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All Journal JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JURNAL MAHAJANA INFORMASI Jurnal Sains dan Teknologi Jurnal Tekinkom (Teknik Informasi dan Komputer) INFOKUM Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN)
Windania Purba
Program Studi Sistem Informasi Universitas Prima Indonesia Medan
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Other

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APLIKASI SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KINERJA KARYAWAN MENGGUNAKAN METODE PROFILE MATCHING Siti Aisyah; Windania Purba
JURNAL MAHAJANA INFORMASI Vol 4 No 2 (2019): JURNAL MAHAJANA INFORMASI
Publisher : Universitas Sari Mutiara Indonesia Medan

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

Abstract

Universitas Prima Indonesia memiliki penilaian kinerja karyawan yang dilakukan setiap tahun, berdasarkan sasaran kerja, kedisiplinan dan beberapa aspek pendukung lainnya yang merupakan bahan evaluasi penilaian karyawan. Bagi karyawan yang terpilih akan diberikan penghargaan. Banyaknya karyawan menjadi kesulitan tersendiri dalam memilih karyawan berkinerja, tidak dipungkiri juga bahwa penilaian kinerja karyawan berkinerja pun sering dilakukan tidak objektif. Untuk mengetahui karyawan berkinerja baik perlu diadakan penilaian kinerja terhadap karyawan. Melakukan suatu penilaian dalam pemberian penghargaan untuk karyawan berkinerja baik diantaranya menggunakan sistem pendukung keputusan dalam membantu pemecahan suatu masalah. Metode yang digunakan dalam melakukan pemberian penghargaan untuk karyawan berkinerja baik yaitu dengan metode profile matching. Dengan adanya penerapan metode profile matching untuk penilaian kinerja karyawan terbaik dalam memecahkan permasalahan yang ada pada saat proses penilaian kinerja karyawan terbaik, agar tidak terjadi kesalahan dalam pengambilan keputusan. Diharapkan dengan upaya ini dapat memberikan nilai secara objektif terhadap karyawan dan membantu pimpinan dalam memberikan penilaian kinerja karyawannya.
APLIKASI SISTEM PENDUKUNG KEPUTUSAN ANALISIS KELAYAKAN PEMBERIAN KREDIT MENGGUNAKAN METODE SAW PADA PERUSAHAAN LEASING Siti Aisyah; Windania Purba
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 1 No. 2 (2018): Jutikomp Volume 1 Nomor 2 Oktober 2018
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v1i2.472

Abstract

Salah satu masalah aktual yang dihadapi oleh perusahaan leasing dalam memberikan kredit kepada pelanggan mereka adalah risiko kredit macet. Untuk mengatasi masalah ini, aplikasi berbasis sistem pendukung keputusan, yang memfasilitasi pendekatan yang lebih baik dalam menentukan kelayakan memberikan wawasan yang lebih mendalam tentang kemampuan pelanggan, dapat menjadi solusi. Salah satu metode yang tersedia untuk digunakan adalah Simple Additive Weighting (SAW). Metode ini memungkinkan perhitungan nilai untuk menentukan kelayakan suatu permintaan. Konsep dasar SAW adalah untuk mengetahui jumlah kinerja tertimbang di setiap alternatif. Faktor atau kriteria yang digunakan dalam penelitian ini meliputi disiplin pelanggan, jumlah uang muka, pendapatan bulanan, jaminan kredit, dan status tempat tinggal. Pada lingkup akademik, penelitian ini juga dapat digunakan sebagai pengayaan bahan ajar terutama dalam kursus Sistem Pendukung Keputusan serta sistem informasi secara umum. Hasil penelitian ini juga diharapkan menjadi salah satu referensi bagi siswa dalam menerapkan sistem pendukung keputusan dalam kasus nyata
PERANCANGAN SISTEM INFORMASI PEMESANAN TIKET ONLINE PADA KMP.IHAN BATAK BERBASIS ANDROID Windania Purba; Dilona Ujunga; Tri Wahyuni Lestari Sihalohoa; Jantiaman Damanik
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 3 No. 2 (2020): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9767/jikomsi.v3i2.64

