jamaludin Muhammad Irsyad Nilda Tri Putri Novriyanto Novriyanto Rahmad Kurniawan Riyan Wibowo Saputra Shari Mohd Yusof Tengku Nurainun