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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Media Statistika Jurnal Studi Manajemen Organisasi Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah KOMPUTASI BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) Jiko (Jurnal Informatika dan komputer) JURNAL PENDIDIKAN TAMBUSAI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Jurnal Pendidikan dan Konseling bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) International Journal of Advances in Data and Information Systems Al-Mutharahah: Jurnal Penelitian dan Kajian Sosial Keagamaan Studies in Learning and Teaching Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) Jurnal Bisnis Indonesia Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) International Journal of Community Service International Journal of Data Science, Engineering, and Analytics (IJDASEA) Journal of Renewable Energy, Electrical, and Computer Engineering Jurnal Inkofar Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Jurnal Ilmiah Edutic : Pendidikan dan Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Eksponensial Baitul Hikmah: Jurnal Ilmiah Keislaman STATISTIKA Kohesi: Jurnal Sains dan Teknologi Information Technology International Journal (ITIJ) Seminar Nasional Teknologi dan Multidisiplin Ilmu Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal ilmiah teknologi informasi Asia RAGAM: Journal of Statistics and Its Application Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Trimono, Trimono
Data Science Department, Faculty Of Computer Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Batas Atas Ukuran Risiko Agregat Pada Portofolio Saham INDF.JK dan ICBP.JK Trimono Trimono; Amri Muhaimin; Andreas Nugroho Sihananto
Statistika Vol. 21 No. 2 (2021): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v21i2.340

Abstract

Pada investasi agregat aset finansial, setiap aset tunggal dapat memunculkan potensi risiko kerugian yang harus ditanggung oleh investor. Pada kondisi ini, untuk memprediksi nilai risiko kerugian dapat digunakan konsep risiko agregat. Prediksi nilai risiko dapat diukur melalui suatu ukuran risiko, salah satunya adalah Value at Risk (VaR). Namun, VaR tidak selalu memenuhi sifat subaditif, sehingga VaR bukan merupakan ukuran risiko yang koheren. Ukuran risiko lain sebagai alternatif pengganti VaR adalah Expected Shortfall (ES). Kelebihan utama ES dibandingkan VaR adalah ES telah memenuhi sifat subaditif, sehingga ES adalah ukuran risiko yang koheren. Untuk memprediksi nilai risiko agregat menggunakan VaR maupun ES, dibutuhkan fungsi distribusi bersama dari risiko agregat tersebut. Akan tetap cukup sulit untuk menentukan fungsi distribusi bersama risiko agregat yang disusun oleh beberapa risiko tunggal yang tidak saling bebas. Alternatif yang dapat digunakan apabila fungsi distribusi bersama risiko agregat sulit diperoleh adalah dengan menghitung batas atas risiko agregat dengan memanfaatkan sifat komonotonik dan convex order. Penelitian ini bertujuan untuk mengukur nilai batas risiko agregat menggunakan ukuran risiko ES untuk investasi agregat pada saham PT. Indofood Sukses Makmur Tbk (INDF.JK) dan PT Indofood CBP Sukses Makmur Tbk (ICBP.JK). Berdasarkan hasil analisis menggunakan data return saham INDF.JK dan ICBP.JK periode 02/01/21 – 17/09/21, nilai batas atas ukuran risiko aregat VaR dan ES pada portofolio saham untuk tingkat kepercayaan 95% dan holding period 1 hari masing-masing adalah -0,05231 dan -0,07731.
Antithesis of Human Rater: Psychometric Responding to Shifts Competency Test Assessment Using Automation (AES System) Mohammad Idhom; I Gusti Putu Asto Buditjahjanto; Munoto; Trimono; Prismahardi Aji Riyantoko
Studies in Learning and Teaching Vol. 4 No. 2 (2023): August
Publisher : Indonesia Approach Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46627/silet.v4i2.291