Abstract

Pada KMP Ihan Batak, sistem pemesanan tiket yang berlaku saat ini masihbelum online. Sistem pemesanan tiket yang demikian memiliki kelemahanantara lain, kurangnya sistem keamanan dalam pengolahan data. Untuk itulahdalam penelitianini dibuat suatu aplikasi pemesanan tiket berbasis mobile gunamenjawab permasalahan yang dihadapi selama ini. Untuk mendapatkan hasilyang maksimal dalam pemesanan tiket maka di buatlah suatu sistem yang dapatmempermudah penumpang dalam memesan tiket, agar penumpang tidak lagiantri dalam memesan tiket. Sistem yang akan dibangun adalah teknologi mobilepemesanan tiket. Dengan adanya sistem ini maka akan jauh lebih baikdibandingkan dengan sistem manual baik dari segi keamanan, kecepatan, sertaketertiban
Impact of Online Learning in the Era Pandemic Using the Algorithm C 4.5 Windania Purba; Desty Rukmana; Derry Rosanta Br.sitanggang; Lina Sari Harefa
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 2 (2021): Journal of Computer Networks, Architecture and High Performance Computing, July
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i2.990

Abstract

The presence of the Corona virus disease 2019 (Covid-19) pandemic has changed the order in all corners of the world in a very short time. This large-scale change has occurred in the last two years starting from 2019 until now. This has resulted in the world of education experiencing major changes in the teaching and learning process. The learning process during the COVID-19 pandemic (online) is very much different from the previous learning process (face to face). This is a big problem in the world of education. The online learning policy, which was thought to be the solution to this problem, turned out to be just a bridge to break the passion for learning for students. evidenced by the impact felt by students during online learning. The satisfaction of online learning by Prima Indonesia University students can be seen from the results of the keosener (google form) that the researcher has distributed to 501 students. Researchers use data mining to explore important information that is expected to be used as consideration for enforcing the current online learning process. Researchers use the C 4.5 Algorithm method in data mining in order to bring out the impact of online learning. Measurement of satisfaction level is done by calculating the Entropy and Gain of each data that becomes a Decision tree and testing the results using Rapid Miner. The C 4.5 algorithm is very helpful for researchers to find out the impact of online learning carried out during the covid 19 pandemic. From the results of calculations and testing, it shows that there is a decrease in student interest in learning in the online learning process. this concludes that online learning in the pandemic era has a negative impact on students at Prima Indonesia University.
The Design of a Website-Based Motorcycle Installment Bill Check Application at Indah Motor KM.5 Windania Purba; Irsan Jaya Sihombing; Ayu Elpriyani Sidabutar; Nur Ainun Siahaan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 2 (2021): Journal of Computer Networks, Architecture and High Performance Computing, July
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i2.1010

Abstract

Looking at current developments, many activities have implemented the capabilities and advantages of technology in them so that the operational costs, time and energy needed can be found. This technological development also develops this technology also creates needs in the community and even new needs. Along with the need for credit is one alternative carried out by the community and business entities to obtain something with the aim of meeting their needs. This credit or installment activity also does not rule out the possibility of being applied to this type of motorcycle sales business, because in reality the need for motorcycles is currently important and has a high level of demand so that some motorcycle sales provide a payment system for motorcycles that are designed to improve performance. and quality of service, the community needs flexibility to speed up payment for motorbikes that are being sold in installments. From the research that has been done as mentioned above, the author intends to carry out development in terms of installment implementation into a website-based application, so the author takes the title "Designing a Website-Based Motorcycle Installment Bill Check Application at Indah Motor Km.5". From the problems that occur, the researcher intends to simplify credit or installment problems into a website that can make it easier for admins to process and solve problems that apply in the community.
APPLICATION OF DATA MINING TO IDENTIFY DIABETES MELLITUS USING THE SUPPORT VECTOR MACHINE (SVM) ALGORITHM AND KNN Windania Purba; Yessy Yessy; Riski Nofarianus Gulo
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (253.474 KB)

Abstract

Damage to the performance of human organs is very detrimental Received Revised Accepted And is the source of the most problems at this time. One of the diseases that is the number one killer in the world is diabetes mellitus. Diabetes mellitus is a metabolic disease characterized by hyperglycemia caused by and obstacle in insulin secretion from insulin action or both. Diabetes mellitus is divided into several types, type 1 diabetes mellitus generally gives rise to indications before the patient is 30 years old. Although in fact the indications of the disease can arise at any time. This study aims to apply the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) method to identify diabetes mellitus and calculate the comparison value of the accuracy of the two algorithms. From the results of this study. It can be concluded that the Support Vector Machine (SVM) algorithm produces an accuracy value of 76% while the accuracy value of the K-Nearest Neighbor (KNN) algorithm is 75%
USING THE NAIVE BAYES CLASSIFIER METHOD ON SOCIAL MEDIA SENTIMENT ANALYSIS Windania Purba; Ade Syahpitri; Grace Fitri Anggi Munthe
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.042 KB)

