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All Journal Jurnal Teknologi Industri Pertanian Jurnal Manajemen dan Organisasi Jurnal Manajemen dan Agribisnis Forum Pasca Sarjana Jurnal Manajemen Teknologi Jurnal Social Economic of Agriculture TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmu Komputer dan Agri-Informatika Jurnal Penelitian Pascapanen Pertanian JAM : Jurnal Aplikasi Manajemen Journal of Engineering and Management in Industrial System Indonesian Journal of Business and Entrepreneurship (IJBE) Sinergi Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Riset Industri agriTECH Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Jurnal Industri Hasil Perkebunan Register: Jurnal Ilmiah Teknologi Sistem Informasi Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Teknologi dan Sistem Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Sistem dan Manajemen Industri JKBM (JURNAL KONSEP BISNIS DAN MANAJEMEN) Jurnal Bina Praja International Research Journal of Business Studies (E-Journal) Albacore : Jurnal Penelitian Perikanan Laut Communications in Science and Technology CYBERNETICS Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) International Journal of Supply Chain Management Warta Penelitian Perhubungan STI Policy and Management Journal JURNAL PANGAN Systematics Indonesian Journal of Electrical Engineering and Computer Science Industry Xplore Journal of Computer Networks, Architecture and High Performance Computing International Journal of Mechanical Engineering Technologies and Applications (MECHTA) BISNIS & BIROKRASI: Jurnal Ilmu Administrasi dan Organisasi International Journal of Social Service and Research AGRI-TEK : Jurnal Penelitian Ilmu-ilmu Eksakta JURNAL TEKNIK INDUSTRI Mamangan Social Science Journal Journal of Scientific Research, Education, and Technology Policy Brief Pertanian, Kelautan, dan Biosains Tropika International Research Journal of Business Studies JURNAL REKAYASA KIMIA & LINGKUNGAN Warta Penelitian Perhubungan

Yandra Arkeman

Department Of Agroindustrial Technology, Faculty Of Agricultural Engineering And Technology, Bogor Agricultural University PO BOX 220, Campus IPB Dramaga, Bogor 16602

Author-ID : 233450

Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Transportation

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Software Defect Prediction Using Neural Network Based SMOTE Rizal Broer Bahaweres; Fajar Agustian; Irman Hermadi; Arif Imam Suroso; Yandra Arkeman
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2090

Software defect prediction is a practical approach to improve the quality and efficiency of time and costs for software testing by focusing on defect modules. The defect prediction software dataset naturally has a class imbalance problem with very few defective modules compared to non-defective modules. Class imbalance can reduce performance from classification. In this study, we applied the Neural Networks Based Synthetic Minority Over-sampling Technique (SMOTE) to overcome class imbalances in the six NASA datasets. Neural Network based on SMOTE is a combination of Neural Network and SMOTE with each hyperparameters that are optimized using random search. The results use a nested 5-cross validation show increases Bal by 25.48% and Recall by 45.99% compared to the original Neural Network. We also compare the performance of Neural Network based SMOTE with SMOTE + Traditional Machine Learning Algorithm. The Neural Network based SMOTE takes first place in the average rank.

Optimization of aggregate planning of rice husk charcoal production with Fuzzy Goal Programming approach Erni Krisnaningsih; Taufik Djatna; Yandra Arkeman; Marimin Marimin; Erliza Hambali
SINERGI Vol 26, No 1 (2022)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2022.1.009

This study proposes a Fuzzy Goal Programming approach to optimize the problem of aggregate planning of production processes in companies that produce charcoal husks. The application proposed to the company describes the process of Rice Husk Charcoal Production taking into account the uncertain factors involved in the aggregate planning process of Rice Husk charcoal production. Decision-making related to the level of material needs in each type of rice husk charcoal product is considered based on planning for the next 12 months by including weighting value in membership function, determination of membership function of each function objectives with equivalent Crip of fuzzy goal programming. Fuzzification is based on three main objectives with three membership levels for each purpose of Goal Programming. This research provides the results of the proposed adaptive model applied to companies that produce charcoal husks.

