bluuebunny/crossref_metadata_2025 huggingface dataset:
Pendekatan Berbasis DMAIC untuk Perbaikan Proses Suplai Bahan Baku
Authors: Baldah Nasrun , Safitri Wiji
Published: July 2024

Penelitian ini bertujuan untuk mengevaluasi transaksi bahan baku di area penyimpanan dan proses kerja material handling yang bertugas menyuplai bahan baku ke area lini proses perakitan AL.agar lebih akurat. Masalah utamanya yaitu adanya perbedaan data bahan baku yang masuk ke area penyimpanan dengan output hasil produksi, kemudian adanya antrian saat pengambilan bahan baku dikarenakan perlintasan yang padat pada jalur pengambilan,sehingga berdampak pada keterlambatan bahan baku pada lini proses. Pengumpulan data dilakukan melalui observasi, data sekunder dari laporan hasil transaksi di tempat penyimpanan bahan baku yang dianalisis menggunakan metode DMAIC, dengan tahapan Define, Measure, Analyze, Improve, dan Control. Hasil penelitian menunjukkan peningkatan akurasi data transaksi bahan baku, berkurangnya tingkat stok, berkurangnya keterlambatan pasokan bahan baku, menghilangnya potensi kesalahan proses, mengurangi tingkat kepadatan lalu lintas di area penyimpanan bahan baku, percepatan informasi dan pengendalian stok secara real-time. Pendekatan DMAIC dapat memperbaiki akurasi data stok bahan baku mencapai akurasi 100%, mengurangi tingkat kepadatan jalur pengambilan bahan baku sebesar 50% sehingga proses suplai lebih cepat dan sesuai kebutuhan dengan mengurangi lead time 1,8 hari menjadi 0,5 hari.
Pengukuran Green Supply Chain Pada UMKM Produsen Ayam Potong dan Distribusi Ayam Broiler
Authors: Hidayatuloh Syarif , Uswatun Kasanah Yulinda , Arini Ratih Windu
Published: July 2024

Setelah pandemi covid berbagai jenis industri berusaha mempertahankan operasional perusahaannya. Salah satunya industri yang bergerak dalam suplai pangan seperti distributor unggas. Kegiatan usaha ayam potong pada tingkat Usaha Mikro Kecil dan Menengah (UMKM) masih kesulitan mempertahankan kegiatan operasional produksi daging ayam akibat dari fluktuasi ekonomi akhir-akhir ini. Selain itu, harga dari daging ayam yang cenderung fluktuatif apabila dibandingkan dengan sebelum pandemi. Untuk itu perlu dilakukan pengukuran kinerja rantai pasok untuk mengetahui tingkat kinerja rantai pasoknya sehingga dapat mengetahui akar permasalahan yang terjadi dan perbaikan yang harus dilakukan. Penelitian ini mengangkat topik manajemen rantai pasok dengan pendekatan green pada UMKM Mitra Unggas Mandiri. Selain itu juga mengukur kinerja rantai pasok hijau dengan menggunakan pendekatan model SCOR 12.0 dan AHP. Hasilnya yaitu ada 19 KPI yang digunakan, dimana empat KPI termasuk dalam aspek green sebagai pengukuran rantai pasok hijau. Total skor pengukuran adalah 75.017, dimana nilai ini termasuk kedalam kategori Good. Hal ini menunjukkan secara keseluruhan proses rantai pasok hijau pada UMKM Mitra Unggas Mandiri sudah berjalan dengan baik.
Implementasi Kansei Engineering dalam Menentukan Konsep Pengembangan Kemasan Rujak Buah Potong
Authors: Isna Ade , Sari Novi Purnama , Maharani Devyta , Fadhillah Fahri
Published: July 2024

