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PROYEKSI LAJU BI RATE BULANAN DI INDONESIA MENGGUNAKAN MODEL ARIMA Puput Purnamasari; Zumrotis Sholihah; Fitri Nur Afifah; Latipah; Achmad Budi Susetyo
Jurnal Media Akademik (JMA) Vol. 3 No. 11 (2025): JURNAL MEDIA AKADEMIK Edisi November
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/n2kwpx08

Abstract

BI Rate merupakan instrumen utama kebijakan moneter yang digunakan oleh Bank Indonesia sebagai acuan dalam menentukan tingkat suku bunga antarbank, serta berpengaruh terhadap tingkat bunga kredit, simpanan, dan kondisi likuiditas di pasar uang domestik. Penelitian ini bertujuan untuk memprediksi pergerakan BI Rate di Indonesia selama periode Januari 2025 hingga Desember 2025, mengingat hingga saat ini belum banyak kajian yang secara khusus membahas periode tersebut. Peramalan ini diperlukan sebagai alat analisis yang dapat dimanfaatkan dalam pengambilan keputusan kebijakan moneter. Metode yang digunakan adalah analisis ARIMA dengan pendekatan Box-Jenkins, yang dinilai efektif dan sesuai untuk melakukan peramalan pada rentang waktu tertentu. Data yang digunakan merupakan data sekunder berbentuk time series yang diperoleh dari Badan Pusat Statistik (BPS), berupa nilai BI Rate bulanan di Indonesia periode Januari 2020 hingga Desember 2024. Pengolahan data dilakukan menggunakan perangkat lunak EViews 13 dan hasil pengujian menunjukkan bahwa data telah stasioner pada level sehingga tidak memerlukan proses differencing. Model terbaik yang dihasilkan adalah ARIMA (1,0,0) dengan nilai Akaike Information Criterion (AIC) sebesar -5.814962, Schwarz Information Criterion (SIC) sebesar -5.709324, serta Adjusted R-squared sebesar 0.392174. Berdasarkan hasil tersebut, model peramalan menunjukkan kecenderungan BI Rate mengalami peningkatan yang stabil  selama periode estimasi satu tahun ke depan.
The Influence of Sharia Economic Politics on the Development of Sharia Financial Institutions in the Digital Era in Indonesia Wahdatul Nadia Rawi; Latipah; Raudlatus Solihin
Al-Fadilah: Islamic Economics Journal Vol. 3 No. 2 (2025): Potential and Innovation in Islamic Economic
Publisher : Penerbit Hellow Pustaka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61166/fadilah.v3i2.37

Abstract

The development of Islamic financial institutions in Indonesia is growing rapidly, particularly with the advent of the digital era. Islamic economic politics plays a significant role in shaping policies and regulations that support the growth of this sector. This article examines how Islamic economic politics influences the development of Islamic financial institutions in Indonesia, focusing on the application of digital technology. Using a qualitative descriptive approach, this study identifies that government policies based on Islamic principles, coupled with technological innovation, are key factors in increasing access and efficiency of Islamic financial services. Based on data from the Financial Services Authority (OJK), the Islamic fintech sector in Indonesia has recorded growth of around 50% per year in recent years. Furthermore, Islamic fintech has also grown rapidly in recent years, offering various services such as digital payments, peer-to-peer (P2P) financing, and Islamic-based investments. The research method used in this study is a literature review.
Keteladanan Guru sebagai Strategi Penguatan Perkembangan Sosial-Emosional Anak Usia Dini di PAUD Al Barkah Rengasdengklok Deden Deni Mahendra; Yanti Apriani; Latipah; Siti Karmila; Daresih; Yulia Ayu Rahmatul Fitri
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 04 (2025): Volume 10 No. 04 Desember 2025 In Process
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i04.39644

