Article Per Year (5 Year)
p-Index From 2021 - 2026
2.501
P-Index
This Author published in this journals
All Journal Sistemasi: Jurnal Sistem Informasi Jurnal CoreIT Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Pendidikan Guru (JPG) Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research JUTECH : Journal Education and Technology Malcom: Indonesian Journal of Machine Learning and Computer Science Indonesian Science Education Journal (ISEJ) INOVTEK Polbeng - Seri Informatika
Oktavia, Lola
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 18 Documents
Search

 1   2 
Clustering Data Penduduk Desa Menggunakan Algoritma Mean Shift Maulani, Tedi; Haerani, Elin; Wulandari, Fitri; Oktavia, Lola
TIN: Terapan Informatika Nusantara Vol 6 No 1 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i1.7550

Abstract

Social welfare remains a serious challenge in Indonesia, including in Riau Province, which, despite its abundant natural resources, still struggles with unequal distribution of welfare. One of the government’s efforts to address this issue is through social assistance programs. However, identifying the right beneficiaries remains problematic. This study aims to cluster residents of Desa Bina Baru using the Mean Shift algorithm to support more targeted social aid distribution. The clustering results were evaluated using the Silhouette Score to measure their quality. The optimal clustering was achieved at a quantile of 0.9, with the highest Silhouette Score of 0.5747, producing nine clusters with varying socioeconomic characteristics. Based on the analysis, clusters 2, 1, 5, and 6/7 were identified as the most eligible groups to receive government aid due to economic pressure, high number of dependents, and inadequate housing conditions. This prioritization is crucial for more accurate, data-driven distribution of aid and provides valuable insights to support sustainable poverty alleviation strategies in Desa Bina Baru.
Islamic Studies on the Metabolism Process of Vitamins and Minerals in the Body Dinanti, Sri Wahyu; Oktavia, Lola; Hasanah, Qomariah
ISEJ : Indonesian Science Education Journal Vol. 3 No. 1 (2022): Januari 2022
Publisher : Yayasan Darussalam Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62159/isej.v3i1.692

Abstract

Humans to maintain survival need food as the most basic thing. However, it remains to be considered whether these foods have optimal nutritional value. The food consumed by humans must contain various kinds of nutritional content that can support human life processes. how optimal public health can be increased with the implementation of hygienic and halal food, this fulfills the criteria of good food in Islamic and health studies. This study uses a literature review method in which the researcher conducts a series of studies involving various kinds of information from the literature such as books, encyclopedias, documents, and so on. The data is described and analyzed by understanding and explaining it. with the aim of finding various kinds of theories and ideas which can then be formulated results in accordance with research objectives. Islam and health basically have the same goal for the good of humanity. Therefore, in consuming food there are several conditions that must be met and really paid attention to so that humans avoid various types of diseases that originate from food. The study of Islam in the Al-Quran is found in QS.AlBaqarah, 2:168 Halal food and thoyyib means food and drink that are permissible for consumption according to Islam, according to the type of food and how to obtain it. Halal in the understanding of fuqaha is lawful in terms of substance and process. It is also called thoyyib if the food is safe, good, and does not cause any problems if consumed, both short and long term and can provide benefits to the body.
MENINGKATKAN KARAKTER MAHASISWA PRODI TADRIS IPA UINFAS BENGKULU MELALUI ORGANISASI UKM-KI Oktavia, Lola; Edo Saputra, Riski; Topano, Adrian
JPG: Jurnal Pendidikan Guru Vol. 5 No. 1 (2024): JPG: Jurnal Pendidikan Guru
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Ibn Khaldun Bogor

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

Abstract

Pendidikan merupakan suatu proses yang mencakup tiga dimensi, individu, masyarakat atau komunitas nasional dari individu tersebut, dan seluruh kandungan realitas, baik material maupun spiritual yang memainkan peranan dalam menentukan sifat, nasib, bentuk manusia maupun masyarakat. UINFAS Bengkulu merupakan perguruan tinggi islam yang memiliki mahasiswa dari latar belakang yang bermacam-macam. Karakter yang Dimiliki mahasiswa nya pun beragam. Kepribadian merupakan ciri atau karakteristik atau sifat khas dari diri seseorang yang bersumber dari bentukan-bentukan yang diterima dari lingkungan, misalnya keluarga pada masa kecil, dan juga bawaan sejak lahir. faktor terbentuknya karakter mahasiswa ialah keluarga, masyarakat, teman sepergaulan, serta lingkungan disekitar, peningkatan karakter mahasiwa ipa UINFAS Bengkulu dapat dilakukan melalui organisasi UKM-KI, UKM-KI atau Unit Kegiatan Mahasiwa Korelasi Islam adalah sebuah Lembaga organisasi didalam lingkup lingkungan kampus yang bergerak dalam bidang kerohanian islam. Dengan adanya organisasi ini diharapkan dapat menerapkan nilai-nilai karakter Qur’ani dalam kehidupannya maupun lingkungan masyarakat. dengan adanya kegiatan yang ada di kampus dapat memberikan pengaruh terhadap mahasiswa dengan lingkungan sosialnya. tujuan dari penelitian ini untuk menerapkan kegiatan UKM-KI guna membentuk karakter mahasiswa IPA di UINFAS Bengkulu. Dalam penelitian ini, peneliti menggunakan metode kualitatif dan untuk mengumpulkan data, peneliti melakukan jenis penelitian library research yaitu mengumpulkan karya tulis ilmiah yang berhubungan dengan masalah yang dibahas. Adapun hasil penelitian mengenai implementasi karakter mahasiswa pada kegiatan UKM-KI. Dengan adanya penerapan yang dilakukan oleh UKM-KI UINFAS Bengkulu yang melakukan kegiatan-kegiatan yang positif dan bermanfaat bagi mahasiswa dapat membentuk karakter mahasiswa menjadi lebih baik.
Klasifikasi Penyakit Cacar Monyet Menggunakan Metode Support Vector Machine Anugrah, Wendy; Haerani, Elin; Yusra, Yusra; Oktavia, Lola
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5149

