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Jurnal Transformatika
Published by Universitas Semarang
ISSN : 16933656     EISSN : 24606731     DOI : -
Core Subject : Science,
Computer Science & IT
Transformatika is a peer reviewed Journal in Indonesian and English published two issues per year (January and July). The aim of Transformatika is to publish high-quality articles of the latest developments in the field of Information Technology. We accept the article with the scope of Information Systems, Web Technology, Computer Networks, Artificial Intelligence, and Multimedia.
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Articles 9 Documents
 1 
Search results for , issue "Vol. 22 No. 1 (2024): July 2024" : 9 Documents clear
Pengembangan E-Modul Berbantuan Flipbook Berbasis Literasi Untuk Mata Kuliah Statistika Kusumaningrum, Yulinda; Utomo, Victor Gayuh; Ellyawati, Hetty Catur; Maulana, Charis
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.10233

Abstract

Statistics is the basis for studying other subjects in the Informatics Engineering Study Program. However, some lecturers have not used teaching materials such as interactive modules to help students learn statistics. For this reason, research is needed which aims to (1) develop literacy-based Flipbook-assisted interactive e-modules in statistics courses that are valid, (2) determine the practicality of literacy-based Flipbook-assisted interactive e-modules in statistics courses for students. This type of research is Research and Development (R&D). The research subjects were 30 Informatics Engineering students taking Statistics courses. The development steps in this research are using ADDIE, namely Analysis, Design, Development, Implementation, and Evaluation. The research results obtained: 1) the literacy-based flipbook-assisted e-module that was developed was declared valid/feasible with an average percentage of material experts of 80% and media experts of 85.41%, 2) the flipbook-assisted interactive e-module that was developed met the criteria practically with a percentage reaching 75%.
Perbandingan Algoritma K-Means dan K-Medoids Untuk Clustering Harga Beras di Provinsi Jawa Tengah Setiaji, Galet Guntoro; Putri, Astrid Novita; Wicaksana, Dinar Anggit
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.10092

Abstract

Beras merupakan komoditas pangan utama bagi masyarakat di Indonesia khususnya di Jawa Tengah. Sebagai kebutuhan pokok, ketersediaan dan harga beras sangat mempengaruhi stabilitas ekonomi dan kesejahteraan masyarakat. Oleh karena itu, pemantauan dan analisis harga beras menjadi hal yang sangat penting. Salah satu hal dalam memahami harga beras adalah dengan melakukan clustering atau pengelompokan harga berdasarkan harga eceran beras medium. Clustering dapat memberikan gambaran lebih jelas variasi harga di jawa tengah metode yang digunakan yaitu K-Means dan K-Medoid dengan membandingkan metode  tersebut diharapkan mendapatkan informasi detail dan pola harga beras di berbagai daerah. Hasil yang didapatkan bahwa validitas DBI K-Means dengan K=3 dan K=5 lebih unggul dari pada menggunakan K-Medoids.
Pengembangan Media  Pembelajaran Statistika dan Probabilitas Berbasis Aplikasi Android Untuk Mendukung  Pembelajaran Hybrid Wicaksana, Dinar Anggit; Maulana, Charis; Gunata, Krida Pandu
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.10230

Abstract

Pada masa new normal membuat pembelajaran hybrid menjadi salah satu yang wajib dimanfaatkan dalam melakukan transfer ilmu pengetahuan kepada mahasiswa. Berdasarkan hasil ujian statistika dan probabilitas semester genap tahun 2023 menunjukkan bahwa 55% mahasiswa menerima nilai cukup (C). Mahasiswa masih kesulitan dalam menganalisis uji hipotesis, analisis regresi dan korelasi. Penelitian ini bertujuan menghasilkan produk media pembelajaran statistika berbasis android yang dapat mendukung pembelajaran hybrid. Jenis penelitian ini adalah model Research and Development. Produk divalidasi oleh dua ahli yaitu ahli materi dan ahli media pembelajaran. Instrumen yang digunakan berupa angket dengan menggunakan skala likert. Diperoleh hasil validasi untuk produk media pembelajaran statistika mahasiswa teknik informatika universitas semarang adalah sebesar 3,35 dengan kategori sangat valid.
Sistem Rekomendasi Film pada Platform Streaming Menggunakan Metode Content-Based Filtering Azri Saputra, Jeremia Maheswara; Huizen, Lenny Margaretta; Arianto, Dede Brahma
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.7041

