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All Journal Jurnal Media Infotama METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Jurnal Abdi Ilmu Majalah Ilmiah Kaputama JTIK (Jurnal Teknik Informatika Kaputama) KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer MEANS (Media Informasi Analisa dan Sistem) Syntax: Journal of Software Engineering, Computer Science and Information Technology Journal Of Information And Technology Unimor (JITU) Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Jurnal Widya Bulletin of Multi-Disciplinary Science and Applied Technology Journal of Computer Science and Informatics Engineering Journal of Artificial Intelligence and Engineering Applications (JAIEA) International Journal of Informatics, Economics, Management and Science Journal of Engineering, Technology and Computing (JETCom) Journal of Mathematics and Technology (MATECH) Jurnal Pengabdian Pada Masyarakat METHABDI International Journal of Health, Engineering and Technology Jurnal Penelitian Sistem Informasi Indonesian Journal of Education And Computer Science Indonesian Journal of Science, Technology, and Humanities Nusantara Journal of Multidisciplinary Science Jurnal Penelitian Teknologi Informasi dan Sains Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan Switch: Jurnal Sains dan Teknologi Informasi Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Saturnus: Jurnal Teknologi dan Sistem Informasi Pascal: Journal of Computer Science and Informatics
Yani Maulita
STMIK Kaputama
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PENERAPAN DATA MINING PENGELOMPOKAN PESERTA BPJS KETENAGAKERJAAN BERDASARKAN PROGRAM YANG DIAMBIL MENGGUNAKAN METODE CLUSTERING Zema; Maulita, Yani; Arliana, Lina
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v6i2.166

Abstract

The implementation of the social security program is one of the responsibilities and obligations of the State, to provide socio-economic protection to the community. Indonesia, like other developing countries, develops social security programs based on funded social security, namely social security that is funded by participants and is still limited to working people in the formal sector. BPJS Ketenagakerjaan continues to improve competence in all aspects of service while developing various programs and benefits that can be directly enjoyed by workers and their families. Non-Wage Recipient Workers (BPU) are employees who carry out economic activities or businesses independently to earn income from their activities or business. The problem that hinders the length of data collection for BPJS Employment participants is the process of determining the social security program that will be taken by Non-Wage Recipient (BPU) workers from the program taken by BPJS Ketenagakerjaan participants. owned is very small and only enough for the daily needs of participants. Data Mining is a data mining process in very large amounts of data using statistical, and mathematical methods, and utilizing the latest Artificial Intelligence technology. Data mining in the process of grouping data can use a grouping method, namely the Clustering method. The system is designed with the MATLAB R2014a programming application, after testing with the system, the results obtained are that in group 1 there are 370 data, group 2 there are 359 data and group 3 there are 271 data with a total of 100 data participants.
Pemamfaatan Metode Clustering Pada Nasabah Peminjaman Modal (Studi Kasus: PT. Faderal International Finance Binjai) Sembiring, Wildan Yuanda Malik; Maulita, Yani; Ramadani, Suci
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v6i2.191

Abstract

Peminjaman modal merupakan transaksi tersepakati dari dua belah pihak bermaksud meminjan uang/dana kepada seseorang atau badan usaha peminjaman. PT. Faderal International Finance Binjai sebagai salah satu satu badan usaha yang bergerak di bidang keuangan atau jasa keuangan yang menyediakan peminjaman modal dengan menjaminkan surat berhaga sebagai penjamin Dalam rekapitulasi data nasabah dalam pengelompokkan nasabah untuk mengetahui jumlah nasabah dalam peminjaman modal sering dilakukan secara komputerisasi bahkan manual yang mengakibatkan sulit dalam pengelompokkan dan mengetahui jumlah nasabah. Pada penelitian ini dalam Pemamfaatan Pada Nasabah Peminjaman Modal menggunakan metode clustering dalam nilai yang di hasilkan menggunakan program mendapatkan hasil yang berbeda - beda pada penggunaan cluster 2 dan cluster 3. maka dapat di simpulkan penggunaan metode clustering mampu mengelompokkan data nasabah peminjaman modal di PT. Faderal International Finance Binjai.
PENERAPAN METODE SAW DAN TOPSIS SEBAGAI PERBANDINGAN HASIL SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LOKASI LAHAN TAMBAK PALING TERBAIK UNTUK DIJADIKAN USAHA TAMBAK AIR PAYAU Yani Maulita; Buaton, Relita; Malau, Farid Reza
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 1 No. 1 (2017): Volume 1, Nomor 1, Januari 2017
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v1i1.742