Abstract

This research is part of proof tests to a combination of statistical processing methods, collecting assessment rubrics in vocational education by comparing two systems, automated essay scoring and human rater. It aims to analyze the final assessment score of essays in Akademi Komunitas Negeri (AKN) Pacitan (Pacitan’s State Community College) and Akademi Komunitas Negeri (AKN) Blitar (Blitar’s State Community College) in East Java, Indonesia. The provisional assumption is that the results show an antithesis to the assessment of human feedback with an automated system due to the conversion of scores between the rubric and the algorithm design. As the hypothesis, algorithm-based score conversion affects automated essay scoring and human rater methods, which led to antithesis feedback. The validity and reliability of the measurement maintain the scoring consistency between the two methods and the accuracy of the answers. The novelty of this article is comparing between AES system and Human Rater using statistical methods. The research shows that there is a similar result using the psychometrics approach, which indicates different metaphor expressions and language systems. Thus, the objective of this study is to provide assistance in the advancement of an information technology system that utilizes a scoring mechanism merging computer and human evaluations, employing a psychological approach known as psychometric leads.
Media Digital Untuk Pembelajaran PAI Trimono, Trimono
Jurnal Pendidikan dan Konseling (JPDK) Vol. 5 No. 2 (2023): Jurnal Pendidikan dan Konseling
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jpdk.v5i2.20810

Abstract

Artikel ini bertujuan untuk mengetahui salah satu fungsi internet sebagai pengelola informasi sudah menjadi hal biasa bagi kalangan usia mulai dari anak-anak hingga orang dewasa guna memperluas wawasannya. Pembelajaan secara digital dapat dilakukan melalui penerapan e-learning pada kegiatan belajar mengajar melalui penggunaan teknologi. Selain itu artikel ini bertujuan untuk mendeskripsikan pembelajaran pendidikan agama Islam berbasis digital. Metode penelitian yang digunakan yaitu metode kualitatif deskriptif. Data yang dikumpulkan berasal dari data sekunder melalui analisis pustaka dari jurnal, artikel, buku, dan web terkait. Hasil penelitian ini menunjukkan bahwa media pembelajaran PAI berbasis digital seperti e- learning dalam proses pembelajaran akan menimbulkan kemauan dan minat baru bagi peserta didik, serta meningkatkan motivasi dalam belajar. Adapun media yang digital yang dapat dijadikan sebagai alat untuk meyampaikan materi PAI diantaranya melalui aplikasi Zoom,Meet,Classroom,dan WaGruop proses pembelajaran berbasis digital, yang kini banyak dilakukan oleh berbagai lembaga pendidikan. Kemahiran atau kurangnya pemahaman terhadap perangkat teknologi informasi dan komunikasi menjadi masalah yang muncul dari pembelajaran pendidikan agama Islam
Pendidik Dalam Pandangan Hadits Nabi Muhammad Saw Trimono, Trimono
Jurnal Pendidikan dan Konseling (JPDK) Vol. 5 No. 3 (2023): Jurnal Pendidikan dan Konseling
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jpdk.v5i3.20814

Abstract

karena guru harus bisa membimbing dan mengarahkan peserta didiknya ke arah yang positif dan lebih baik, dari semua aspek yang ada pada peserta didik baik dari segi kognitif, afektif, dan psikomotorik. Dalam kaitannya dengan masalah tersebut, akan dibahas dalam penelitian ini berbagai asumsi yang diambil dari sumber kedua dalam agama Islam yakni Sunnah Rasul (hadits). Dalam sumber tersebut banyak sekali literatur-literatur yang membahas tentang pendidik. Metode yang digunakan dalam penelitian ini adalah metode dokumentasi dengan jenis penelitian kalitatif, penganalisaan data lebih difokuskan pada penelitian perpustakaan (library research), yaitu berpedoman Sunnah Rasul (Hadits) sebagai referensi primer datanya, dan dibantu dengan buku-buku lain yang mendukung sebagai referensi sekunder dari beberapa pemikiran para tokoh ahli Hadits dan tokoh- tokoh pendidikan tentang tema pendidik. Teknik analisa dalam penelitian ini adalah teknik content analysis. Penelitian ini bertujuan untuk mengetahui tentang berbagai teori tentang pendidik (guru) dalam perspektif hadits Rasulullah saw. Dari hasil penelitian telah ditemukan beberapa hal diantaranya pendidik dalam perspektif hadits sebagai berikut: (1) Pendidik harus beriman,(2) Pendidik berniat ikhlas, (3) Pendidik harus berlapang dada,(4) Pendidik harus berlemah lembut dan tersenyum, (5) Pendidik harus memperhatikan kondisi muridnya.
Pemanfaatan Tepung Kentucky untuk Menumbuhkan Ekonomi di Tengah Pandemi Covid-19 Rizal, Syamsul; Giantara, Febri; Hervrizal, Hervrizal; Trimono, Trimono; Kusdani, Kusdani; Bainar, Bainar
Jurnal Pendidikan Tambusai Vol. 5 No. 3 (2021): 2021
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v5i3.2369

