Garuda - Garba Rujukan Digital

p-Index From 2019 - 2024

0.882

P-Index

This Author published in this journals

All Journal Kilat Journal of Students‘ Research in Computer Science (JSRCS) INCOME: Indonesian Journal of Community Service and Engagement Journal Of Computer Science Contributions (JUCOSCO)

Dian Hartanti

Informatika; Universitas Bhayangkara Jakarta Raya

Author-ID : 6187251

Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Social Sciences Other

Published : 8 Documents Claim Missing Document

Claim Missing Document

Articles

Title

Penetapan Titik Pendeteksi Antrian Kendaraan Pada Perempatan Lampu Lalu Lintas Dian Hartanti; Wisnu Hendro Martono
KILAT Vol 5 No 2 (2016): KILAT
Publisher : Sekolah Tinggi Teknik - PLN

More dense motor vehicle on the highway will cause a jam. situation where there is accumulation of a motor vehicle was at the time in traffic lights or also called traffic light. Intersection have time to switch the traffic lights that remain in each lane felt less effective because each lane has a different traffic density. Determination of the working area at the intersection of Matraman the survey results for a number of locations in Central Jakarta around each intersection. With data collection for some time with the details of the current condition of the morning, afternoon and evening in every weekday obtained a detailed picture of differences in real conditions. Furthermore, by applying the ISO 7391 (2008) on the specification of street lighting in Urban Area and the rule of PU on the highway, the traffic volume average daily DGH DGH, as well as the use of algorithms Greedy acquired unit quantities dead time live traffic light then can determine the distance sensor placement. From the amount of time living and dead traffic lights can then be developed algorithms and data structures that will be used in the design of software programs intelligent traffic lights

Analisis Faktual Keterbatasan Pemanfaatan Sarana Dan Prasarana Penunjang Proses Belajar Mengajar Dilingkungan STT PLN Rahma Farah Ningrum; Puji Catur Siswipraptini; Dian Hartanti
KILAT Vol 5 No 2 (2016): KILAT
Publisher : Sekolah Tinggi Teknik - PLN

PLN Engineering of College (STT PLN) is a campus that has a big potential to continue to grow, especially in the Department of Information Engineering. Along with the continued increase in students, to impact the use of campus facilities and infrastructure for the learning process and also more dense lecture scheduling process. This study aims to find an effective solution to the limitations of the use of infrastructures means that the learning process can run smoothly. To avoid inconsistencies in the modeling, then the Focus Group Discussion (FGD) against the criteria, sub-criteria and strategic alternatives with respondents to determine the stage of making a valid model with significant elements that affect models. Results obtained from the questionnaire FGD are significant criteria, sub-criteria significant, and significant alternatives that make up the decision making process. Data processing respondents in this FGD, processed using statistical methods conchrant Q test. Having obtained the criteria, sub-criteria and strategic alternatives valid next step using Analytical Hierarchy Process (AHP) to the data processing using Expert Choice program in 2000.

Model Clustering Menggunakan Algoritma K-Means Pada Data Keluhan Pelanggan PT. PLN (Studi Kasus : PT. PLN (Persero) Distribusi Jakarta Dan Tangerang) Dian Hartanti
KILAT Vol 4 No 1 (2015): KILAT
Publisher : Sekolah Tinggi Teknik - PLN

Data mining adalah proses mengubah sejumlah besar data sampai menghasilkan keterhubungan antar isi data, proses pengelompokkan data (data clustering) menjadi sangat penting karena adanya peningkatan jumlah data dalam format teks yang cukup signifikan. Pengelompokkan data bertujuan membagi data dalam beberapa kelompok (cluster) sedemikian hingga data-data dalam cluster yang sama (intra-cluster) memiliki derajat kesamaan yang tinggi, sementara data-data dalam cluster yang berbeda (inter-cluster) memiliki derajat kesamaan yang rendah. Model clustering data gangguan yang dirancang dengan metode algoritma k-means, model aplikasi ini dapat menampilkan gambaran dan menunjukan pola sebaran data keluhan pelanggan.

Co-Authors Abrar Hiswara Achmad Noe’man Hafizah Hafizah Hantoro, Kusdarnowo Marni Ardilla Ningrum, Rahma Farah Siswipraptini, Puji Catur Wisnu Hendro Martono

Title Search

Found 3 Documents Search Journal : Kilat

Abstract

Abstract

Abstract

Title

Found 3 Documents
Search
Journal : Kilat