Saat ini kemasan menjadi alat promosi untuk meningkatkan nilai daya beli dan membangun kepercayaan konsumen. Kemasan rujak buah yang dijumpai pada pedagang kaki lima hanya menggunakan plastik mika atau kertas minyak yang tidak memiliki label branding serta tidak memiliki proteksi yang baik untuk melindungi rujak buah. Tujuan dilakukan penelitian ini adalah untuk menentukan konsep desain kemasan yang sesuai dengan preferensi konsumen. Metode yang digunakan dalam penelitian ini adalah Kansei Engineering dan model Principal Component Analysis atau PCA. Kansei Engineering dapat mengetahui preferensi konsumen terhadap konsep kemasan rujak buah yang mempertimbangkan aspek emosional maupun perasaan dengan melakukan survei responden. Pengolahan dengan model Principal Component Analysis dilakukan penye­der­hanaan data yang didapatkan dari responden loyal rujak buah potong. Hasil dari penelitian yang didapatkan sebanyak 82,6% konsumen berharap bahwa perlu untuk melakukan pengembangan kemasan rujak buah potong. Jumlah total sampel dan kata Kansei yang telah diseleksi untuk dijadikan referensi konsumen ialah sebanyak 38 sampel dan 39 Kansei word. Setelah melakukan penyaringan dengan metode PCA didapat tiga model konsep kemasan yang akan dikembangkan pada produk rujak buah potong. Tiga model konsep yang didapat diantaranya adalah “Fresh – Practice”, “Sustainable – Safety”, dan “Fun – Functional”. Ketiga konsep tersebut merupakan data yang dipertahankan karena value pada metode Kaiser, Standar Deviasi, dan Cumulative Proportion bernilai lebih dari satu (>1) dan memiliki proporsi lebih dari 80%. Namun, konsep yang didapat perlu dianalisis kembali dalam menentukan elemen desain yang sesuai dengan kebutuhan konsumen.
Faktor Penyebab Kecelakaan Sepeda Motor: Studi Literatur
Authors: Maryani Anny , Iridiastadi Hardianto
Published: July 2024

Kecelakaan sepeda motor mendominasi jenis kecelakaan lalu lintas sebesar 70% sampai 75%. Akibat yang ditimbulkan dari kejadian kecelakaan sepeda motor dikategorikan pada tidak ada cidera, cidera ringan, cidera berat sampai kematian (fatalitas). Risiko fatalitas pada korban kecelakaan sepeda motor adalah 27 kali dibandingkan kecelakaan kenda­raan bermotor lain, dikarenakan minimnya perlindungan saat berkendara sepeda motor. Selain itu, kecelakaan sepeda motor juga menyebabkan timbulnya kerugian materi yang diperlukan untuk penanganan kesehatan, perbaikan kendaraan, dan kerugian kerusakan jalan. Di Indonesia tercatat 250 miliar rupiah per tahun kerugian yang diakibatkan oleh kecelakaan sepeda motor. Mengingat bahayanya kecelakaan sepeda motor ini, maka artikel ini bertujuan untuk melakukan studi literatur terkait faktor penyebab terjadinya kecelakaan dan keparahan akibat kecelakaan sepeda motor. Artikel berupa jurnal dan proseding berbahasa Inggris yang dipublikasikan secara internasional dikumpulkan dan didapatkan 139 artikel. Analisa mendalam dilakukan pada artikel terbitan 2016 sampai awal 2022. Sebanyak 18 artikel yang meneliti faktor berpengaruh pada kecela­kaan sepeda motor dibahas dan dianalisa secara mendalam. Hasil analisa menyatakan faktor penyebab kecelakaan sepeda motor berasal dari faktor manusia meliputi karakter dan perilaku pengendara, faktor jalan meliputi karakter dan kondisi jalan, faktor kendaraan meliputi kapasitas mesin dan usia kendaraan, serta faktor lingkungan meliputi cuaca, cahaya dan waktu. Detail hubungan ditampilkan pada kerangka sistematis yang berguna untuk menerapkan strategi mitigasi berupa intervensi untuk mengurangi kejadian kecela­kaan dan keparahan yang diakibatkan. Intervensi tersebut diantaranya adalah melalui edukasi (pendidikan), infrastruktur, dan kebijakan. Untuk penelitian selanjutnya ditekan­kan pada edukasi terutama meningkatkan kesadaran berkendara dengan aman melalui perbaikan perilaku berkendara. Selain itu kerangka kecelakaan sepeda motor juga dapat digunakan sebagai acuan peta jalan penelitian keselamatan sepeda motor pada masa yang akan datang.
Usulan Peningkatan Efektivitas Mesin Hammer Milling dengan Metode ORE dan FMECA
Authors: Ilmi Fuad Bahrul , Garside Annisa Kesy , Khoidir Amelia , Wardana Rahmad Wisnu
Published: July 2024