Abstract

Pengabdian kepada Masyarakat yang dilakukan merupakan bentuk usaha perbaikan ekonomi masyarakat di RT 02 RW 02 Kelurahan Agrowisata Rumbai dengan tujuan dari Pengabdian kepada Masyarakat ini adalah untuk mengedukasi masyarakat bagaimana cara memanfaatkan tepung kentucky yang baik dan benar serta mengajarkan memasarkan melalui media online. Metode penelitian yang digunakan adalah PAR dan dianalisis menggunakan pendekatan deskriptif. Hasil yang diperoleh adalah telihatnya perubahan pengetahuan warga tentang bagaimana cara mengolah tepung kentucky menjadi olahan makanan yang tepat dan bermanfaat serta memiliki nilai jual yang tinggi dimasyarakat. Hal ini terlihat dari hasil observasi warga. Selain itu juga ditemukan beberapa warga melanjutkan proses pendampingan ini menjadi bentuk sebuah usaha mikro kecil menengah yang mampu memberikan pemasukan tambahan bagi warga tesebut.
Prediction of The Islamic Stock Price Index and Risk of Loss Using The Long Short-Term Memory (LSTM) and Value At Risk (VaR) Taufik, Ikbar Athallah; Trimono, Trimono; Muhaimin, Amri
IJDASEA (International Journal of Data Science, Engineering, and Analytics) Vol. 4 No. 01 (2024): International Journal of Data Science, Engineering, and Analytics Vol 4, No 1,
Publisher : Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijdasea.v4i01.16

Abstract

Investment aims to increase the value of capital or earn additional income through asset growth, dividends or profits. One investment instrument that is in demand, especially among the Muslim community, is Islamic stocks, which are in accordance with Islamic principles that focus on a healthy economy. This research is focused on predicting Islamic stock prices using the Long Short-Term Memory (LSTM) method and measuring risk with Value at Risk (VaR) using the Cornish-Fisher Expansion (ECF) method. Stock price data from the food sector (PT Indofood), technology sector (Telkom Indonesia), and construction sector (Indocement) for the period 2018-2023 were analyzed. The results show that the ADAM model provides the best performance with the lowest prediction error rates for INTP and TLKM stocks (around 1.22%, 1.98%, and 1.41%). In addition, the SGD model shows limitations in accurate predictions with an error rate above 12%. VaR analysis reveals a slightly higher level of risk in INTP stocks, with a VaR value of around 2.85% at the 95% confidence level. Meanwhile, TLKM stock shows a lower level of risk, with a VaR of around 2.25% at the same confidence level. An in-depth understanding of the risk and growth characteristics of each stock, as well as the selection of the optimization model, are key in making wise investment decisions.
Analysis of Factors Affecting Minimum Salary of Workers in Indonesia Using Binary Logistic Regression Hadi, Surjo; Renaldi, Sahat; Trimono, Trimono; Susrama Mas Diyasa , I Gede
Information Technology International Journal Vol. 2 No. 1 (2024): Information Technology International Journal
Publisher : Magister Teknologi Informasi UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/itij.v2i1.20

Abstract

Salary is an important indicator used to measure the compensation and recognition individuals receive for their contributions to the workforce. Investigating the factors that influence salary levels is an intriguing research area. This study uses a logistic regression approach to analyze the relationship and influence of job field, job level, company location, and tenure on workers' salaries in Indonesia. The research findings reveal that the variables of job level and company location have a significant relationship with the minimum salary level received by workers. Based on the logistic regression modeling results, the variables that influence the minimum salary level are the company location (foreign) and average tenure
Modelling of Return of S&P 500 Using the Non Linear Generalized Autoregressive Conditional Heteroscedasticity (NGARCH) Model Trimono, Trimono; Damaliana, Aviolla Terza; Putri, Irma Amanda
Nusantara Science and Technology Proceedings 8th International Seminar of Research Month 2023
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4110

