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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Kursor Jurnal Teknologi Infotech Journal JURNAL MEDIA INFORMATIKA BUDIDARMA InComTech: Jurnal Telekomunikasi dan Komputer Jurnal Tekno Insentif Jurnal Manajemen Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS
Nisa Hanum Harani
Politeknik Pos Indonesia
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Social Sciences Other

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KANSA: high interoperability e-KTP decentralised database network using distributed hash table Rolly Maulana Awangga; Nisa Hanum Harani; Muhammad Yusril Helmi Setyawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 3: June 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i3.11758

Abstract

e-KTP is an Indonesian Identity Card based on Near Field Communicator technology. This technology was embedded in every e-KTP card for every Indonesian citizen. Until this research, e-KTP technology never to be utilized by any stack-holder neither government agencies nor nongovernment organization or company. e-KTP Technology inside the card never been used and go with conventional with manual copy it with photocopy machine or take a photograph with it. This research was proposing an open standard to utilized e-KTP Technology. The open standard will bring e-KTP technology used as is and used broadly in many government agencies or much commercial company. This research was proposing decentralized network model especially for storing e-KTP data without breaking privacy law. Besides providing high specs of the server, a decentralized model can reduce the cost of server infrastructure. The model was proposing using Distributed Hast Table which was used for peer-to-peer networks. The decentralized model promised high availability and the more secure way to save and access the data. The result of this model can be implemented in many network topology or infrastructure also applicable to implement on Small Medium Enterprise Company.
KAFA: A novel interoperability open framework to utilize Indonesian electronic identity card Rolly Maulana Awangga; Nisa Hanum Harani; Muhammad Yusril Helmi Setyawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.11755

Abstract

Indonesian people have electronic citizen card called e-KTP. e-KTP is NFC based technology embedded inside Indonesian citizenship identity card. e-KTP technology has never been used until now since it was launch officially by the government. This research proposes an independent framework for bridging the gap between Indonesia regulation for e-KTP and commercial use in the many commercial or organization sector. The Framework proposes interoperability framework using novel combination component, there are e-KTP reader, Middleware and Web Service. KAFA (e-KTP Middleware and Framework) implementing Internet of Things (IoT) concept to make it as open standard and independent. The framework use federation mode or decentralized data for interoperability, to make sure not breaking the law of privacy. Extended development of AES-CBC cipher algorithm was used to encrypt the data on the transport between middleware and web service.
Electronic Data Interchange (EDI) Applications Use the Decision Tree Method to Determine Vendor Recommendations Mariana Rospilinda Siki; Nisa Hanum Harani; Cahyo Prianto
Jurnal Ilmiah Kursor Vol 10 No 2 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v10i2.217

Abstract

Electronic Data Interchange (EDI) is an electronic data exchange mechanism between a company and another company or Business to Business (B2B) in a supply chain cycle. In this study, EDI's role in managing the procurement of goods as well as the EDI model has been applied. Determination of vendor recommendations is one element of vendor performance evaluation of the procurement process. Lack of information and analysis obtained by PT. Cinovasi Rekaprima makes it difficult to predict vendor recommendations. Predicted vendor recommendations can help the Procurement Division in developing appropriate strategies to determine recommended vendors. This problem can be applied to data mining techniques to make predictions using the classification method. Decision Tree is a method that converts facts into decision trees that represent rules that can be interpreted by humans. Attributes that influence the determination of vendor recommendations consist of the availability of goods, services, ease of ordering and product quality. Sample data obtained directly from the Procurement Division of PT. Cinovasi Rekaprima is primary data in the form of vendor data (quotation) and secondary data in the form of vendor performance evaluation forms. The result of the EDI application is a classification consisting of 2 classes, namely recommended vendors and non-recommended vendors and the Procurement Division can use it for decision making to determine the right vendor, so that the procurement process becomes easier and increases company profitability. The testing model uses k-fold cross-validation with the k value is 1 to 10 fold. This application can determine vendor recommendations with the highest accuracy 87.00 % on k-3 and k-5 fold.
Implementation of Multiple Linear Regression Methods as Prediction of Village Spending on Village Financial Management System Nisa Hanum Harani; Hanna Theresia Siregar; Cahyo Prianto
Jurnal Ilmiah Kursor Vol 10 No 2 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v10i2.216