Abstract

Sistem rekomendasi merupakan sebuah metode yang digunakan untuk memberikan rekomendasi pada sebuah produk seperti buku, musik dan film dengan memberikan nilai prediksi tertinggi pada penggunanya. Sistem Rekomendasi Film adalah sebuah sistem yang dapat memberikan rekomendasi-rekomendasi Film kepada pengguna sesuai dengan minat tonton pengguna. Jurnal ini dibuat dengan tujuan menciptakan Sistem Rekomendasi Film untuk membantu orang-orang dalam mencari Film yang mirip dengan Film kesukaan mereka. Rekomendasi Film dibuat dengan cara mencari kesamaan dari suatu Film, seperti genre nya.
Credit Risk Modeling Based on Geographical Location: A Case Study of Savings and Loan Cooperatives Widodo, Edi Widodo,; Rifai, Ahmad; Buana, Pratama Angga
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.9710

Abstract

The aim of this study is to examine how geographical location affects the credit risk faced by savings and loan cooperatives. Using a quantitative approach, this research will develop a credit risk model that considers geographical variables,measured by the Human Development Index (HDI). The initial stage of the research involves classifying the credit dataset according to the categoriesdetermined by Bank Indonesia. The data cleansing process resulted in attributes such as credit ceiling, HDI, and credit category. Analysis was conducted using Chi-Square, and Logistic Regression methods. The Chi-Square analysis results showed  statistically significant relationship between credit ceiling, HDI, and credit category (p-value < 0.05). The Logistic Regression models demonstrated high accuracy in classifying the data, with Logistic Regression achieving 89.71%. In conclusion, credit ceiling and HDI have a significant influence on credit category, with the Logistic Regression model data classification. This study provides valuableinsights into how credit ceiling and HDI influence credit categories, which can be used to make better decisions related to public policy, developmentplanning, and social interventions
Expert System for”Hypertension Disease Diagnoses Using Web Based Certainty Factor Method Laukamang, Vicky Olfianto N.; Prasetyo, Dwi; Sina, Derwin R.
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.8037

Abstract

Tekanan darah tinggi (hipertensi) merupakan kondisi di mana tekanan darah pada dinding arteri terlalu tinggi. Sampai saat ini, hipertensi menjadi isu kesehatan masyarakat, di mana jarang menimbulkan gejala yang jelas pada kesehatan. Hipertensi menjadi salah satu faktor resiko penyakit jantung koroner, gagal jantung, dan stroke. Hipertensi dikenal sebagai pembunuh secara tiba-tiba, karena seringkali penderita hipertensi tidak menyadari kondisinya dan baru mengetahuinya setelah melakukan pemeriksaan ke dokter dan mengalami komplikasi. Sistem pakar hadir sebagai sistem cerdas yang dapat digunakan sebagai solusi dan analisis dalam bidang medis, misalnya untuk mendiagnosis penyakit, pengguna dapat menggunakan sistem ini untuk mendiagnosis dan mendapatkan solusi terkait keluhan kesehatan yang mereka alami. Oleh sebab itu, sistem pakar ini dirancang, dibuat, dan dikembangkan untuk diagnosis dini penyakit hipertensi secara berbasis web dengan mengunakan metode certainty factor. Hasil pengujian sistem dengan menggunakan 100 data kasus, terbukti bahwa metode certainty factor mampu mendiagnosis penyakit hipertensi dengan tingkat akurasi mencapai 82%.
Penerapan Data Mining Dalam Strategi Bisnis Menggunakan Algoritma Apriori Bloemhard, Putri E; Pandie, Emerensye Sofia Yublina; Fanggidae, Adriana; Rumlaklak, Nelci Dessy; Widiastuti, Tiwuk; Sina, Derwin Rony; Nabuasa, Yelly Yosiana
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.10194

