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All Journal JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Indonesian Journal of Electrical Engineering and Computer Science Unri Conference Series: Community Engagement Jurnal Sistem Informasi dan Teknik Informasi HISTORIA: Jurnal Program Studi Pendidikan Sejarah
Indra, Zul
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Humanities Computer Science & IT Medicine & Pharmacology Social Sciences Other

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The Comparison of Accuracy on Classification Climate Change Data with Logistic Regression Adnan, Arisman; Yolanda, Anne Mudya; Erda, Gustriza; Goldameir, Noor Ell; Indra, Zul
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 1 (2023): Articles Research Volume 7 Issue 1, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i1.11914

Abstract

Machine learning methods can be used to generate climate change models. The goal of this study is to use logistic regression machine learning algorithms to classify data on greenhouse gas emissions. The data used is climate change data of several countries obtained from The World Bank, with total greenhouse gas emissions as the response variable and 61 other attributes as explanatory variables. This data is preprocessed using min-max normalization to handle unbalanced ranges, and then the data is split into 70% training data and 30% testing data. Based on the logistic regression modeling, it was discovered that the data from the min-max transformation resulted in better modeling than the data modeling without the transformation process. The accuracy, precision, sensitivity, and specificity of the transformation are 87.60%, 87.76%, 87.04%, and 88.14%, respectively
A proposed semantic keywords search engine for Indonesian Qur’an translation based on word embedding Trisnawati, Liza; Binti Samsudin, Noor Azah; Bin Ahmad Khalid, Shamsul Kamal; Bin Ahmad Shaubari, Ezak Fadzrin; Sukri, Sukri; Indra, Zul
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp987-995

Abstract

Obtaining relevant information from the Holy Qur’an can be really challenging for people who cannot speak Arabic, such as the Indonesian people. One technology implementation which is commonly used to tackle this problem is to develop a search engine application for Al-Qur’an verses. This paper proposes a search engine based on semantic representation keywords for the Indonesian translation of the Al-Qur’an which consists of 3 phases i.e., data preparation, document representation, and search engine development. In the first stage, the Al-Qur’an dataset was built using the official translation of the Al-Qur’an from the Ministry of Religion and then enriched with the Wikipedia corpus. The second phase is document representation which produces feature vectors by utilizing the Word2Vec algorithm. Finally, the development of a search engine that can find the most relevant verses by calculating the cosine similarity between the document and the keywords. It was found that the proposed search engine succeeded in exceeding the performance of ordinary search engines by finding wider information due to the use of semantic keywords. Apart from that, the proposed search engine succeeded in maintaining the relevance of search results by achieving precision and recall levels of 98.7% and 97.3% respectively.
History of SMAN 3 Painan as the First Boarding School in Pesisir Selatan (2011-2024) Indra, Zul; Najmi, Najmi
HISTORIA: Jurnal Program Studi Pendidikan Sejarah Vol 13, No 1 (2025): HISTORIA: Jurnal Program Studi Pendidikan Sejarah
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/hj.v13i1.10816

Abstract

This research examines the history of SMAN 3 Painan as the first boarding school in Pesisir Selatan during the 2011-2024 period. SMAN 3 Painan implements an educational model where students live in dormitories for 24 hours, following an integrated educational program. This study uses historical methods, including heuristics, source criticism, interpretation, and historiography. Primary sources were obtained from government archives and interviews, while secondary sources came from books and journals. The results show that the establishment of SMAN 3 Painan began after the junior high school competency test results in West Sumatra in 2008, where Pesisir Selatan ranked second. The school was built to accommodate high-achieving students to ensure they continued studying in their home region. Since its founding, SMAN 3 Painan has achieved various national-level accomplishments.
Penguatan Kapasitas Komunitas Statistika Bantar dalam Tata Kelola Data Desa untuk Pembangunan Berkelanjutan Adnan, Arisman; Yolanda, Anne Mudya; Erda, Gustriza; Syamsudhuha, Syamsudhuha; Indra, Zul; Solfitri, Titi; T, Masrina Munawarah
Unri Conference Series: Community Engagement Vol 6 (2024): Seminar Nasional Pemberdayaan Masyarakat
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/unricsce.6.640-645