Analisis Kelayakan Produksi Silikon dari Abu Ampas Tebu Bambang Mulyana Hermanto; Erliza Noor; Yandra Arkeman; Etty Riani
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol. 9 No. 3 (2019): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan
Publisher : Graduate School Bogor Agricultural University (SPs IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.9.3.818-825

It is estimated that the increase of sugarcane production will also increase the amount of bagasse. Sugar mills utilize dried bagasse as boiler fuel and the burning results a bagasse ash.Unrefined bagasse is estimated to contribute to the impact of the environment, including health problems when inhaled by humans. When covers the leaves, it will block the process of photosynthesis in plant. This are due to the size of ash and the contents of silica dioxide compound inside the bagasse. Besides providing impact, silica dioxide compounds are compounds that have high economic value as it can be used as silicon. The purposes of the utilization of bagasse ashes into silicon are to reduce the impact on the environment, to increase the economic value of bagasse ash and to empower community. The results of the feasibility analysis of silicon production from bagasse ash arethe planned production capacity of 10,000 tons/year, breakeven point (BEP) that is 3,400 tons/year or 34% of production capacity, Return of Investment (ROI) that is 28%, Payout Time (POT) of 3,6 years and 28,25% of Internal Rate of Return (IRR).Therefore, the plan to utilize the bagasse ash from silicon can be considered to be done.

Model deep learning untuk klasifikasi fragmen metagenom dengan spaced k-mers sebagai ekstraksi fitur Nur Choiriyati; Yandra Arkeman; Wisnu Ananta Kusuma
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 3, Year 2020 (July 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13407

An open challenge in bioinformatics is the analysis of the sequenced metagenomes from the various environments. Several studies demonstrated bacteria classification at the genus level using k-mers as feature extraction where the highest value of k gives better accuracy but it is costly in terms of computational resources and computational time. Spaced k-mers method was used to extract the feature of the sequence using 111 1111 10001 where 1 was a match and 0 was the condition that could be a match or did not match. Currently, deep learning provides the best solutions to many problems in image recognition, speech recognition, and natural language processing. In this research, two different deep learning architectures, namely Deep Neural Network (DNN) and Convolutional Neural Network (CNN), trained to approach the taxonomic classification of metagenome data and spaced k-mers method for feature extraction. The result showed the DNN classifier reached 90.89 % and the CNN classifier reached 88.89 % accuracy at the genus level taxonomy.

The Clustering Rice Plant Diseases Using Fuzzy C-Means and Genetic Algorithm Faza Adhzima; Yandra Arkeman; Irman Hermadi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 2 (2022): April 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Rice is an agricultural sector that is very important for Indonesia's economy. The main problem with rice plants is pest and disease control which has a hazardous impact and economic losses for farmers. The apparent characteristics of rice leaves have a greater area than other plant structures; rice leaves can be applied for the early diagnosis of rice plant diseases. The approaches employed are fuzzy C-Means (FCM) and Genetic Algorithm-Fuzzy C-Means (GA-FCM). The center of the cluster is obtained while adopting genetic algorithms for optimization. The primary dataset used in this research is Teaching Sawah Farm IPB, and the second dataset is UCI Rice Leaf Diseases. According to the comparison results, the GA-FCM optimization results in a higher level of clustering precision with a 65% optimal cluster center point on the silhouette coefficient value compared to just 60% for FCM. This research shows that the proposed method can add 5% accuracy to the clustering results in correctly identifying rice plant diseases.

National Innovation Capability Variables and Dimensions Ahmad Dading Gunadi; Yandra Arkeman; Rizal Syarief Siaiful Nazli; Teguh Rahardjo; Aulijati Wachjudiningsih
STI Policy and Management Journal Vol 3, No 2 (2018): STI Policy and Management
Publisher : Center for Science and Technology Development Studies, Indonesian Institute of Sciences

The purpose of this paper is to analyze the dimensions and variables of National Innovation Capability. The findings in this paper are to refine the National Innovation Capabilities Dimension model developed by Chang and Lin (2012) by integrating a Network Dimension of Innovation. This paper analyzes the dimensions and variables of National Innovation Capability through a system approach that includes Input Sub System, Process Sub System, and Output Sub System. Network Dimensions Innovation is an integral part of the National Innovation Capabilities Dimension. This dimension is an important part, because the National Innovation Capability will largely depend on how innovative actors form networks and interact among them. The dimensions of National Innovation Capability are integrated into three sub system in a systems approach that includes input, process, and output. In the input consists of Dimensions of Innovation Resources. In the process consists of Innovation Demand Dimension, Innovation Network Dimension and Innovation Diffusion Dimension. In the output consists of Dimensions of Innovation Output. Each Dimension has some different variables. The entire dimensions and variables of these three sub system become unified as a Dimension and Variable of National Innovation Capability. Keywords: National Innovation Capability, Dimensions, Variables, Sub Systems

Perancangan Model Sistem Angkutan Studi Kasus Fasika Khaerul Zaman; Yandra Arkeman; Sri Hartoyo
JURNAL PANGAN Vol. 20 No. 3 (2011): PANGAN
Publisher : Perum BULOG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33964/jp.v20i3.162