Abstract

The realization of village welfare and improvement of Village development can be started from the financial management aspects of the village. The village government has authority ranging from planning, implementation, reporting to accountability. There are two important variables as the financial aspects, there is village income, and village expenditure. The village budget process is a plan that will be compiled systematically. Planning has an association with predictions which is an indication of what is supposed to happen and predictions relating to what will happen. To provide a good village budget planning the village budget prediction feature is required. This prediction feature is done using data mining which is modeled i.e. multiple linear regression algorithm. The variable is selected using a purposive sampling technique and the sample count is 29 villages. Dependent variables are village Expenditure as Y, and independent variables i.e. village funds as X1 and village funding allocation as X2. The best values as validation were gained in the 3rd fold with a correlation coefficient of 0.8907, Mean Absolute Error value of 87209395.37, the value of Root Mean Squared Error of 114867675.6, Roll Absolute Error (RAE) Percentage was 42 %, and Root Relative Squared Error was 44 %.
Segmentasi Pelanggan Produk Digital Service Indihome Menggunakan Algoritma K-Means Berbasis Python Nisa Hanum Harani; Cahyo Prianto; Fikri Aldi Nugraha
Jurnal Manajemen Informatika (JAMIKA) Vol 10 No 2 (2020): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v10i2.2683

Abstract

Telekomunikasi Indonesia is one of the companies that prioritize customers, but there is no information about customer characteristics. In this research, an analysis of customer characteristics used as a basis for determining customer segmentation and customer profiling for digital products add on Indihome services using the K-Means Algorithm. Determination of the best number of clusters done using the Elbow method and a value of K = 3 obtained, so that customer data grouped into three segments. Customer data processing is divided into 3 simulations with the percentage of train data and test data 80% - 20%, 70% - 30% and 50% - 50%. The data used totaled 1392 records as a population where the data will used to find the characteristics of each data. Cluster evaluations carried out using the Silhouette Index, Davies Bouldin Index, and Calinski Harabasz Index methods. The results of the study show that the third simulation is the best based on cluster evaluation with 50% data train presentation and 50% data test where customer profiling is seen by analyzing the members of each cluster from the third simulation where cluster 0 has 396 customer members with a customer category that provides the biggest profit for the company, cluster 1 has members of 286 customers in the category of customers who unwittingly have great potential in providing benefits for the company, and cluster 2 has a member of 14 customers in the customer category that provides fewer benefits than the cost of providing services.
Pemetaan Pelanggan IndiHome Sebagai Daerah Sasaran Promosi (Studi Kasus : Witel Bandung) Nisa Hanum Harani; Cahyo Prianto; Andri Fajar Sunandhar
Jurnal Manajemen Informatika (JAMIKA) Vol 10 No 2 (2020): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v10i2.2738

Abstract

In this globalization era, marketing communication is very important to help increase sales promotion of indihome digital service products by utilizing customer location points that use indihome services. Currently there are many information systems that are used to support and solve problems in determining the location of a place. Determination of location can be done using mapping. The mapping of Indihome customers is done by utilizing a map provided by Google, the Google Maps API based on the address of the Indihome service customer. Therefore, we need a system to find out which areas use the most indihome services, so that it will make it easier to target promotions for indihome customers who have not used to add services to Indihome such as Movin, Indihome Gamers, Indihome Music, Indihome Music, Indihome Studies, Indihome Storage, Indihome Servers, Video Calls, and other additional packages. The results of this mapping can determine areas / regions that have the potential to be promoted in connection with the addition of indihome service products, so that it will have an impact on increasing customers and sales revenue of Add On products.
Analisis Sentimen Terhadap Kandidat Presiden Republik Indonesia Pada Pemilu 2019 di Media Sosial Twitter Cahyo Prianto; Nisa Hanum Harani; Indra Firmansyah
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i4.1549