Abstract

ARIMA Box-Jenkins is one of the most popular forecasting methods. ARIMA modeling requires a non-heteroskedastic care that shows constant residual variants. Awake, meaning residual residue from heteroscedastic ARIMA modeling (not constant). To overcome the problem of residual heteroskedasticity ARIMA used modeling volatility that is Generalized Autoregressive Conditional Heteroscedasticity (GARCH). GARCH is used to model the ARIMA residual variant which means symmetric. Some financial data has an asymmetric nature caused by the influence of good news and bad news. To accommodate these asymmetric properties, we use the Non-Linear Generalized Autoregressive Conditional Heteroscedasticity (NGARCH) volatility model which is the development of the GARCH model. This research applies NGARCH model using S & P 500 share price index data from January 1, 2019, until July 31, 2023 during active day (Monday-Friday). The purpose of this study, to find the best model NGARCH. The best model generated for S & P 500 stock price index data is ARIMA (1,0,1) NGARCH (1,1) because it has small AIC.
Sentiment Analysis on Digital Korlantas POLRI Application Reviews Using the Distilbert Model Putri, Nabila Rizky Amalia; Trimono, Trimono; Damaliana, Aviolla Terza
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 4 No. 2 (2024): September 2024
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v4i2.17197

Abstract

The implementation of digitalization in public services by Korlantas Polri has facilitated faster administration, wider access, and improved service quality. The Korlantas Polri Digital app has garnered more than 5 million downloads on the Google Play Store, with a rating of 3.7 and around 110 thousand reviews. Given that an app's reputation can be significantly affected by criticism, sentiment analysis becomes very important to categorize user reviews as positive, negative, or neutral, thus assisting developers in identifying app shortcomings. This study uses DistilBERT, a deep learning model distilled from BERT, to assess the effectiveness of sentiment analysis on reviews. Data was collected from user reviews on the Google Play Store between September 1, 2023 and May 31, 2024, resulting in 8,752 reviews retained for analysis. Model performance was evaluated at three data ratios: 60:40, 70:30, and 80:20, with the best performance results seen at a ratio of 80:20, achieving 88% accuracy. Increasing the training data ratio from 60:20 to 80:20 has a positive impact on the model, suggesting that the model can learn better with larger training data.
Modelling of Return of S&P 500 Using the Non Linear Generalized Autoregressive Conditional Heteroscedasticity (NGARCH) Model Trimono Trimono; Aviolla Terza Damaliana; Irma Amanda Putri
Nusantara Science and Technology Proceedings 8th International Seminar of Research Month 2023
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4110

