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All Journal Jurnal Biogenerasi (JIMBE) (JISCO) Journal of Information System and Computing
Grecia Trinatal Simbolon
Universitas Negeri Medan
Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Other

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Analisis Perbandingan Ekstrak Kulit Buah Naga (Hylocereus polyrhizus) dan Kunyit (Curcuma longa L.) Sebagai Indikator Identifikasi Boraks Pada Makanan Claudia Nainggolan; Eka Setiawan; Emon Sejahtera Zendrato; Grecia Trinatal Simbolon; Kania Restya Diva; Larasati Arum Utami; Rejeki Sihite
Jurnal Biogenerasi Vol. 11 No. 2 (2026): April - Juni 2026
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/sbjm5j61

Abstract

This study aimed to analyze and compare the effectiveness of red dragon fruit peel (Hylocereus polyrhizus) extract and turmeric (Curcuma longa L.) extract as natural indicators for detecting borax in food samples. The research used a laboratory experimental method with a qualitative descriptive approach. Food samples tested included sausages, ketupat, lontong, white tofu, crackers, siomay, meatballs, cilok, pempek, nuggets, white noodles, and yellow noodles. The testing process was conducted by dripping dragon fruit peel extract and turmeric extract onto each sample and observing the resulting color changes. The results showed that most samples tested negative for borax, while meatballs and yellow noodles indicated positive results. The color change in turmeric to reddish-brown occurred due to the reaction between curcumin and borax, while dragon fruit peel extract changed color because anthocyanin pigments are sensitive to pH changes. The findings indicate that both natural materials can be used as simple, inexpensive, safe, and effective natural indicators for the qualitative preliminary detection of borax in food. However, further quantitative testing is needed to obtain more accurate results.
Classification Analysis of Educational Access in Villages Based on School Facilities Using the Support Vector Machine Method with RStudio Aurelya Oktaven Radotia Simangunsong; Grecia Trinatal Simbolon; Riris Sihol Marito Sihombing; Sartika Magdalena Sihite
JISCO : Journal of Information System and Computing Vol 4 No 1 (2026): Journal of Information System and Computing
Publisher : UIN Sulthan Thaha Saifuddin Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30631/jisco.v4i1.5933

Abstract

Educational equity remains one of the major challenges in human resource development in Indonesia. Differences in the availability of educational facilities across regions may affect the quality of educational services and widendevelopment disparities. This study aims to classify educational access levels across regencies/cities in Central Kalimantan Province based on educational facility availability using the Support Vector Machine (SVM) algorithm. Aquantitative approach was employed using secondary data obtained from Statistics Indonesia (BPS) in 2025, consisting of the number of elementary schools, junior high schools, senior high schools, vocational schools, and higher education institutions across 13 regencies/cities. The research procedures included data preprocessing, Min-Max normalization, category labeling usingtertile classification, training-testing data splitting, and SVM model  development. Model performance was evaluated using a confusion matrix and accuracy measurement. The findings indicate that most regencies/cities fallwithin the moderate educational access category, while only a few belong to the high and low categories. The SVM model successfully identified patterns in the distribution of educational facilities with a very high level of accuracy. These results demonstrate the potential of machine learning approaches as decisionsupport tools for educational development planning. Practically, the findings can assist policymakers in prioritizing educational infrastructure development in underserved regions 
Pengembangan Media Pembelajaran Berbasis MicroLearning pada Materi Nilai Eigen dan Vektor Eigen Aurelya Oktaven Radotia Simangunsong; Grecia Trinatal Simbolon; M. Hendro Saputra; Riris Sihol Marito Sihombing; Sartika M. Sihite
Jurnal Ilmu Manajemen, Bisnis dan Ekonomi Vol 4 No 1 (2026): Juni
Publisher : PT Maju Malaqbi Makkarana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59971/jimbe.v4i1.1177

Abstract

Penelitian ini bertujuan untuk mengembangkan media pembelajaran berbasis MicroLearning pada materi Nilai Eigen dan Vektor Eigen serta mengevaluasi penggunaannya sebagai media pembelajaran pendukung dalam mata kuliah Aljabar Linear. Penelitian ini menggunakan metode Research and Development (R&D) dengan model ADDIE yang meliputi tahap analysis, design, development, implementation, dan evaluation. Produk yang dikembangkan terdiri atas video explainer, infografis, dan motion graphic. Responden penelitian berjumlah 20 mahasiswa Program Studi Statistika yang telah menempuh mata kuliah Aljabar Linear. Media pembelajaran dibagikan melalui WhatsApp dan evaluasi dilakukan menggunakan Google Form yang berisi 7 soal pilihan ganda. Data dianalisis secara deskriptif menggunakan frekuensi, persentase, nilai rata-rata, nilai tertinggi, dan nilai terendah. Hasil penelitian menunjukkan bahwa sebanyak 15 mahasiswa (75%) memperoleh minimal 5 jawaban benar sehingga dikategorikan memahami materi, sedangkan 5 mahasiswa (25%) belum mencapai batas ketuntasan. Nilai rata-rata yang diperoleh responden adalah 5,05 dengan nilai tertinggi 7 dan nilai terendah 2. Hasil tersebut menunjukkan bahwa media pembelajaran berbasis MicroLearning yang dikembangkan mampu membantu mahasiswa memahami materi Nilai Eigen dan Vektor Eigen dengan cukup baik. Oleh karena itu, media pembelajaran berbasis MicroLearning dapat menjadi alternatif pembelajaran yang efektif untuk mendukung proses pembelajaran Aljabar Linear.
Co-Authors Aurelya Oktaven Radotia Simangunsong Claudia Nainggolan Eka Setiawan Emon Sejahtera Zendrato Kania Restya Diva Larasati Arum Utami M. Hendro Saputra Rejeki Sihite Riris Sihol Marito Sihombing Sartika M. Sihite Sartika Magdalena Sihite