Abstract

Social-emotional development in early childhood is an important aspect in shaping children’s behavior and personality that requires attention from an early age. Early childhood education environments play a strategic role in facilitating this development, particularly through teachers’ role modeling in daily interactions. This study aims to describe teacher role modeling as a strategy for strengthening the social-emotional development of early childhood learners at PAUD Al Barkah Rengasdengklok. The study employed a qualitative approach with a descriptive design. Data were collected through observation, interviews, and documentation involving teachers and early childhood learners as research subjects. The findings indicate that teacher role modeling is reflected in polite communication, calm emotional regulation, consistent discipline, and guidance provided to children in resolving conflicts. Children demonstrated improvements in emotional regulation, social interaction, and responsibility through processes of observation and imitation of teachers’ behavior. Teacher role modeling creates a safe learning environment that supports children’s social-emotional development. The conclusion of this study indicates that teacher role modeling contributes to strengthening early childhood social-emotional development through everyday practices in the school environment. Keywords: teacher role modeling, social-emotional development, early childhood
Peningkatan Visibilitas Digital melalui Implementasi Search Engine Optimization (SEO) di PT. Olean Permata Telematika Achmad Zakki Falani; I Putu Artaya; Latipah; Lukman Junaedi
Asthadarma : Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 1 (2026): Maret
Publisher : Universitas Merdeka Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55173/asthadarma.v7i1.72

Abstract

Digital transformation has encouraged Internet Service Provider (ISP) companies to optimize digital media as a strategic tool for marketing and customer communication. One of the major challenges faced is the low visibility of company websites on search engines, which limits public access to information regarding services offered. This activity aims to enhance the digital visibility of PT Olean Permata Telematika through the implementation of Search Engine Optimization (SEO) strategies. The methods employed include an initial website analysis, technical and content optimization, as well as training and mentoring for company personnel on sustainable SEO practices. The results indicate an improvement in website visibility on search engine results and an increased level of understanding among the partner regarding SEO implementation. This activity is expected to strengthen the company’s digital marketing strategy and improve its competitiveness in the ISP industry.
Unsupervised Twitter Sentiment Analysis on The Revision of Indonesian Code Law and the Anti-Corruption Law using Combination Method of Lexicon Based and Agglomerative Hierarchical Clustering Prayoga, Nur Restu; Tresna Maulana Fahrudin; Made Kamisutara; Rahagiyanto, Angga; Primananda Alfath, Tahegga; Latipah; Winardi, Slamet; Susilo, Kunto Eko
EMITTER International Journal of Engineering Technology Vol 8 No 1 (2020)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v8i1.477

Abstract

The rejection on ratification of the revision of Indonesian Code Law or known as RKUHP and Corruption Law raises several opinions from various perspectives in social media. Twitter as one of many platforms affected, has more than 19.5 million users in Indonesia. Twitter is one of many social media in Indonesia where people can share their views, arguments, information, and opinions from all points of view. Since Twitter has a great diversity of users, it needs a system which is designed to determine the opinion tendency towards the problems or objects. The purpose of this study is to analyze the sentiment of Twitter users' tweets to reject the revision of the Law whether they have positive or negative sentiments using the Agglomerative Hierarchical Clustering method. The data that being used in this study were obtained from the results of crawling tweets based on hashtag (#) (#ReformasiDikorupsi). The next stage is pre-processing which consists of case folding, tokenizing, cleansing, sanitizing, and stemming. The extraction features Lexicon Based and Term Frequency (TF) which performs the process automatically. In the clustering stage, two clusters use three approaches; single linkage, complete linkage and average linkage. In the accuracy calculation phase, the writer uses the error ratio, confusion matrix, and silhouette coefficient. Therefore, the results are quite good. From 2408 tweets, the highest accuracy results are 61.6%.
Co-Authors Achmad Budi Susetyo Achmad Zakki Falani Afiyanta Wulandari Arikatun Maimunah Bachrul Azali Chairul rizal Cindy Hartika Daresih Darmiyati Deden Deni Mahendra Deden Mula Saputra Dwi Putri Ayu Nur Aini Fatonah Fitri Nur Afifah Fitria Ekawati, Iga Hammi, Moh Mufarijul I Putu Artaya Jelita Purwanti Junaedi, Lukman Kamisutara, Made Kawuryan, Uji Muchayan, Achmad Muhammad Ersya Faraby Noorhapizah Poppy Nabilla Pratama, Kharisma Prayoga, Nur Restu Puput Purnamasari Putu Artaya Rahagiyanto, Angga Raudlatus Solihin SITI KARMILA Slamet Winardi Susilo, Kunto Eko Tahegga Primananda Alfath Tazkiyah Fuadiyah Tresna Maulana Fahrudin Wahdatul Nadia Rawi Yanti Apriani Yogi Prihandoko Yulia Ayu Rahmatul Fitri Zumrotis Sholihah