PT. X adalah bagian dari Kappa Group, sebuah bisnis terintegrasi dalam industri rumput laut Indonesia. Salah satu masalah dalam produksi di PT. X adalah mesin hammer milling sering mengalami downtime sehingga menurunkan efektivitas mesin tersebut. Tujuan dari penelitian ini adalah mengukur efektivitas dan memberikan usulan untuk meningkatkan efektivitas mesin hammer milling. Langkah-langkah penelitian terdiri dari pengukuran efek­­­tivitas mesin dengan metode Overall Resource Effectiveness (ORE), identifikasi faktor penyebab rendahnya efektivitas mesin dengan fishbone diagram, perhitungan tingkat kekritisan mode kegagalan dengan Failure Mode Effect and Critical Analysis (FMECA), dan  pemberian usulan peningkatan efektivitas mesin berdasarkan critical analysis. Hasil pengolahan data didapatkan nilai ORE sebesar 55,95% yang menunjukkan efektivitas mesin hammer milling cukup baik dan terdapat beberapa indikasi yang perlu dilakukan perbaikan. Usulan peningkatan efektivitas mesin yang direkomen­dasikan adalah penentuan tingkat persediaan suku cadang original dengan menggunakan metode continuous review, preventive maintenance berdasarkan jadwal perawatan yang ditetap­kan, dan implementasi autonomous maintenance.
Digital Human Modeling sebagai Evaluasi dan Perancangan Meja Kerja Pengelasan untuk Pembelajaran Praktikum Mahasiswa
Authors: Abryandoko Eko Wahyu , Farahdiansari Ardana Putri , Ramadhani Ahmad Ridho , Nurudduja Moh.
Published: July 2024

Perancangan konsep meja kerja pengelasan untuk proses pembelajaran perlu memperÂ­timbangkan resiko Work-related musculoskeletal disorders (WMSDs). Perancangan konsep meja kerja pengelasan dilakukan dengan tujuan meminimalisir risiko EFPs, khususnya jenis gerakan fleksi ke depan pada leher dan posisi lengan yang terangkat saat melakukan pengelasan dalam posisi berdiri dengan estimasi welding selama 360 menit. Penelitian ini bertujuan untuk merancang konsep desain meja kerja pengelasan yang ergonomis, dengan penilaian menggunakan beberapa parameter yang disimulasiÂ­kan menggunakan Digital Human Modeling. Metode yang digunakan untuk merancang konsep meja kerja pengelasan adalah metode Pugh concept Selection, yang kemudian disimulasikan menggunakan perangkat lunak Catia V5 R21 untuk menganalisis nilai LBA dan RULA. Parameter postur tubuh model manusia disesuaikan dengan tiga subjek yang diuji menggunakan meja kerja sebelum dimodifikasi. Hasil identifikasi pada konsep desain, ditemukan alternatif konsep desain I untuk meja kerja pengelasan. Konsep ini menÂ­cakup beberapa parameter spesifikasi, terÂ­masuk kemampuan meja untuk disesuaiÂ­kan secara langsung, penjepit komponen pengeÂ­lasan yang dibuat secara permanen, penggunaan manual tanpa alat bantu setup, kemampuan penyesuaian sudut kemiringan meja, dan ketinggian meja yang dapat disesuaikan menggunakan sistem ulir. Setelah mendapatkan konsep desain tersebut, dilakukan pengujian simulasi pada konsep desain terpilih. Hasil pengujian simulasi didapatkan nilai LBA pada konsep desain meja pengelasan dengan ketinggian 70 cm dan 100 cm (tinggi meja dapat menyesuaikan postur tubuh) lebih aman dan nyaman dibandingkan dengan desain meja pengelasan sebelum dimodifikasi (50 cm). Hal ini juga terjadi pada penilaian RULA, Dimana desain meja kerja pengelasan baru mampu meningkatkan nilai yang semula 7 menjadi 3. Berdasarkan temuan tersebut, pengemÂ­bangan konsep meja kerja pengelasan terbukti efektif untuk digunakan dalam proses pembelajaran, karena mahasiswa dapat mempelajari secara langsung penggunaan meja yang tepat dengan memperhitungkan kesejahteraan ergonomis operator untuk mengurangi risiko cedera WMSDs pada pekerjaan pengelasan.
Analysis of lean-agile-resilient-green (LARG) implementation in the electric car industry in Indonesia
Authors: Purba Humiras Hardi , Jaqin Choesnul , Aisyah Siti , Nabilla Mutiara
Published: July 2024