Abstract

Banyaknya metode-metode yang tersedia pada sistem pendukung keputusan sehingga kadang membuat bingung memilih mana yang cocok penggunaaan metode yang sesuai dengan kasus sistem pendukung keputusan. Untuk itu dibuat suatu perbandingan dari kasus sistem pendukung keputusan pemilihan lokasi lahan tambak paling terbaik untuk dijadikan usaha tambak air payau untuk perbandingan hasil keputusan. Metode yang digunakan yaitu Simple Additive Weighting (SAW) dan Topsis dengan menentukan banyaknya jumlah kriteria, jenis kriteria (Cost dan Benefit), dengan 3 alternatif. Hasil penelitian yaitu hasil perhitungan manual sama dengan perhitungan yang ada pada sistem. Setiap perhitungan dari dari metode SAW dan Topsis menunjukkan bahwa hasil keputusan pemilihan lokasi lahan tambak paling terbaik untuk dijadikan usaha tambak air payau setiap metode memiliki hasil akhir yang berbeda-beda.
PERBANDINGAN HASIL PENGGUNAAN METODE WP DAN ELECTRE SEBAGAI PENDUKUNG SISTEM KEPUTUSAN PEMILIHAN LOKASI LAHAN TAMBAK PALING TERBAIK UNTUK DIJADIKAN USAHA TAMBAK AIR PAYAU Maulita, Yani
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 1 No. 2 (2017): Volume 1, Nomor 2, Juli 2017
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v1i2.749

Abstract

Banyaknya metode-metode yang tersedia pada sistem pendukung keputusan sehingga kadang membuat bingung memilih mana yang cocok penggunaaan metode yang sesuai dengan kasus sistem pendukung keputusan. Untuk itu dibuat suatu perbandingan dari kasus sistem pendukung keputusan pemilihan lokasi lahan tambak paling terbaik untuk dijadikan usaha tambak air payau untuk perbandingan hasil keputusan. Metode yang digunakan yaitu weighted product (WP) dan Topsis dengan menentukan banyaknya jumlah kriteria, jenis kriteria (Cost dan Benefit), dengan 3 alternatif. Hasil penelitian yaitu hasil perhitungan manual sama dengan perhitungan yang ada pada sistem. Setiap perhitungan dari dari metode WP dan Electre menunjukkan bahwa hasil keputusan pemilihan lokasi lahan tambak paling terbaik untuk dijadikan usaha tambak air payau setiap metode memiliki hasil akhir yang berbeda-beda. Berdasarkan hasil perhitungan metode WP diatas, Desa Duton Batu merupakan alternatif yang terbaik untuk membangun lahan usaha tambak air payau. Berdasarkan dari hasil perhitungan metode ELECTRE, Desa Duton Batu merupakan alternatif yang tertinggi karena Desa Duton Batu memiliki 2 elemen yang bernilai true.
JARINGAN SYARAF TIRUAN UNTUK MEMPREDIKSI NILAI KELULUSAN SIDANG (STUDI KASUS : STMIK KAPUTAMA BINJAI ) Siregar, Retni Noviyanti; Kadim, Lina Arliana Nur; Maulita, Yani
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 3 No. 2 (2019): Volume 3, Nomor 2, Juli 2019
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v3i2.771

Abstract

Thesis session is a process that must be followed by a student in order to account for the thesis that has been done. Thesis trial scores determine student graduation, and student graduation rates are used as a measure of campus quality. The problem is that many students are depressed and afraid in the face of a thesis hearing, not a few among students who are stressed in facing thesis and some even delay the work of the thesis so that it affects the trial value obtained. Besides that there are students who have good IP but the trial value is not good, and vice versa. This method the Artificial Neural Network using the Backpropagation algorithm was chosen because it was able to predict the graduation value of the thesis trial based on input from the value of the semester IP from semester I to semester VII and the value of the trial. The study was conducted in two ways, namely training and testing. The training process aims to recognize or look for expected results by using a lot of training, so that it will produce the best pattern for training the data. After the training reaches the goal based on the best pattern, it will be tested with new data to see the accuracy between the targets using Matlab R2014a software. Based on the results of testing using Matlab R2014a software, the results are convergent, with a target error of 0.2. From the results of the training and the tests carried out, it was predicted that the graduation score of the thesis trial was predicted to be 0.8727. This research can also help predict the graduation score of thesis students at STMIK Kaputama Binjai
Data Mining Klasterisasi Aduan Masyarakat Kota Binjai Menggunakan Algoritma K-Means Dimas Prayogi; Yani Maulita; Rusmin Saragih
Indonesian Journal of Science, Technology and Humanities Vol. 1 No. 2 (2023): IJSTECH - October 2023
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/ijstech.v1i2.120