Abstract

Strategi yang diambil dalam mengelola bisnis kuliner sangat penting dalam memenangkan persaingan. Data transaksi penjualan dari Chicken Brotus selama tahun 2016 hingga 2023 memberikan gambaran penting mengenai pengelolaan strategi pemasaran dan manajemen persediaan. Dalam penelitian ini, algoritma Apriori digunakan untuk mencari hubungan antar item penjualan dalam satu dataset. Hasil pengujian terhadap 11.123 record data, dengan kombinasi nilai minimum support 8% dan minimum confidence 25% serta minimum support 10% dan minimum confidence 25%, menghasilkan pola analisis frekuensi dan aturan asosiasi. Analisis menunjukkan bahwa item terlaris adalah es teh jumbo dengan nilai support 46,5%. Selain itu, ditemukan bahwa jika konsumen membeli ayam geprek biasa komplit, maka 63,1% kemungkinan mereka juga akan membeli es teh jumbo. Hasil ini memberikan wawasan berharga bagi Chicken Brotus untuk mengembangkan strategi pemasaran dan pengelolaan persediaan yang lebih efektif dan efisien. Dengan demikian, Chicken Brotus dapat meningkatkan penjualan dan kepuasan pelanggan melalui strategi yang didasarkan pada data yang akurat dan analisis yang mendalam
Bootstrapped Aggregating Optimization in Random Forest for Hepatitis Risk HISWATI, MARSELINA ENDAH; DIQI, MOHAMMAD; SYAFITRI, ENDANG NURUL; FAUZIYYAH, ANNUR
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.9073

Abstract

This research optimizes the Random Forest model with Bootstrapped Aggregating to predict hepatitis risk. The global significance of hepatitis as a health problem is underscored by its widespread impact. Using a Kaggle dataset comprising 596 records and 20 attributes, including age categories and gender, the study identifies limitations in predicting hepatitis risk. Through hyperparameter optimization, such as adjusting the number and depth of trees, the Random Forest model with bootstrapped aggregate achieves an accuracy of 96%, surpassing the standard model's 88%. The results demonstrate a significant improvement in precision, recall, and f1 score, particularly in reducing false negatives. The conclusion highlights the practical potential of this model for a more accurate assessment of hepatitis risk. While acknowledging limitations related to the size of the dataset, these findings provide a foundation for developing predictive models in the context of hepatitis risk, emphasizing the importance of employing ensemble techniques to improve model performance.
Sistem Pakar Diagnosis Hama Dan Penyakit Tanaman Jeruk Keprok Menggunakan Metode Dempster Shafer Berbasis Web Buala, Adi Saldi
Jurnal Transformatika Vol. 22 No. 1 (2024): July 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v22i1.9084

Abstract

Soe Tangerines are a type of local orange from the Soe area and are one of the leading agricultural commodities in East Nusa Tenggara (NTT) Province. The fruit is round and small with an average diameter of between 5-7 cm. Oranges are an important need for Indonesian people. Although the harvest of these oranges has not yet reached its maximum potential, this is caused by several factors such as cultivation techniques, environmental conditions, as well as pest and disease attacks. These three factors can cause a decrease in productivity and even crop failure. Therefore, an expert system was designed using the Dempster Shafer method. This method aims to detect pests and diseases based on the symptoms that appear on Tangerine plants and provide solutions to overcome these problems. The goal is to reduce the risk of pest and disease attacks on plants. The test results used 50 case data from the TTS Regency Agriculture and Plantation Service. The system test results from 50 data produced 42 case data that were in accordance with the expert diagnosis, 6 data that were in accordance with the expert diagnosis but below the threshold of 80% and 8 data that were not appropriate. Testing system accuracy by comparing system and expert diagnosis results obtained accuracy results of 84%.

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