Vehicle type approval (VTA) total registration of electronic vehicles in Indonesia for the accumulation period until August 2023 is 81,525 units with a composition of 4-wheeled vehicles 18,300 units. The use of electric vehicles is still a tiny portion compared to the motorized vehicle population in Indonesia, which will reach more than 146 million units in 2022. It is different from developments in Europe, the United States, and China, where more research into the use of electric vehicles is being carried out. The readiness of the automotive industry system to produce electric vehicles is absolutely necessary to achieve superior productivity levels. National auto­motive companies need to anticipate that changes in production systems will also change along with changes in processes and components in electric vehicles. In the next few years, world-class manufacturing production systems will refer to LARG (lean, agile, resilient, and green) aspects. Lean, agile, resilient, and environmentally friendly manufacturing industrial opera­tions are critical. This research aims to determine the level of appli­cation of LARG aspects in the electric vehicle automotive industry. The method used was exploratory, and a questionnaire was filled out with industry experts and analyzed using the analytical hierarchy process (AHP) and objective matrix (OMAX). The results of this study confirm that all aspects of LARG require improvement. Resilience (R) and green (G) have performance below 10 percent, so these two aspects are priorities for improvement by the electric car industry in Indonesia.
Use of analogies by future Physics teachers in conducting supervised internship activities
Authors: Parma Fabiano Willian , Vieira Murilo Henrique Alfredo , Nardi Roberto
Published: July 2024

Analogies are frequently used in people's daily lives to relate unfamiliar domain knowledge to everyday knowledge. Because analogies are so common to humanity, using them in teaching and learning is effective for helping students better understand abstract material. In this way, in a supervised internship, we sought to investigate how future physics teachers used analogies during a mini-course on thermology. Classes were held in two school centres from different contexts: a youth and adult education unit and a high school. The theoretical and methodological references of Pecheutian Discourse Analysis, as well as the models for constructing Teacher With Analogies (TWA) and the Focus-Action-Reflection (FAR) guide, were employed for data analysis. It could be inferred that the teachers’ analogies were drawn spontaneously, while considering the analogies that students were already familiar with. Furthermore, as a result of reflection, there were variances between an analogous relationship and another.
Pengaruh Terapi Butterfly Hug terhadap Tingkat Kecemasan pada Remaja
Authors: Aulia Azka Widi Zulfa , Yuliastuti Estin , Suyatno Suyatno
Published: July 2024

