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All Journal International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI)
Fatika La Viola Ifanka
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering

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MONITORING DASHBOARD USING LINEAR REGRESSION FOR EMPLOYEE PERFORMANCE Muhammad Oktoda Noorrohman; Mochammad Ilham Aziz; Saifulloh Azhar; Satria Pradana Rizki Yulianto; Widodo; Devi Ratnasari; Fatika La Viola Ifanka; Melvien Zainul Asyiqien
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 11 (2025): OCTOBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijset.v4i11.1101

Abstract

Company management needs to continuously monitor and measure the performance of its employees to ensure the achievement of the goals that have been set. The performance monitoring process requires data and information obtained from 35 employees. The problem is in the process of the employee payroll system, attendance, leave and the main thing is data management for monitoring employees still use conventional method by manual. The results of performance monitoring will then be conveyed to interested parties, efficiently and effectively. After that, the existing data were analyzed using SPSS which stands for Statistical Product and Service Solution. Validity testing can also be done using SPSS and produces a validity test of the data, which is < 0.05 so it is valid. The reliability test of the data is > 0.70, 0.751 for employee salaries and 0.757 for employee performance so it is reliable. The normality test of the data are > 0.05, 0.077 for employee salaries and 0.059 for employee performance so that the data is normally distributed. The linearity test of the data is 0.604 > 0.05, it can be concluded that there is a linear relationship between salary and employee performance. Regression analysis test simple linear data from the data, namely the significance level of 0.001 < 0.05 then the regression model can be used to predict the participation variable or in other words there is an effect of the salary variable on the performance variable.
ANALYSIS OF PATIENT ATTENDANCE RATES USING RUSBOOST Widodo; Dyah Ika Krisnawati; Saifullah Azhar; Fatika La Viola Ifanka; Muhammad Ilham Aziz; Satria Pradana Rizky Yulianto; Devi Ratnasari; Muhammad Oktoda Noorrohman
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 11 (2025): OCTOBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijset.v4i11.1110

Abstract

Patients have the option of undergoing examinations and treatment without having to stay in the hospital. The number of clinics serving patients continues to grow due to the high demand and busy schedules faced by patients. However, hospitals and clinics are still operating well because there are patients who need services, both outpatient and inpatient. In many countries, numerous clinics and hospitals have not implemented an effective data management system for outpatient queues. This results in a number of registered patients not showing up for their appointments, which is certainly detrimental to the nurses and doctors on duty that day. This situation is a loss for clinics and hospitals because manual data management prevents them from predicting the number of patients who will visit. One way to organize patient visit data, both for outpatient and inpatient care, is to utilize big data. The method used in processing this data is Decision Tree classification with Rusboost. By applying Decision Tree classification and Rusboost, we can obtain more accurate predictions, thereby assisting in decision-making.
Evaluasi Kematangan Tata Kelola TI Menggunakan COBIT 4.1 pada Diskominfo Kota Probolinggo Muhammad Oktoda Noorrohman; Mochammad Ilham Aziz; Widodo; Stevanus Gatot Supriyadi; Fatika La Viola Ifanka; Melvien Zainul Asyiqien
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.975

Abstract

Pemanfaatan teknologi informasi (TI) pada instansi pemerintah seringkali menghadapi kendala dalam hal tata kelola yang tidak terstandarisasi, sehingga menghambat efektivitas layanan publik. Penelitian ini bertujuan untuk mengevaluasi tingkat kematangan tata kelola TI pada Dinas Komunikasi dan Informatika (Diskominfo) Kota Probolinggo dengan menggunakan kerangka kerja COBIT 4.1. Peneliti mengarahkan fokus evaluasi pada domain Deliver and Support (DS) untuk menilai aspek operasional dan keamanan, serta domain Monitor and Evaluate (ME) untuk menilai pengawasan kinerja TI. Peneliti menggunakan metodologi penelitian yang meliputi pengumpulan data melalui kuesioner, wawancara mendalam terhadap pemangku kepentingan yang ditentukan melalui diagram RACI, dan observasi lapangan. Hasil penelitian menunjukkan bahwa rata-rata tingkat kematangan saat ini (current maturity level) untuk domain DS adalah 1,61 dan domain ME sebesar 1,25. Temuan ini mengindikasikan bahwa proses tata kelola TI di Diskominfo Kota Probolinggo berada pada level Initial/Ad Hoc hingga Repeatable but Intuitive, di mana pengelolaan masih bersifat reaktif, belum terorganisir secara rutin, dan sangat bergantung pada inisiatif individu. Berdasarkan hasil tersebut, peneliti mengajukan rekomendasi strategis berupa standarisasi prosedur operasional, pengelolaan kapasitas sumber daya manusia, serta penguatan audit internal guna mencapai tingkat kematangan yang diharapkan organisasi.
Co-Authors Devi Ratnasari Krisnawati, Dyah Ika Mega Fatimah Rosana Melvien Zainul Asyiqien Mochammad Ilham Aziz Muhammad Oktoda Noorrohman Saifullah Azhar Satria Pradana Rizki Yulianto Satria Pradana Rizky Yulianto Stevanus Gatot Supriyadi Widodo