Pangan merupakan salah satu kebutuhan dasar manusia yang paling asasi. Beras masih menjadi komoditi utama penopang ketahanan pangan nasional. Perum BULOG penyelenggara usaha logistik pangan pokok yang melakukan penyebaran persediaan melalui kegiatan angkutan antar Divisi Regional (Divre). Penelitian bertujuan merancang sistem angkutan antar Divre. Metode penelitian menggunakan metode perancangan sistem yaitu kegiatan merancang sistem melalui tahapan-tahapan tertentu untuk menjawab permasalahan yang ada. Menggunakan model optimasi dalam Pemrograman Linieryaitu Transportation Problem (Permasalahan Transportasi). Total biaya angkutan untuk tahun 2010 dengan model optimasi lebih rendah Rp. 17.461.590.772,- apabila dibandingkandengan total biaya yang dihitung dengan metode yang digunakan saat ini. Penggunaan pemrograman linier untuk angkutan antar Divre Perum BULOG menghasilkan optimasijumlah persediaan yang diangkut, jalur dan biaya angkutan. Model optimasi tidak hanya dilakukan terhadap kondisi ideal tetapi juga terhadap kemungkinan adanya perubahan perubahan melalui analisa pasca optimasi. Hasil analisa menunjukkan bahwa sistem operasional angkutan terbagi kedalam Sistem Perencanaan, Sistem Pelaksanaan, Sistem Evaluasi dan Sistem Penunjang. Keempat sistem tersebut saling berkaitan satu dengan lainnya dengan tujuan akhir adalah pelaksanaan angkutan antar Divre. Sistem ini banyak ditunjang oleh penggunaan pemrograman linier untuk mendapatkan biaya angkutan yang minimum.Food is one of the most basic human rights. Rice is still a major commodity supporting the national food security. Perum BULOG is the business organizer who makes the distribution supplies through transport activities among the Regional Divisions (Divres). The research aims to design a transportation system among the Divres. Research method used for designing the system is a system design activities through certain stages to address existing problems using Linear Programming optimization model in the Transportation Problem. The total cost of transport for 2010 was Rp. 17.461.590.772 which is lower compared to the total cost calculated by the method used today. The use of linear programming to transportation among Divres produces transported amount of inventory optimization, route and transportation costs. Optimization model is not only carried out on ideal conditions but also to the possibility of changes through the postoptimization analysis. The result showed that the operational system of transportation is divided into Planning System, Support System, Evaluation System and Integrated System. The four systems are interconnected with each other with the ultimate goal is the implementation of transport among Divres. This system is much supported by the use of linear programming to obtain the minimum transportation cost.

Peningkatan Performansi Multi Objektif NSGA-II Dengan Operator Mutasi Adaptif Pada Kasus Portofolio Reksadana Saham Putri Yuli Utami; Yandra Arkeman; Agus Buono; Irman Hermadi
CYBERNETICS Vol 3, No 02 (2019): CYBERNETICS
Publisher : Universitas Muhammadiyah Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29406/cbn.v3i02.2194

Non-dominated sorting genetic algorihm (NSGA-II) merupakan salah algoritma pencarian solusi optimal dengan mengurutkan solusi berdasarkan pareto-front untuk mengindentifikasi feasible solutions. Performansi algoritme NSGA-II sangat dipengaruhi oleh operator parameter. Salah satu parameter adalah operator mutasi yang memegang kendali untuk diversitas kandidat solusi. Pada riset ini operator mutasi dibuat adaptif dengan menggunakan distribusi probabilitas polinomial (parameter nm). Parameter ini mengontrol kekutatan mutasi dan mengubah nilai mutasi secara adaptif serta mengubah probabilitas mutasi secara dinamik untuk mengatur banyaknya gen yang mengalami mutasi. Berdasarkan hasil penelitian nilai standar deviasi mutasi non-adaptif lebih kecil daripada mutasi adaptif. Nilai standar deviasi merepresentasikan varians sehingga mutasi adaptif memiliki varians yang beragam dibandingkan dengan mutasi non-adaptif. Mutasi adaptif dapat meningkatkan diversitas kromosom sehingga mencapai konvergensi kromosom agar terhindar dari konvergensi dini dengan waktu komputasi yang lebih efektif. Pada kasus portofolio reksadana saham menghasilkan standar deviasi yang lebih besar sehingga solusi yang dihasilkan semakin beragam.