Abstract

Menerapkan metode K-Means dalam data mining untuk menganalisis aduan masyarakat Kota Binjai yang diterima oleh Satpol PP. Dengan metode ini, data aduan dapat dikelompokkan ke dalam klaster-klaster yang memiliki karakteristik serupa. Hal ini membantu dalam memahami pola aduan dan potensi masalah yang mungkin muncul di masyarakat. Membangun sistem data mining untuk aduan masyarakat di kantor Satpol PP Kota Binjai. Ini akan mencakup pengumpulan data, pemrosesan data, klasterisasi, dan penyajian hasil. Dengan adanya sistem ini, Satpol PP dapat terus memantau dan memahami dinamika aduan masyarakat secara lebih efisien. Dari 402 pengelompokan data Pengaduan berdasarkan Kelurahan, aduan dan Tindakan terdapat 4 group, dimana kelompok yang terbanyak pada pengujian pertama ini berada pada cluster 1 dengan jumlah 120 data pada group dengan pusat centroid  34.20, 6.97, 2.40 yaitu kelurahan tangsi aduan Pembangunan tanpa IMB dan Tindakan melakukan evaluasi. cluster 2 dengan jumlah 78 data pada group dengan pusat centroid  20.67, 12.69, 1.92 yaitu kelurahan pekan binjai aduan orang mabuk meresahkan dan Tindakan melakukan evaluasi. cluster 3 dengan jumlah 118 data pada group dengan pusat centroid  16.19, 3.73, 2.63 yaitu kelurahan mencirim aduan manusia silver dan Tindakan melakukan penertiban. . cluster 4 dengan jumlah 86 data pada group dengan pusat centroid  4.14, 7.58, 2.47 yaitu kelurahan binjai estate aduan Razia hotel dan Tindakan melakukan evaluasi
Sistem Pelaporan Kerusakan Jalan Raya Berbasis Android Dengan Metode Item Collaborative Filtering (Studi Kasus : Dinas PU Kota Binjai) Muhammad Prabowo Hartanta Sitepu; Yani Maulita; Hermansyah Sembiring
Nusantara Journal of Multidisciplinary Science Vol. 1 No. 2 (2023): NJMS - September 2023
Publisher : PT. Inovasi Teknologi Komputer

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

Abstract

Kerusakan jalan raya merupakan masalah yang umum terjadi di berbagai kota di seluruh dunia, termasuk Kota Binjai. Dalam upaya untuk mengatasi masalah ini, Dinas Pekerjaan Umum (PU) Kota Binjai membutuhkan sistem pelaporan kerusakan jalan yang efisien dan responsif. Penelitian ini mengusulkan pengembangan Sistem Pelaporan Kerusakan Jalan Raya Berbasis Android dengan menerapkan Metode Item Collaborative Filtering. Sistem ini dirancang untuk memungkinkan masyarakat secara mudah melaporkan kerusakan jalan raya melalui aplikasi Android yang dapat diunduh secara gratis. Metode Item Collaborative Filtering digunakan untuk mengelola laporan kerusakan jalan dan memberikan rekomendasi prioritas perbaikan berdasarkan histori laporan sebelumnya. Hal ini akan membantu Dinas PU Kota Binjai dalam mengalokasikan sumber daya dengan lebih efisien. Penelitian ini juga mencakup studi kasus pada Dinas PU Kota Binjai untuk menguji keefektifan sistem yang diusulkan. Hasil penelitian menunjukkan bahwa sistem ini dapat membantu dalam mendeteksi dan mengatasi kerusakan jalan raya dengan lebih cepat dan efisien, serta memberikan rekomendasi prioritas perbaikan yang lebih akurat. Dengan demikian, sistem ini memiliki potensi besar untuk meningkatkan layanan infrastruktur jalan raya di Kota Binjai dan berpotensi diadopsi oleh kota-kota lain dalam upaya meningkatkan kualitas infrastruktur jalan secara keseluruhan.
Penerapan Metode Bayes untuk Mendiagnosa Penyakit Saraf Kejepit Esti Sundari; Yani Maulita; Husnul Khair
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 3 (2024): SEPTEMBER : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v2i3.2380