Latar Belakang:  Remaja merupakan masa transisi di mana ketika terjadi kesalahan dalam bertindak dapat menimbulkan reaksi emosi yang tidak stabil sehingga menyebabkan kecemasan. Salah satu upaya untuk mengatasi kecemasan adalah Terapi Butterfly Hug. Tujuan: Penelitian ini memiliki tujuan untuk mengidentifikasi pengaruh Terapi Butterfly Hug terhadap tingkat kecemasan pada remaja. Metode: Penelitian ini menggunakan desain quasi-experiment dengan satu kelompok pretest-posttest. Penelitian ini dilaksanakan pada 18-23 Maret 2024 di salah satu sekolah menengah atas di Boyolali. Sebanyak 42 responden dipilih secara purposive sampling. Pengukuran tingkat kecemasan menggunakan HARS (Hamilton Anxiety Rating Scale) sebelum dan setelah tindakan Terapi Butterfly Hug. Terapi Butterfly Hug dilakukan sebanyak satu kali pertemuan terdiri atas 8 sesi yang dilakukan secara berkelompok dengan durasi 10 menit per sesi. Analisis data dilakukan dengan Wilcoxon Rank Test. Hasil: Hasil uji analisis didapatkan bahwa nilai p 0,000 (p<0,05). Kesimpulan: Tindakan Terapi Butterfly Hug pada remaja memiliki pengaruh signifikan terhadap tingkat kecemasannya. Penelitian ini memberikan kontribusi penting dalam memperluas pemahaman tentang efektivitas terapi ini dalam konteks kecemasan remaja, serta memberikan dasar bagi penelitian lebih lanjut atau penerapan klinis lebih lanjut terkait dengan terapi ini.
Edukasi Terapeutik untuk Meningkatkan Kepatuhan Pembatasan Cairan Pasien Gagal Ginjal Kronik
Authors: Marini Lutfiana Arum Putri , Enikmawati Anik , Suyanti Suyanti , Widyastuti Yuli
Published: July 2024

Latar belakang : Ketidakpatuhan pada pasien hemodialisa dapat menyebabkan komplikasi serius. Salah satu ketidakpatuhan yang sering terjadi yaitu mengenai kepatuhan pembatasan cairan. Akibat dari ketidakpatuhan tersebut dapat menyebabkan penumpukan cairan didalam tubuh dan zat lainya sehingga menyebabkan pasien merasa tidak nyaman hingga berakhir kematian. Warga kota Surakarta yang menjalani hemodialisa terdaftar sebagai penerima JKN berjumlah 586.166 jiwa. Oleh karena itu, Upaya yang dapat dilakukan salah satunya pemberian edukasi yang efektif. Edukasi yang terstruktur dan berkelanjutan dapat membantu pasien menigkatkan kepatuhan dan kualitas hidup. Tujuan : Untuk mengidentifikasi pengaruh edukasi terapeutik terhadap kepatuhan pasien gagal ginjal kronik yang menjalani hemodialisa terhadap pembatasan cairan. Metode : penelitian ini  menggunakan quasi-eksperimental dengan rancangan one group pre-test – post-test design. Pengambilan sample penelitian menggunakan purposive sampling dengan jumlah sample sebanyak 36 responden dan menggunakan uji Wilcoxon signed rank test. Teknik pengumpulan data menggunakan kuesioner data demografi dan lembar observasi interdialytic body weight gains (IDWG). Hasil : penelitian ini menunjukan hasil nilai kepatuhan pembatasan cairan IDWG sebanyak 75% dan hasil uji analisis 0,004 yang dimana p=<0,05. Kesimpulan : Edukasi terapeutik meningkatkan kepatuhan pembatasan cairan pasien gagal ginjal kronik terhadap pembatasan cairan, mengurangi risiko komplikasi seperti edema, hipertensi dan masalah jantung, serta meningkatkan kualitas hidup pasien.
Optimalisasi Pengetahuan Pasien dan Keluarga dalam Penanggulangan Tuberkulosis Paru di Wilayah Kerja Puskesmas Purbaratu Kota Tasikmalaya
Authors: Widia Chita , Anih Kurnia  , Eli Kurniasih  , Ilham Alifiar
Published: July 2024