Abstract

Monkey pox is a zoonotic disease caused by the monkey pox virus and this disease is very dangerous. Monkey pox can be detected in advance by using information contained in patient data and applying machine learning techniques. This study aims to classify monkey pox using the Support Vector Machine (SVM) method. This test is carried out using a confusion matrix by comparing the ratio of training data and test data with a ratio of 70:30, 80:20, 90:10 and using the RBF kernel. Based on the test results, the highest ratio results were obtained at 90:10 with the best accuracy value of 65% with SVM parameter testing, namely the value C= 10 and y (gamma)= 1. Based on the results of tests carried out using the Support Vector Machine method, the accuracy values ​​were quite good.
Analisis Manajemen Risiko Teknologi Informasi pada KPU Menggunakan Cobit 5 Domain APO12: Analysis of Information Technology Risk Management at KPU Using Cobit 5 Domain APO12 Wirayudha, Muhammad Aldi; Novriyanto, Novriyanto; Darmizal, Teddie; Oktavia, Lola
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 2 (2024): MALCOM April 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i2.1225

Abstract

Komisi Pemilihan Umum adalah lembaga negara yang menyelenggarakan pemilihan umum di Indonesia. Sebagai penyelenggara pemilu, pemanfaatan teknologi informasi sangat penting untuk mendukung operasional bisnis dan meningkatkan kualitas organisasi. Oleh karena itu, penting bagi lembaga negara untuk menerapkan pengelolaan risiko teknologi informasi khususnya pada Komisi Pemilihan Umum Kabupaten XYZ guna mencegah terjadinya kerugian risiko serta meningkatkan efikasi dan efisiensi manajemen risiko teknologi informasi. Pengelolaan risiko teknologi informasi di KPU Kabupaten XYZ belum maksimal sehingga rentan terhadap kejadian risiko yang dapat berdampak negatif terhadap pelaksanaan tanggung jawabnya. Analisis manajemen risiko teknologi informasi di Komisi Pemilihan Umum Kabupaten XYZ khususnya pada aspek keamanan data, sistem informasi, dan infrastruktur TI bertujuan untuk menilai capability level dengan menggunakan framework COBIT 5 domain APO12 yang secara khusus mengatur manajemen risiko. Nilai kapabilitas organisasi yang ditentukan berdasarkan analisis domain APO12 adalah 1,35 yang menunjukkan bahwa organisasi telah mencapai level kapabilitas 1 (proses yang dilakukan). Artinya, proses manajemen risiko teknologi informasi telah diterapkan, namun masih belum terstruktur dan tidak konsisten. Agar proses APO12 mencapai level 2 (proses terkontrol), ditemukan celah 1 di setiap subdomainnya. Berdasarkan analisis kesenjangan, diberikan saran perbaikan. Rekomendasi ini akan menjadi landasan penilaian manajemen risiko teknologi informasi di KPU Kabupaten XYZ ke depan.
KLASIFIKASI SENTIMEN MASYARAKAT TERHADAP EFISIENSI ANGGARAN PEMERINTAH MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Alfaridzy, M. Audi; Haerani, Elin; -, Jasril; Oktavia, Lola
JUTECH : Journal Education and Technology Vol 6, No 1 (2025): JUTECH JUNI
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v6i1.4969