Abstract

Social media is one of the many technological developments that greatly affect human communication and socialization systems. Most people voice their opinions through social media, with the aim that they can be heard and seen by the general public. However, the use of social media often backfires for the owners themselves due to their excessive use. In particular, this study discusses the grouping of sentiment data from Prima Indonesia University students where to seek negative and positive opinions from students as a benchmark for online learning methods carried out in the campus environment. The data grouping process uses the nave Bayes algorithm, because this algorithm has been widely used in data processing. The tests carried out in this study resulted in an accuracy of 68% of the dataset selected as the data training process. This results in a classification of new data to find out a sentiment on students belonging to the negative or positive class.
Analisis Cluster Provinsi Indonesia Berdasarkan Produksi Bahan Pangan Menggunakan Algoritma K-Means Tonny Tendean; Windania Purba
Jurnal Sains dan Teknologi Vol. 1 No. 2 (2020): Sains dan Teknologi
Publisher : CV. Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34013/saintek.v1i2.31

Abstract

Food is material produced through agricultural products which has a great influence on human survival. Having agriculture spread throughout Indonesia, making Indonesia a country that always produces raw food. Raw food can be in the form of fruits, vegetables, rice, peanuts, and others. Clustering algorithm is applied to group the number of provinces according to the results of food production with K-Means. The data from this study were sourced from information on the number of provinces according to the results of food production produced by the National Statistics Agency. There are 34 provinces that will be used in this study. There are 5 variables used, namely corn production, peanut production, soybean production, rice production, and cassava production. The data collected will be processed by clustering in 3 clusters, namely high foodstuff production clusters, medium foodstuff production clusters, and low foodstuff production clusters. In its implementation using rapidminer software. The results obtained can be input for the government in analyzing the provinces according to food production.
MENGANALISIS KEUNTUNGAN DAN BIAYA TERHADAP PROSES PENGOLAHAN SARANG BURUNG WALET MENGGUNAKAN ALGORITMA C5.0 Windania Purba; Angelin Angelin
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 4 No 2 (2021)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v4i2.398

Abstract

This study aims to analyze the costs and benefits required to produce swiftlet nests. Swallow's nest is a very popular health product today. This can happen because swallow's nest has many health benefits such as antioxidant, anti-inflammatory, antiaging, anticancer, increasing immunity and accelerating wound healing. Currently, the production of swallow's nest at PT. Cefa Indonesia Sejahtera Lestari is difficult to do so that swallow nest products are expensive. To help PT. Cefa Indonesia Sejahtera Lestari overcomes the problem of the cost of processing dirty swallow's nests to finished products so that they can be handled properly using the C5.0 algorithm by classifying these problems. The results showed that the root node was obtained, namely the drying stage of the swallow's nest. If the costs required at this stage are equivalent to the existing capital, the company will benefit. Conversely, if the required cost exceeds the existing capital, the company will experience a loss.
ANALISIS TINGKAT KEPUASAN PELANGGAN PADA RUDANG HOTEL BERASTAGI MENGGUNAKAN METODE CUSTOMER SATISFACTION INDEX (CSI) Okta Jaya Harmaja; Windania Purba; Maxwell Paulus Siregar; Henry Triadi Manurung; Fransisco Andreas Sirait
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.511

Abstract

Service quality is very important in the hospitality industry because of the great competition in the industry. Therefore, the hotel must provide the best service to its guests. This study was conducted to see how the quality of service at the Rudang Berastagi hotel to guests using the CSI method to calculate the level of customer satisfaction at the Rudang Berastagi Hotel as an evaluation material to improve hotel services in the future. Data processing in this study was carried out using the Python programming language through Google Colab. Based on the calculation of guest satisfaction at Rudang Berastagi Hotel through a questionnaire of 110 respondents, it was found that the guests were satisfied with the services provided by Rudang Berastagi Hotel with a satisfaction level of 78.4% using the Customer Satisfication Index (CSI) method. According to the questionnaires that have been distributed, it is concluded that question number 1 with the contents of the questions having a complete, comfortable, clean, and well-organized room interior gets the highest mean value of 4.27%.
Co-Authors Ade Syahpitri Aguan Aritonang Angelin Angelin Ayu Elpriyani Sidabutar Derry Rosanta Br.sitanggang Desty Rukmana Dilona Ujunga Elbert Ghozali Evta Indra Fransisco Andreas Sirait Grace Fitri Anggi Munthe Henry Triadi Manurung Irsan Jaya Sihombing Jantiaman Damanik Lina Sari Harefa Mario Gota Manalu Maxwell Paulus Siregar Nur Ainun Siahaan Okta Jaya Harmaja Palma Juanta Riski Nofarianus Gulo Saut Parsaoran Tamba Siti Aisyah Steven Steven Tonny Tendean Tri Wahyuni Lestari Sihalohoa Yessy Yessy Yoel Ferdinand Zai