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All Journal Jurnal Simetris Telematika SISFOTENIKA Prosiding SNAST Journal of Computer Science and Technology (JCS-TECH)

Mariana Windarti

Universitas Widya Dharma Klaten

Author-ID : 2538320

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Articles

Korelasi Nilai UAN, IP Tahun Pertama Terhadap Masa Studi Dengan Backpropagation Mariana Windarti; Istri Sulistyowati
SISFOTENIKA Vol 9, No 2 (2019): SISFOTENIKA
Publisher : STMIK PONTIANAK

Pada pendidikan tinggi prestasi akademik dapat dilihat dari nilai Indeks Prestasi Kumulatif (IPK) dan masa studi sedangkan pada pendidikan sekolah menengah ditunjukkan dengan nilai Ujian Akhir Nasional (UAN) atau Ujian Nasional (UN). Hubungan beberapa variabel seperti nilai UAN, IP dan masa studi dapat dinyatakan dengan mengukur tingkat korelasi menggunakan sejumlah data mahasiswa. Data yang digunakan dalam penelitian ini adalah data alumni program studi Teknik Informatika Universitas Widya Dharma Klaten dengan tahun lulus 2013-2017. Tujuan penelitian untuk mengukur tingkat korelasi antara atribut nilai UAN dan IP tahun pertama terhadap masa studi mahasiswa menggunakan metode jaringan syaraf tiruan backpropagation yang diterapkan pada perangkat lunak Matlab r2013a. Pada proses pelatihan jaringan, penelitian ini menghasilkan nilai MSE (Mean Square Error) sebesar 0.0051721 dan koefisien korelasi (R=0.56563). Sedang pada proses pengujian nilai MSE = 0.025073 dan R = -0.031142. Selain itu hasil ini membuktikan bahwa nilai UAN dan IPK tahun pertama memiliki korelasi negatif terhadap masa studi mahasiswa.Kata kunci — korelasi , data mining, masa studi, backpropagation

Perbandingan Kinerja 6 Algoritme Klasifikasi Data Mining untuk Prediksi Masa Studi Mahasiswa Mariana Windarti; Agustinus Suradi
Telematika Vol 12, No 1: Februari (2019)
Publisher : Universitas Amikom Purwokerto

Salah satu faktor yang memengaruhi kualitas sebuah perguruan tinggi adalah kinerja mahasiswa yang dapat diukur melalui lamanya masa studi. Perolehan pengetahuan dalam basis data (sejumlah data yang besar) biasa disebut dengan data mining atau penambangan data. Penelitian ini bertujuan untuk mengetahui kinerja keenam algoritme klasifikasi yang digunakan yaitu Decision Tree (DT) C4.5, Bayesian Network (BN), K-Nearest Neighbors (KNN), Naïve Bayes (NB), Neural Network (NN) dan SVM (Support Vector Machine). Kemudian menganalisa perbandingan kinerja keenam algoritme tersebut. Hasil penelitian menunjukkan bahwa Bayesian Network memiliki kinerja paling baik dengan nilai akurasi sebesar 80.615%, nilai presisi dan recall sebesar 0.785 dan 0.806, sedang untuk nilai AUC (Area Under Curve) termasuk dalam kategori baik yaitu 0.837. Sedangkan DT C4.5 memiliki kinerja terendah dengan nilai akurasi sebesar 76.615%.

PENERAPAN MODEL DELONE DAN MCLEAN PADA SI-PMB ONLINE DARI PERSPEKTIF PENGGUNA UNTUK MENINGKATKAN KUALITAS LAYANAN Agustinus Suradi; Mariana Windarti Windarti
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 11, No 1 (2020): JURNAL SIMETRIS VOLUME 11 NO 1 TAHUN 2020
Publisher : Universitas Muria Kudus

Inovasi strategi pengembangan sistem informasi perlu dikembangkan untuk mendukung kesuksesan dan kualitas layanan sistem penerimaan mahasiswa baru. Masyarakat pengguna sistem informasi penerimaan mahasiswa baru sering mengalami kesulitan ketika mencari informasi yang mereka butuhkan. Tujuan penelitian ini untuk mengidentifikasikan kesuksesan sistem informasi penerimaan mahasiswa baru (SI-PMB) online dan variabel-variabel yang mempengaruhinya. Model DeLone McLean IS Success model digunakan dalam penelitian ini, dengan komponen variabel seperti: information quality, system quality dan service quality. Analisis data yang digunakan adalah model struktural dengan alat analisis Partial Least Square (PLS) menggunakan software Smart PLS. Hasil dari penelitian diperoleh hubungan variabel Information Quality à User Satisfaction, dengan nilai t statistik 0,324, hubungan variabel Service Quality àUser Satisfaction, nilai t statistic 2,530, dan hubungan variabel System Quality à User Satisfaction, nilai t statistik 3,107, sehingga dapat disimpulkan bahwa terdapat hubungan positif dan siginifikan antara variabel system quality dan user satisfaction, terdapat hubungan positif dan siginifikan antara variabel service quality dan user satisfaction. Hubungan variabel User Satisfaction à Net Benefits, nilai t statistik 8,708 menyatakan bahwa ada hubungan positif dan siginifikan antara variabel kepuasan pengguna (user satisfaction) dengan manfaat-manfaat bersih (net benefit).

