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All Journal Jurnal Riset Multidisiplin dan Inovasi Teknologi JoET
Tuljannah, Jamila
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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Test of Escherichia Coli and Total Microbes on Burger Meat Sold in Kedinding and Pogot Villages, Surabaya, East Java Tuljannah, Jamila; Hartati, Fadjar Kurnia
Jurnal Riset Multidisiplin dan Inovasi Teknologi Том 2 № 01 (2024): Jurnal Riset Multidisiplin dan Inovasi Teknologi
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/jimat.v2i01.367

Abstract

A burger is a type of fast food that consists of a bun in the middle that contains a patty (ground beef), vegetables, and some sauce. There are several parameters in determining food quality and safety, one of which is analyzing the content of microbiology such as bacteria, viruses, and protozoa in food. Biological hazards, especially in food, need special attention because they are often the causative agents of food poisoning cases. This study aims to determine Eschericia coli contamination and Total Plate Number (TPC) in burger meat samples sold in Kedinding and Pogot villages, Surabaya, East Java. This research is observational with a cross sectional approach. The inspection method used to determine Escherichia coli contamination and the Total Plate Count (TPC) is the Most Likely Number method to determine E. coli and the Total Plate Count (TPC). The results of this study showed that there was no E. coli in all burger meat samples and there were 6 burger meat samples contaminated with bacteria, namely in Samples A, B, C, G, H and I, which exceeded the contamination limit according to to SNI 8503 (2018).
A Systematic Literature Review: Human Resource Analytics For Predicting Employee Turnover Using Machine Learning Multazam, Achmad; Arini, Devi Febrianti; Itabashi, Kazuki; Tuljannah, Jamila; Fatimah, Nuzulul; Putra, Riyan Sisiawan
Journal of Entrepreneurship & Technopreneurship Vol. 3 No. 1 (2026): September
Publisher : STMIK Dharmapala Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47927/joet.v3i1.1493

Abstract

Employee turnover merupakan salah satu permasalahan penting dalam manajemen sumber daya manusia karena dapat meningkatkan biaya operasional, menurunkan stabilitas organisasi, serta mengganggu produktivitas kerja. Penelitian ini bertujuan untuk menganalisis peran Human Resource (HR) Analytics dalam memprediksi employee turnover dalam konteks manajemen sumber daya manusia strategis. Metode yang digunakan adalah Systematic Literature Review (SLR) mengacu pada pedoman PRISMA, dengan HR Analytics sebagai variabel X dan employee turnover prediction sebagai variabel Y. Data sekunder diambil dari referensi Google Scholar, Scopus, dan ScienceDirect dengan periode publikasi lima tahun terakhir. Berdasarkan tinjauan literatur terhadap 8 artikel yang memenuhi kriteria, hasil penelitian menunjukkan bahwa penerapan HR analytics yang dikombinasikan dengan teknik machine learning seperti Random Forest, XGBoost, Artificial Neural Networks, dan ensemble learning mampu meningkatkan akurasi prediksi employee turnover serta mengidentifikasi faktor-faktor utama yang mempengaruhi keputusan karyawan untuk keluar dari organisasi, seperti kepuasan kerja, kompensasi, masa kerja, dan lingkungan kerja.
Co-Authors Arini, Devi Febrianti Fadjar Kurnia Hartati, Fadjar Kurnia Itabashi, Kazuki Multazam, Achmad Nuzulul Fatimah Riyan Sisiawan Putra