ANALISA MENENTUKAN KRITERIA PEMILIHAN PELABUHAN PENGUMPAN TOL LAUT MENGGUNAKAN METODE AHP Dian Junita Arisusanty; Yandra Arkeman; Sri Rahardjo; Deni Achmad Soeboer
ALBACORE Jurnal Penelitian Perikanan Laut Vol. 2 No. 1 (2018): Albacore
Publisher : Departemen PSP IPB

Tol laut merupakan salah satu program prioritas pemerintahan Joko Widodo untuk mewujudkan Indonesia sebagai poros maritim dunia. Latar belakang program tol laut karena adanya disparitas harga yang cukup tinggi antara wilayah barat dan timur Indonesia. Tol laut diharapkan dapat mendorong pemanfaatan potensi ekonomi yang ada serta membuka pasar baru untuk produk yang dihasilkan di kawasan timur Indonesia. Sistem transportasi laut mempunyai peran penting untuk negara kepulauan. Tol laut merupakan bentuk pelayaran perintis dalam mengangkut barang. Perlu dilakukan analisa yang sistematis terhadap kriteria pelabuhan pengumpan yang akan disinggahi kapal tol laut sehingga subsidi yang dikeluarkan pemerintah dapat tepat sasaran dan mampu mendorong sinergisitas pelaku usaha pelayaran untuk mendorong distribusi barang. Metode penelitian yang digunakan dalam penelitian ini adalah metode AHP (Analytical Hierarchy Process) yang digunakan dalam sejumlah penelitian untuk mengatasi masalah transportasi. Berdasarkan hasil analisis AHP, prioritas utama yaitu aspek hinterland dengan nilai bobot sebesar 39,5% diikuti dengan aspek pelabuhan sebesar 35,5%, aspek konektivitas sebesar 15% dan aspek demografi sebesar 10%. Sedangkan bedasarkan sub kriterianya, urutan prioritasnya adalah sub kriteria disparitas harga, kondisi dermaga, intermoda link, potensi muatan balik, ketersediaan peralatan B/M dan TKBM, jumlah penduduk, lapangan penumpukan, alur pelayaran, gudang, daya beli masyarakat, dan angkutan laut non subsidi.Kata kunci: AHP, kriteria pemilihan pelabuhan, Tol laut.

Supply Chain Management on the Production Process and Distribution Flows of the Superior Teak Seedlings Production Muhammad Alkaff; Marimin Marimin; Yandra Arkeman; Sukardi Sukardi; Herry Purnomo
International Journal of Supply Chain Management Vol 7, No 3 (2018): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.161 KB)

Management of supply chain that interrelates and integrates both consumers and suppliers in a process to make a value of product or service for consumers is very importance and strategic as well. The research objective is to analyze and improve the sustainability performance of production process and distribution flow of the teak seedling production within its supply chain. This research used multiple dimensional analysis and value stream mapping to identify the sustainability performance and analytical network process to find the key factors that improve the SCM performance of superior teak production. The research found that 1) the Parameter influencing SCM is supplier and therefore it requires system improvement. The problem is that the delivery of materials purchased in Surabaya takes too long time before they are stored in the warehouse. Placing a purchase order long time beforehand may apparently solve the problem. But in fact, it creates another problem because the materials are not to be stored in the warehouse for a long time due to their short expiry date and due to the limited infrastructures like warehouse and roads. SCM values on the production system of superior teak seedling production of BPPT located in Jatisari area is 56.62 with a quite high category. Based on the leverage analysis, the most dominating SCM components are waiting factor at the value of 2.71; overproduction at 2.30 and inventory at 2.25, 2) Based on the ANP analysis, the research found a position map of SCM components at the stress value of 3.411% meaning that it is an Excellent model suitability while the index of fit (R) is at 94.673% meaning it meets the appropriateness. Transportation process consists of transportation of auxiliary material of seedling production, travel of seedlings from nurseries to adapting areas, and distribution of seedlings. Slow supply of consumables required for seedling production process due to long distance between the production areas and supplier sites will cause delayed delivery of goods particularly of those that are not scheduled because of special cases. Keywords: Supply Chain, ANP, Transportation, Distribution Flows, Superior Teak Seedlings