PERBANDINGAN KINERJA ALGORITMA NAIVE BAYES DAN BAYESIAN NETWORK DALAM KLASIFIKASI MASA STUDI MAHASISWA Mariana Windarti
PROSIDING SNAST Prosiding SNAST 2018
Publisher : IST AKPRIND Yogyakarta

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

One factor that influences the quality of college is that student performance can be measured through the length of the study period. The faster study period of student, then better student's performance, and vice versa. Data mining can be interpreted as a process to get useful information from large amount of data so that a knowledge is obtained. This research aims to analyze the comparative performance of probabilistic algorithms namely Naïve Bayes (NB) and Bayesian Network (BN) to classifying the student study period of Universitas Widya Dharma (UNWIDHA) Klaten. Variables for classification are Achievement Index (IP) (1st semester, 2nd semester, and 3rd semester), student school majors and college entrance path. The data used in the form of data are 100 graduates of UNWIDHA. Classification of student study period consisting of study periods <4 years, ≥ 4 & <4.5 years, ≥ 4.5 & <5 years, ≥ 5 & <5.5 years, ≥ 5.5 & <6 and ≥ 6 years. . The results showed that the precision value and recall, BN algorithm were better than NB. On performance measurement with percentage split 90, NB and BN algorithms have the same accuracy value of 80%. Whereas in percentage split 80, BN is superior with an accuracy of 75% while NB is 70%.

SISTEM PAKAR PENDIAGNOSA PENYAKIT DIABETES MELITUS MENGGUNAKAN FORWARD CHAINING Depi Trisnawati; Mariana Windarti; Istri Sulistyowati; Fajar Budi Hartono
Journal of Computer Science and Technology Vol 2 No 1 (2022): Mei 2022
Publisher : LPPM Universitas Widya Dharma

Diabetes is a disease that causes death which is quite high in the world, even in Indonesia, this is indicated by the position of Indonesia with the highest number of diabetic patients, which is 7th out of 10 countries. Diabetes Mellitus is also a chronic disease that is a public health problem in Indonesia. By 2020, the number of diabetes attacks will reach 18 million. The increasing use of computer technology causes the rapid flow of information and communication from one place to another. One application of technology is an expert system. This expert system is used for early detection of the type of disease suffered by the patient based on the symptoms caused without having to go to the doctor. In this study, an expert system for diagnosing diabetes mellitus will be designed. The method used is the forward chaining inference method and Microsoft Visual FoxPro 9.0 software. The forward chaining method works by analyzing the facts obtained from the input based on the rules stored in the database to get a conclusion. This expert system for diagnosing diabetes mellitus is used by the community as a tool for early detection without having to consult directly with a doctor. The conclusion or solution obtained from this expert system is that the user is predicted to have diabetes or does not have mild or secondary diabetes along with the results of the diagnosis according to the solution provided by the system

VISUALISASI GLOBAL WARMING UNTUK SD DENGAN ADOBE FLASH CS Rohmawati; Rizka Safitri Lutfiyani; Mariana Windarti
Journal of Computer Science and Technology Vol 1 No 1 (2021): November 2021
Publisher : LPPM Universitas Widya Dharma

One of the obstacles of elementary school learning process is there of material that cannot be directly observed by students. Childrens quickly get bored and not focus on materials like that. Science is one of the subject that has a lot of material that cannot be directly observed, example a global warning. Through learning media with visualization, it be expected that the material can be delivered well. There are four stages of this research, that is data requirenment, design, implementation and testing. The techniques used at the data requirenment stage are interviews and observations. Meanwhile, at the design stage, storyboards and other designs of this learning media were made. In the third stage, the previously created design is implemented by the Adobe Flash CS3 application. The final stage, the results of the design are examined by means of a questionnaire. The result of this research is a learning media made with lots of visuals so that students stay focused on the material. The suggestion of this research is that this research can be developed using a smartphone, android.

A APLIKASI SISTEM PARKIR UNIVERSITAS WIDYA DHARMA KLATEN Hendro Joko Prasetyo; Mariana Windarti; Agustinus Suradi; Istri Sulistyowati
Journal of Computer Science and Technology Vol 2 No 2 (2022): November 2022
Publisher : LPPM Universitas Widya Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54840/jcstech.v2i2.4

The parking management information system at Widya Dharma University Klaten is a form of parking information system to collect data and parking arrangements whose application plans will be used at Widya Dharma University Klaten. The purpose of this study is to create a parking system application that can later be used as a parking system aid which is computerized so that it is expected to be more efficient and have efficiency values that can improve service quality and increase income. The research method uses direct observation, while also reading the literature or literature. In this study, namely the implementation of parking management with computerized data collection of vehicle numbers. Research materials and materials include data on parking locations, population of parking vehicles which include cars or motorbikes in the Widya Dharma University area. This design software uses Microsoft Visual Foxpro 9.0 application software, for database design using SQL Server 2000, Microsoft Office 2007 (Word, Excel, Powerpoint, Visio). The results of this study are a computerized Parking System Application which can later be used by Widya University Dharma Klaten so that it is expected to be able to produce information quickly, save time and also for prevention efforts against vehicle theft in the Widya Dharma Klaten University campus. In addition, it can be used to calculate how much rupiah is generated, if there is an activity such as a graduation ceremony, so that the distribution of results can be evenly distributed and there is no mutual suspicion between parking officers (security guards). Keywords: Parking Information System, Microsoft Visual Foxpro 9.0, SQL Server 2000

Co-Authors Agustinus Suradi Depi Trisnawati Fajar Budi Hartono Hendro Joko Prasetyo Istri Sulistyowati Rizka Safitri Lutfiyani Rohmawati

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