Abstract

The development of technology today has been growing rapidly and has an impact on the behavior patterns of people who feel it. The Ministry of Communication and Information (KOMINFO) released a data that of 265 million people of Indonesia, there are around 54% have used internet technology or about 143 million people. In one survey IDN Research Institute said that there are three Social Media that are widely used in Indonesia, namely Facebook, Instagram and Twitter. This study focuses on extracting data in the form of text produced from social media twitter that responds to the account of the RI presidential candidates in the 2019 elections. Sentiment analysis is obtained through tweet classification using sentiment analysis tools such as NRC Lexicon and Bing Lexicon so that information is obtained in the form of positive polarity and negative polarity from community tweets towards the Presidential candidates in the 2019 elections. Using March data before the 2019 election, for candidate 01 Joko Widodo, the NRC Lexicon analysis gave a value of 249 and bing lexicon of 267 with an average value of 0.11, while for candidate 02 Prabowo Subianto the NRC Lexicon analysis gave a value of 195 and bing lexicon of 204 with an average value of 0.085. Using april data after the 2019 election. Candidate 01 Joko Widodo still received a lot of responses from netizens but the sentiment value shifted more negatively compared to candidate 02 Prabowo Subianto. For candidate 01 Joko Widodo the NRC Lexicon analysis gave a value of 17 and bing lexicon of -273 with an average value of -0,246, while for candidate 02 Prabowo Subianto the NRC Lexicon analysis gave a value of 238 and bing lexicon of -73 with an average value of -0.02430939.
Implementasi Algoritma C5.0 Untuk Menentukan Pelanggan Potensial Di Kantor Pos Cimahi Nisa Hanum Harani; Fanny Shafira Damayanti
Jurnal SITECH : Sistem Informasi dan Teknologi Vol 4, No 1 (2021): JURNAL SITECH VOLUME 4 NO 1 TAHUN 2021
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/sitech.v4i1.6281

Abstract

Saat ini banyak perusahaan swasta yang bergerak di bidang jasa pengiriman yang mengakibatkan banyaknya pesaing bagi Kantor Pos Cimahi dan dapat mengakibatkan penurunan jumlah pelanggan yang menggunakan jasa Kantor Pos Cimahi. Oleh karena itu, diperlukan suatu sistem untuk membantu Kantor Pos Cimahi dalam mengidentifikasi calon pelanggan, sehingga dapat diketahui calon pelanggan mana yang dapat memperoleh perlakuan khusus, sehingga pelanggan tersebut dapat terus menggunakan jasa Kantor Pos Cimahi. Sistem yang dibangun menggunakan bahasa pemrograman PHP dan metode Algoritma C 5.0 yang merupakan salah satu algoritma pohon keputusan yang dapat membantu untuk menentukan pelanggan potensial. Penelitian menggunakan data transaksi periode bulan januari – oktober 2020 dimana atribut yang digunakan yaitu bulan, nama perusahaan, jenis kiriman yang digunakan, jumlah transaksi selama sebulan, dan total uang. Hasil penelitian menunjukan bahwa algoritma C 5.0 mampu melakukan menentukan data pelanggan potensial dengan akurasi sebesar 96%.
Penerapan Metode Algoritma K-Means untuk Menentukan Pemberian Reward terhadap Pelanggan PT. Telkom Kandatel Bone Muh. Rifky Prananda; Rd. Nuraini Siti Fathonah; Nisa Hanum Harani
Jurnal Tekno Insentif Vol 15 No 2 (2021): Jurnal Tekno Insentif
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah IV