Abstract

A pinched nerve is a condition where certain nerves are compressed by tissues around the body, such as bones, cartilage and muscles. This causes the nerve to become damaged with symptoms of severe pain, tingling, and numbness during activity. Nerve pain can spread throughout the body. For example, patients with radiculopathy type spinal cord disease make the patient numb, and the nerve pain can spread to the feet and hands. Sylvani General Hospital also provides expert doctors who treat various diseases, including pinched nerve disease suffered by patients. However, there are several problems that often occur to patients when going for direct consultation due to time constraints, long queues, long waits, long distances to the hospital, and lack of costs. Because agencies need to have a system that can manage existing symptom data on pinched nerve disease and make it an online expert substitute information by utilizing technological developments to get maximum diagnostic results, and patients can find out the initial symptoms of one of them numbness, leg pain, arm pain, back pain, muscle weakness in the type of pinched nerve disease, namely radiculopathy, carpal tunnel syndrome, pinched nerves in the waist, piriformis syndrome, radial tunnel syndrome and treatment first by consulting through a system that has been created using the Bayes method. From the calculation process using the Bayes method above, it is known that the diagnosis of pinched nerve disease is diagnosed with nerve root syndrome (Radiculopathy) (P01) with a percentage of 72.55%.
Pengelompokan Data Keluhan Masyarakat Terhadap Fasilitas Umum diKota Binjai Menggunakan Metode Clustering Dea Syafitri; Yani Maulita; Lina Arlianan Nur Kadim
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 3 (2024): SEPTEMBER : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v2i3.2381

Abstract

Public Facilities in Binjai City are infrastructure that is provided free of charge that can be enjoyed by the community and is one of the vacation spots that does not need to spend a lot of money, but there are several infrastructure facilities that are not maintained, dirty and have damage from minor to the most severe, even infrastructure, so that it greatly affects the comfort of the community. In the process of maintaining public facilities in Binjai City in accordance with the Binjai City Regional Regulation Letter Number 1 of 2024 concerning public facilities used for public purposes, including for educational, health, worship, socio-cultural, sports and recreational activities (Hamzah, 2024). The Environmental Service of Binjai City really needs input from the community to continue to help maintain and care for the facilities provided so that the agency can handle and respond to community complaints such as a lot of garbage, dirty, rusty, muddy facilities and others as well as input reported by the community on the cleanliness of public facilities in Binjai City. Therefore, the agency needs a system using the clustering method that can manage community complaint data to be used as information that can assist the agency in taking quick action to deal with the problem of community complaints about public facilities in Binjai City. Based on the research conducted on the case experiment above from testing 20 data, there are 3 groups, namely group 1 there are 5 data and group 2 there are 9 data, and group 3 there are 6 data which can be known that in cluster 2 the group of public complaints about public facilities in Binjai City with public facilities (X) Studion Field, with complaints (Y) Becek, Banyak Sampah, & Berkarat, with Advice (Z) Repair & Maintain Cleanliness.
Application of the K-Means Algorithm in Traffic Violations In Langkat District (Case Study: Langkat Police) Sari, Elisa Puspita; Maulita, Yani; Syari, Milli Alfhi
Indonesian Journal of Education And Computer Science Vol. 1 No. 2 (2023): INDOTECH - August 2023
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/indotech.v1i2.50