Abstract

ARIMA Box-Jenkins is one of the most popular forecasting methods. ARIMA modeling requires a non-heteroskedastic care that shows constant residual variants. Awake, meaning residual residue from heteroscedastic ARIMA modeling (not constant). To overcome the problem of residual heteroskedasticity ARIMA used modeling volatility that is Generalized Autoregressive Conditional Heteroscedasticity (GARCH). GARCH is used to model the ARIMA residual variant which means symmetric. Some financial data has an asymmetric nature caused by the influence of good news and bad news. To accommodate these asymmetric properties, we use the Non-Linear Generalized Autoregressive Conditional Heteroscedasticity (NGARCH) volatility model which is the development of the GARCH model. This research applies NGARCH model using S & P 500 share price index data from January 1, 2019, until July 31, 2023 during active day (Monday-Friday). The purpose of this study, to find the best model NGARCH. The best model generated for S & P 500 stock price index data is ARIMA (1,0,1) NGARCH (1,1) because it has small AIC.
Co-Authors Abda Abda Abdullah Abdullah Adam, Cindi Ade Irma Agustian Adelia Adelia, Adelia Adiwidyatma, Afdhal Reshanda Afidria, Zulfa Febi Aliya Dasa Pramesthi Amanillah, Rahmatul Amri Muhaimin Andreas Nugroho Sihananto Ardiani, Ardia Eva Arif, Farah Yusnaida Arifta, Septia Dini Asfiani, Ilil Musyarof Aurelia, Cenditya Ayu Aviolla Terza Damaliana Aviolla Terza Damaliana Aviolla Terza Damaliana Awang, Wan Suryani Wan Azni Aisyah Azzahra, Adelia Ramadhina Bainar Bainar, Bainar Bey Lirna, Cagiva Chaedar Carissa, Savvy Prissy Amellia Damaliana, Aviolla Terza Desy Miftachul Ilmi Arifin Putri Dewi, Ni Luh Ayu Nariswari Di Asih I Maruddani Di Asih I Maruddani Di Asih I Maruddani Diash, Hakam Dzakwan Dinda Putri Arnindi Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Dwi Arman Prasetya Dwi Arman Prasetya Edi Sugiyanto Fahrudin, Tresna Maulana Fairuz Luthfia Winoto Putri, Maretta Faizi, Dandi Nur Farkhan Febri Giantara Febriyanti, Alvi Yuana Febyanti, Iin Hadi, Surjo Hadiyan Pradipta, Alvino Hasan Hendri Prabowo Herlina Herlina Hervrizal, Hervrizal I Gede Susrama Mas Diyasa I Gede Susrama Mas Diyasa I Gusti Putu Asto Buditjahjanto Icha Rohmatul Jannah idhom, Mohammad Ikaningtyas, Maharani Ikaningtyas, Maharani Imanta Ginting Imelda Widya Ningrum Insania, Nichlata Irawan, Tanaya Anindita Irma Amanda Putri Kartika Maulida Hindrayani Kartika Maulida Hindrayani Kartini Kartini Kassim, Anuar bin Mohamed Khairunisa, Adenda Khosyi, Hanun Aufa Nur Kusdani, Kusdani Kuswardana, Dendy Arizki Linggasari, Dienna Eries Lisanthoni, Angela M Zufar Irhab S Putra Maharani Ikaningtyas Maruddani, Di Asih Mas'ad Mas'ad Maulana Pasha, Naufal Ricko Maulidiyyah, Nova Auliyatul Mohammad Idhom Mohammad Idhom Muhaimin, Amri Muhammad Muharrom Al Haromainy Munoto Nabila, Nasywa Azzah Nabilah Selayanti Nafiah, Fajria Ulumin Nariyana, Calvien Danny Nasution, Baktiar Nathania, Vannesa Ningrum, Imelda Widya Ningtiyas, Rona Wulan Nova Auliyatul Maulidiyyah Novita Anggraini Nugraheni, Setiawati Oktaviani, Sheny Eka Panglima, Talitha Fujisai Prisma Hardi Aji Riyantoko Prismahardi Aji Riyantoko Putra, Andrawana Putri, Irma Amanda Putri, Milla Akbarany Baktiar Putri, Nabila Rizky Amalia Putri, Shafira Amanda Rafiqah, Lailan Rafli Feandika Nugroho, Muhammad Ratna Yulistiani Renaldi, Sahat Rhomaningtias, Lina Riswanda, Mohammad Nizar Riyantoko, Prismahardi Aji Rizkiyah, Selly Rizqin, Indira Zein Ryan Dana, Alvin Sabela, Sefilah Naurah Safira Devi, Arsita Safira, Alya Mirza Salma Namira, Alivia Saputra, Wahyu Syaifullah Jauharis Sekar Arum Melati Sihananto, Andreas Sonhaji, Abdulah Sugiarti, Nova Putri Dwi Suprapto, Rheinka Elyana Susrama Mas Diyasa , I Gede Syamsul Rizal Tarno Tarno Taufik, Ikbar Athallah Terza Damaliana, Aviolla Tresna Maulana Fahrudin Utami, Rianti Siswi Utriweni Mukhaiyar Valentina, Tiara Wardah Ariij Adibah Wardah, Salsabila Wardani, Ajeng Puspa Wibowo, Muhammad Bagas Satrio Widayawati, Eny Widayawati, Eny Widison, Daffin Tanjiro Yuciana Wilandari Zalfa Assyadida, Azizah