Abstract

This activity aims to strengthen the capacity of the statistical community in Bantar Village in supporting the transformation and management of data for sustainable development. The program focuses on assisting village officials in effectively managing data at the village level, in line with the Desa Cantik initiative and Indonesia One Data (SDI) program. The goal is to improve data accuracy and the effectiveness of village development planning. As a result, the statistical community, which also includes village officials, has shown increased capabilities in managing sectoral statistics and digitalizing data integrated with the Desa Cantik program. The village officials actively participated in this assistance, supported by the provincial and district BPS, who acted as facilitators. BPS provided training, monitoring, evaluation, and assistance in the preparation of program materials and outputs. One of the key outputs of this program is the creation of an infographic summarizing the statistics and potential of Bantar Village, covering demographic profiles, population density, and key commodities. This infographic serves as a visual communication tool that supports data-driven development planning. The program successfully established a strong foundation for better data management, supporting sustainable village development.
An Improved Okta-Net Convolutional Neural Network Framework for Automatic Batik Image Classification Elvitaria, Luluk; Ahmad, Ezak Fadzrin; Samsudin, Noor Azah; Ahmad Khalid, Shamsul Kamal; Salamun, -; Indra, Zul
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2591

Abstract

Batik is one of Indonesia's most important cultural arts and has received recognition from UNESCO. Batik has high artistic and historical value with a variety of patterns. Currently, Indonesia has 5,849 batik motifs which are generally classified based on shape, color, motif and symbolic meaning. The diversity of batik motifs makes it difficult for ordinary people to fully recognize them. This paper intends to develop an automatic framework for classifying batik motifs as a solution to overcome this issue. To develop this classification automation framework, the paper proposes a new architecture based on deep learning, which is named Okta-net. The architecture consists of 8 convolutional layers with separate convolution operations (SeparableConv2D). The output of the last convolution block will be fed to the fully connected layer using global average pooling. Meanwhile, in developing a deep learning model to classify batik image patterns, a dataset of 5 batik classes (motifs) was organized, consisting of 4,284 batik images. Through a series of experiments carried out, the proposed Okta-Net architecture succeeded in achieving satisfactory results with a validation accuracy of 93.17%, Precision of 91.60%, Recall of 92.28%, F-1 Score of 91.54%, and a loss of just 0.12%. Thus, it can be concluded that Okta-Net architecture can help preserve Indonesia's batik cultural heritage by accurate batik motif’s classification. Apart from that, based on a comparison of research outcomes, Okta-Net outperformed most of earlier studies, the majority of which had an accuracy of below 90%.
Smart Notepad Menggunakan Security Berbasis Android Kristianto, Yudi; Indra, Zul; Puspita Sari , Ira
Jurnal SANTI - Sistem Informasi dan Teknik Informasi Vol. 1 No. 1 (2021)
Publisher : Yayasan Rahmatan Fiddunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (904.422 KB) | DOI: 10.58794/santi.v1i1.14

Abstract

Perkembangan Teknologi di era globalisasi saat ini berkembang sangat pesat. Salah satunya yaitu smartphone, Penggunaan smartphone adalah hal yang sudah wajib bagi masyrakat. Namun banyak pennguna smartphone kehilangan data peting mereka bahkan ada sebahagian data penting mereka seperti foto dan video pribadi di curi orang yang tidak bertanggung jawab dan ada juga di sebar luaskan, sebab banayak pennguana smarthphone hanya menngunakan kunci layar yang kemungkinan besar sangat rentan di ketahaui orang karena hanya menggunakan kunci layar dalam bentuk sandi maupun pola kunci. Oleh sebab itu perlu dibuat penyimpanan yang sifatnya rahasia agar orang lain tidak dapat melihat data rahasia. Yang mana pada penelitian ini menngunakan metode steganography.hasil akhir dari penelitian ini berupa aplikasi notepad security yang dapat membantu menyembunyikan data penting pengguna secara rahasia.
Co-Authors - Salamun Ahmad Khalid, Shamsul Kamal Ahmad, Ezak Fadzrin Anne Mudya Yolanda Arisman Adnan Bin Ahmad Khalid, Shamsul Kamal Bin Ahmad Shaubari, Ezak Fadzrin Binti Samsudin, Noor Azah Goldameir, Noor Ell Gustriza Erda Kristianto, Yudi Liza Trisnawati Luluk Elvitaria, Luluk Najmi Najmi, Najmi Noor Azah Samsudin, Noor Azah Puspita Sari , Ira sukri Sukri, sukri Syamsudhuha Syamsudhuha T, Masrina Munawarah Titi Solfitri