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36787/jti.v15i2.570

Abstract

Abstrak Meningkatnya pertumbuhan industri menjadikan perusahaan bersaing mempertahankan pelanggannya. Persaingan di dunia industri memacu perusahaan untuk mencari cara agar penjualan meningkat disertai loyalitas pelanggannya. Pemberian reward merupakan salah satu piliha yang bisa dilakukan oleh perusahaan. Penelitian ini dirancang dengan menggunakan metode minmax dalam penyetaraan nilai atribut. Untuk proses clustering digunakan teknik pengelompokan k-means sebagai penentu pelanggan penerima reward. Sejumlah 10 sampel data pelanggan telah diujikan. Hasil dari metode algoritma k-means adalah 2 dari 10 pelanggan dinyatakan layak menerima reward, 4 pelanggan kurang layak mendapatkan reward, dan 4 pelanggan tidak layak mendapatkan reward. Hasil penelitian ini dapat membantu perusahaan dalam pemilihan pelanggan terbaik penerima reward dan diharapkan akan mampu meningkatkan loyalitas pelanggan. Abstract The increasing growth of the industry makes companies compete to retain their customers. Competition in the industrial world spurred companies to look for ways to increase sales with customer loyalty. Giving rewards is one of the choices that can be made by the company. This study was designed using the minmax value method in equalizing attributes. For the clustering process, the k-means grouping technique is used as a determinant of reward recipient customers. A total of 10 samples of customer data have been tested. The results of the k-means algorithm method are 2 out of 10 customers who are declared eligible to receive rewards, 4 customers are less deserving of rewards, and 4 customers are not eligible for rewards. The results of this study can help companies in selecting the best customers who receive rewards and is expected to increase customer loyalty.
SISTEM INFORMASI MANAJEMEN ASET MENGGUNAKAN METODE GARIS LURUS DAN MULTI ATTRIBUTE UTILITY THEORY (STUDI KASUS : SMAN 3 CIMAHI) Tasya Wiendhyra; Nisa Hanum Harani; Roni Habibi; Rolly Maulana Awangga
Jurnal Teknologi Vol 14, No 2 (2022): Jurnal Teknologi
Publisher : Fakultas Teknik Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/jurtek.14.2.213-220

Abstract

Asset management carried out by SMA Negeri 3 Cimahi is intended to manage assets at the school to support education and teaching and learning activities at schools. Asset management has been managed by the head of the asset warehouse. The whole process is still done manually by written it out then transferred to Microsoft Excel. For borrowing still use manual forms that are not compiled according to the year and existing items. In impairment  of asset, there is no recommendation for deletion that can facilitate decision making for asset deletion. Based on these problems, it is necessary to make an information system that can handle the asset management process. This information system is used by three Users, namely the Principal, the warehouse (asset) and the facility wakasek. The method of depreciation of assets used to perform calculations in this study is a straight line. Then the method for making decisions on goods to be deleted is the Multi-Attribute Utility Theory method with 3 criteria,  condition of the goods, book value, and the remaining economic life. This information system is web-based to increase the efficiency of schools in using information technology. The calculation tests carried out using the system and manual get the same results, the straight-line method on school desk assets purchased in 2018 at a price of 4,000,000, the depreciation on this month is 358,568. And for the Multi Attribute Utility Theory method, a recommendation for removal is obtained, namely a wooden cabinet with a final value of 0.8.
Co-Authors Andri Fajar Sunandhar Fanny Shafira Damayanti Fikri Aldi Nugraha Hanna Theresia Siregar Indra Firmansyah Josuansef Pardede Mariana Rospilinda Siki Muh. Rifky Prananda Muhammad Yusril Helmi Setyawan Prianto, Cahyo Rahayu, Woro Isti Rd. Nuraini Siti Fathonah Rolly Maulana Awangga, Rolly Maulana Roni Habibi Tasya Wiendhyra