Co-Authors A. Aziz Darwis A.A. Ketut Agung Cahyawan W AA Gede Rai Gunawan Abdul Aziz Adisalamun Adisalamun Agus Buono Agus Maulana Ahmad Dading Gunadi Aji Hermawan Alfian Nur Ubay Alim Setiawan S Alvian Abdul Jabar Anak Agung Gede Rai Gunawan ANDIYONO, ANDIYONO Andreas Murti Ani Suryani Ani Suryani Anny Ratnawati Arief Rakhman Aries Suharso Arif Imam Suroso Asma Assa Aulijati Wachjudiningsih Bambang Mulyana Hermanto Bimahri Qaulan Tsaqiela Budhi Hascaryo Iskandar Bunasor Sanim Bustanul Arifin Casnan Casnan Catur Winarto Dadan Umar Daihani Darsasa Herdiana Anggriyanto Deasy Kartika Rahayu Kuncoro Deni Achmad Soeboer Denni, Alex Dewi Auditiya Marizka Dewi Sondari Dian Ardifah Iswari Dian Junita Arisusanty Djumali Mangunwidjaja Djumali Mangunwidjaja Djumali Mangunwidjaja Dorina Hetharia Edi Sukmadirana Eka Sudarmaji Ekaterina Setyawati Ekaterina Setyawati Eko Agus Prasetio Eriyatno . Erliza Hambali Erliza Noor Erni Krisnaningsih Etty Riani Etty Susilowati Fadhillah Fairuzzahira Fajar Agustian Fajarina Budiantari Faqih Udin Farohaji Kurniawan Farohaji Kurniawan Fasika Khaerul Zaman Faza Adhzima Gibtha Fitri Laxmi Gunawan Gunawan Gusfa Arlian Putra Hari Wibisono Hartoyo Hartoyo Hartrisari Hardjomidjojo Herry Purnomo Herry Purnomo I Nyoman Sujana Idqan Fahmi Imam Ahmad Indah Yuliasih Indra Jaya Indrajani Sutedja Iphov Kumala Sriwana Irawadi Jamaran Irman Hermadi Irwansyah Saputra Iveline Anne Marie Iwan A Soenandi Iwan Sudirlan Jayawarsa, A.A. Ketut Joko Affandi Joko Affandi Joko Ratono Joko Ratono Julfi Restu Amelia, Julfi Restu Julia Kantasubrata Junardi Junardi Kadarwan Soewardi Kapelle, Imanuel B. D. Karlisa Priandana Khaswar Syamsu Kirbrandoko Kirbrandoko Kudang Boro Seminar Kunandi Kunandi kusnadi, adhi Liesbetini Hartoto M. Syamsul Maarif M. Syamsul Ma’arif Machfud Machfud Machfud Machfud Machfud Machfud Marimin , Marimin Marimin Meidhianto Usman Meidhianto Usman Mira Maulida Misgiyarta Misgiyarta Muhammad Agus Muljanto Muhammad Alkaff Muhammad Alkaff Muhammad Firdaus Muhammad Romli dan Suprihatin Andes Ismayana Muslich Muslich . Nora Azmi Nova Oktavia Nunung Nuryartono Nur Arifin Akbar Nur Choiriyati Nur Shabrina Nur Shabrina, Nur Ono Suparno Pamungkas, Wahyu Widji Petir Papilo Putri Yuli Utami Ratna Ekawati Ratna Ekawati Retno Astuti Rina Oktaviani Rini Prasetyani, Rini Rizal Bahara Rizal Broer Bahaweres Rizal Syarief Rizal Syarief Rizal Syarief Siaiful Nazli Roedhy Poerwanto RR. Ella Evrita Hestiandari Samhuri, Refita Yunie Sapta Raharja Saputra, Irwansyah Sarinah Sarinah Setiadi Djohar Siti Jahroh Sony Hartono Wijaya Sri Hartoyo Sri Nurdiati Sri Rahardjo Subowo, Eko Sudirlan, Iwan Sugiarto S Sukardi Sukardi Sukardi Sukardi Sukardi Sukardi Suprihatin Suprihatin Suprihatin Suprihatin Suprihatin Suprihatin Suprihatinr, Suprihatinr Suria Darma Tarigan Suripto Suripto Sutedja, Indrajani Syamsu , Khaswar Syamsul Ma'arif Syamsul Ma’arif Syarifuddin Nasution, Syarifuddin Taufik Djatna Teguh Rahardjo Teja Primawati Utami Titi Candra S Titi Candra S. Titi Candra Sunarti Tobing, Adil Trias Andati Trisna Trisna Try Kusuma Wardana Tun Tedja Irawadi Umi Marfuah Velica Yoyellia Vonny Indah Sari Wardhani, Ratih Anindita Wibisono Chandra Widodo CK, Agus Puji Wilda Sukmawati Winarto, Catur Winnie Septiani Wisnu Ananta Kusuma Yonvitner - Yuana, Rivira Yudi Yudistira Zaman, Fasika Khaerul Zenal Asikin Zulfiandri Zulfiandri

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