Abstract

Societal activities are intertwined with traffic, and people prefer using vehicles. The lack of education and limited understanding of traffic regulations have led to numerous violations. The increasing number of traffic violations has resulted in a rise in traffic violation data. The abundance of traffic violation data has led to data accumulation within institutions. Therefore, data processing through data mining utilizing the K-Means Algorithm is deemed necessary. Research findings have unveiled a cluster of traffic violation data that stands out as the highest and most frequent during processing: the age group of 17 to 25 years, involving Honda Vario 150 vehicles, and evidence of violations related to driver's licenses (SIM) and vehicle registration certificates (STNK). Test results on three clusters from a dataset of 502 traffic violation records reveal the following: Cluster 1 comprises traffic violation data pertaining to individuals aged 26 to 45 years, using Honda CBR 250 vehicles, and violations tied to driver's licenses (SIM) and vehicle registration certificates (STNK). Cluster 2 includes traffic violation data concerning individuals aged 26 to 45 years, utilizing Suzuki Nex vehicles, and violations involving driver's licenses (SIM) as well as carrying more than one passenger. Cluster 3 involves traffic violation data associated with individuals aged 17 to 25 years, employing Honda Vario 150 vehicles, and violations linked to driver's licenses (SIM
Co-Authors , Achmad Fauzi ., Novriyenni Achmad Fauzi Acmad Fauzi Agi Kakana Bangun Ahmad Fauzi Ahmad Kurniawan Prahadi Alanis Humairoh Alfinaty, Nurma Ambarita, Indah Andika, Rio Andri Kristiawan Annatasia, Kristina Arisma Yulistiani Arisya, Feby Arliana, Lina Aula, Nurhasanah Aulia, Damai Aulia Br Karo Ayu Rahayu Febria Ayu Rahayu Febria Buaton, Relita Budi Serasi Ginting Budi Serasi Ginting Citra Ayu Wasih Dea Syafitri Dhea Armaya Dicky Ananda Azhari Dieo Alfiky Ananda Dila Aulia Putri Dimas Prayogi Dina Ervianna Simarmata Dita Sahputri Elfira Iriani Esti Sundari Eva Sasmita Fadilah, Nurul Elsa Farid Reza Malau Farid Reza Malau Farida Hanum Fauzi Ahmad Muda Fauzi, Achmad Fisyanda Yusmalizar Fresti Anjeli Gea, Wisda Wati Gultom, Imeldawaty Hafizh, Faisal Hermansyah Sembiring I Gusti Prahmana Ika Indah Rahayu Intan Sari Irfan Yusuf Jecika Azzahra Kadim, Lina Arliana Nur Katen Lumbanbatu Katen Lumbanbatu Khair, Husnul Khairunisa, Salsabila Kristina Annatasia Br Sitepu Kristina Annatasia Br Sitepu Kusmananda Lubis Lala Arika Leni Tri Ramadhayanti Lina Arliana Liyanti Armaya Sari Lubis, Setia Adiyasa Lumbanbatu, Katen Magdalena Simanjuntak magdalena simanjuntak Magdalena Simanjuntak Malau, Farid Reza Manik, Laurensia Agustin Mariza Marto Sihombing Maskanda Rizky Maulidina, Nadia Melda Pita Uli Sitompul Mhd Arif Permata Mirah, Alta Muammar Khadafi Muhammad Prabowo Hartanta Sitepu Muhammad Rivaldi Prastowo Muhammad Yusri Nadilla Ayudia Pasa Naftali, Juliana Ningsih, Fauziah Nisrina Naufalia Santoso Novriyenni Novriyenni - Novriyenni, Novriyenni Nurhayati Nursakinah Pakpahan , Victor Maruli Pakpahan, Victor Maruli Pardede, Akim Manaor Hara Pasaribu, Tioria Piper Warni Gea Prahmana, I Gusti Pramana, I Gusti Puteri Diyana Putri Ladya Elvanny Putri Lestari Rafli Pramudia Rahayu, Rizka Putri Rahmat Ramadhan Ramadana, Noval Ramadani, Suci Ratih Puspadini Rayuni, Rayuni Retni Noviyanti Siregar Rindi Asti Ananda Rizki Irwansyah Rizky Ramadhan Rusmin Saragih, Rusmin Sari, Elisa Puspita Saripurna, Darjat Selfira, Selfira Selviyani, Selviyani Sembiring, Hermansyah Sembiring, Jhody Alkhalis Sembiring, Wildan Yuanda Malik Setia Ningsih Shella Nadya Shely Eninta BR PA Sihombing, Anton Sihombing, Marto Silvia, Sindy Simanjuntak, Magdalena Sinurat, Sylvia Natalia Siregar, Retni Noviyanti Siswan Syahputra Suci Rahmadani Suci Ramadani Suci Ramadani suci ramadani Suci Ramadani Suci Ramadani Suci Ramadani Sujayanti Br.Giniting, Novia Suma Dia Syahwani Sundari, Yeni Sundari, Yeni Suria Alamsyah Suria Alamsyah Putra Surya Alamsyah Putra Syahputra , Siswan Syahputra, Siswan Syahputra, Suria Alam Syahputri, Heni Syari, Mili Alfhi Syari, Milli Alfhi Tarigan, Kiki Dea Ananda Tiwi, Chairmayni Pratiwi Tria Damayanti Wardhani, Diah Wardhani, Diah Wardhani Wildan Yuanda Malik Sembiring wildan yuanda malik sembiring Winda Sari Yuyun Arnia Zehy Fadia Zema Zema Zema Zema Zhya Anggraini