Abstract

Kebijakan efisiensi anggaran pemerintah Indonesia tahun 2025 merupakan respons terhadap kebutuhan penguatan fiskal dan pengalokasian ulang anggaran untuk program prioritas nasional. Melalui Instruksi Presiden Nomor 1 Tahun 2025, pemerintah menetapkan penghematan sebesar Rp306,7 triliun dengan memotong belanja kementerian/lembaga dan transfer ke daerah. Meskipun ditujukan untuk mendukung program strategis seperti Makan Bergizi Gratis (MBG), kebijakan ini menimbulkan dampak signifikan, seperti pemangkasan anggaran lembaga penting (misalnya BMKG) lebih dari 50%, pembatalan proyek infrastruktur, serta pengurangan tenaga kerja di sektor media publik. Kondisi ini menimbulkan perdebatan di tengah masyarakat terkait kebutuhan penghematan dan potensi risikonya terhadap pelayanan publik, investasi, serta pemerataan pembangunan. Penelitian ini bertujuan mengklasifikasikan sentimen masyarakat terhadap kebijakan efisiensi anggaran berdasarkan komentar dari media sosial Instagram. Tahapan penelitian meliputi pengumpulan data, pelabelan manual, cleaning, case folding, tokenizing, normalisasi, negation handling, stopword removal, stemming, pembobotan TF-IDF, klasifikasi dengan Naïve Bayes, dan pengujian. Sebanyak 1.408 komentar dari dua akun Instagram diklasifikasikan menggunakan metode Naïve Bayes Classifier dengan hasil akurasi 90,74%, presisi 85,16%, recall 98,51%, dan F1-score 91,35%. Penelitian ini diharapkan dapat dikembangkan dengan metode klasifikasi lainnya di masa depan.
Application of ADASYN Technique in Classification of Stroke Disease using Backpropagation Neural Network zikrillah aulia, said rizki; okfalisa, okfalisa; haerani, elin; oktavia, lola
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/jdhv9s39

Abstract

The high prevalence of stroke in Indonesia and the challenge of imbalanced medical record data are major obstacles to the development of an accurate early detection system. This research aims to build a reliable stroke classification model by applying the ADASYN (Adaptive Synthetic Sampling) oversampling technique to address class imbalance before the data is processed using the Backpropagation Neural Network (BPNN) algorithm. The ADASYN technique is applied with the goal of reducing the bias that arises from the imbalanced data distribution between the majority and minority classes. Testing was conducted through various data splitting scenarios (70:30, 80:20, 90:10) and hyperparameter variations to find the optimal configuration. The best results were obtained with the 90:10 data split scheme, using an architecture of 29 neurons and a learning rate of 0.01, which successfully achieved peak performance with an accuracy of 90.46% and an F1-score of 91.03%. This study demonstrates that the combination of ADASYN and BPNN is a highly effective approach for producing a stroke prediction model that is not only accurate but also sensitive to the minority class, thus having great potential as an early detection support tool in the healthcare sector.
Klasifikasi Sentimen Terhadap Topik Pindah Ibu Kota Negara Pada Twitter Menggunakan Metode Naïve Bayes Classifier Dermawan, Jozu; Yusra, Yusra; Fikry, Muhammad; Agustian, Surya; Oktavia, Lola
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 3 (2024): Maret 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7475

Abstract

Towards the middle of 2019, President Joko Widodo announced plans to relocate Indonesia's capital city. This caused pros and cons in the community, which were widely observed in various social media. To quickly measure the level of public sentiment towards the policy of moving the National Capital City (IKN), whose construction is already underway, a classification system that has good performance is needed. This research proposes a classification of public sentiment on the topic using the Naïve Bayes Classifier method. The data used in this study amounted to 4000 tweets that have been classified into two classes, namely 2000 positive class data and 2000 negative class data. The purpose of this research is how to apply the Naïve Bayes Classifier method in classifying sentiment on the topic of moving the nation's capital and determine the accuracy level of the method. The application of the Naïve Bayes classification method using TF-IDF features to classify 10% of the data as testing data resulted in an accuracy of 77.00%, for a precision value of 77.06%, recall 77.08% and f1-score of 77.00%. Based on the results achieved, the Naïve Bayes Classifier method is good at text classification tasks, with a fairly good accuracy rate.
Co-Authors -, Jasril Abdul Haris Kurnia Sandi Harahap Adrian Topano Alfaridzy, M. Audi Ananda, Rahmadan Alam Ardan Anugrah, Wendy Darmizal, Teddie Dermawan, Jozu Dinanti, Sri Wahyu Edo Saputra, Riski Elin Haerani Fitri Insani Fitri Wulandari Hasanah, Qomariah Jasril Jasril kurnia, fitra Lesmana, Aria Maulani, Tedi Muhammad Affandes Muhammad fauzan Muhammad Fikry Muhammad, Raja Allifin Nazir, Alwis Nazruddin Safaat H Novriyanto Novriyanto Okfalisa Okfalisa Okfalisa Prameswari, Putri Reski Mai Candra Saputra, Ikhsan Dwi Surya Agustian Wirayudha, Muhammad Aldi Yusra, Yusra Zahri, Firman zikrillah aulia, said rizki