Penyakit tuberculosis (TB)  merupakan salah satu penyakit menular, salah satu upaya yang sangat mendukung tugas tenaga kesehatan adalah melibatkan keluarga secara aktif  dalam perawatan dan penanggulangan masalah TB Paru. Kegiatan pengabdian kepada masyarakat berupa optimalisasi peran keluarga sebagai pengawas minum obat pada pasienTB Paru di Wilayah Puskesmas Purbaratu KotaTasikmalaya dilaksanakan pada tanggal 20 Juni sampai dengan 30 Juli 2022. Metode yang dilakukan adalah memberikan edukasi melalui kegiatan penyuluhan berbasis keluarga (kerumah pasien) dan praktek. .Hasil dari kegiatan pengabdian masyarakat ini diperoleh peningkatan pengetahuan pasien dan keluarga tentang TB Paru dan peran keluarga dalam pengawas menelan obat. Kegiatan pengabdian masyarakat yang dilakukan merupakan bentuk upaya perawat dalam pengelolaan TB Paru dengan melibatkan pasien dan keluarga.
Model Regresi Cox Weibull Dengan Metode Penaksiran Parameter Efron Partial Likelihood
Authors: Ihsan Ihsan , Suyitno Suyitno , Wahyuningsih Sri
Published: July 2024

Survival analysis is an analysis that involves statistical tests to analyze data on the time or length of time until the occurrence of a particular event. One regression model for time duration data modeling is the Cox PH regression model. Cox PH regression applied to time duration data with Weibull distribution is called Cox PH Weibull regression. The purpose of this study is to obtain a Cox PH Weibull regression model and determine the factors that influence the length of treatment for tuberculosis patients. The parameter estimation in this study is Efron partial likelihood method. The Efron partial likelihood method is suitable for estimating Cox PH regression parameters to data containing ties. Based on the results of parameter estimation the best model is obtained by using  AIC crtiteria. Based on the partial test,  age is factor that influence to the length of treatment. The results of the study show that every increasing age patient one year, then length of treatment until the patient recovered, will increas 1,024 times.
Pengujian Hipotesis Parameter Model Mixed Geographically Weighted Regression Data Indeks Pembangunan Manusia di Kalimantan Tahun 2016
Authors: Utami Riska Putri , Suyitno Suyitno , Hayati Memi Nor
Published: July 2024

Mixed Geographically Weighted Regression (MGWR) model is a Geographically Weighted Regression (GWR) model with some parameters are global (have the same value) and several other parameters are local (have different values) for each observation location. The purpose of this study is to obtain a MGWR model on the Human Development Index (HDI) data and find out the factors that influence the HDI of each district (city) in the provinces of East Kalimantan, Central Kalimantan and South Kalimantan in 2016. The parameter estimation method is carried out through two stages (backshift), namely local parameter estimation by using the Weighted Least Square (WLS) method and global parameter estimation by using  the Ordinary Least Square (OLS) method. Spatial weighting on local parameter estimation is obtained by using an adaptive Bisquare weighting functions, where optimum bandwidth determination uses Generalized Cross-Validation (GCV) criterion. Based on the result of MGWR parameter testing, it was concluded that the school enrollment rates (SMP) affected the HDI of all districts (cities) in East Kalimantan, Central Kalimantan and South Kalimantan, while the population density affects the HDI only in a few districts (cities), namely East Kutai, Balikpapan, Samarinda and Bontang.
Model-Model Regresi Weibull Univariat pada Indikator Pencemaran Air Dissolved Oxygen di Daerah Aliran Sungai Lingkungan Hutan Hujan Tropis Kalimantan Timur
Authors: Chairina Puspa , Suyitno Suyitno , Siringoringo Meiliyani
Published: July 2024

A Univariate Weibull Regression is a model of regression developed from univariate Weibull distribution with the parameter scale is stated in parameter regression. There are some of univariate Weibull regression model, namely Weibull survival regression, Weibull hazard regression and mean model. Univariate Weibull regression model in this research is applied to the water pollution indicator dissolved oxygen (DO data at Mahakam river in East Kalimantan. The purpose of this study is to find out the model of univariate Weibull regression based on the parameter estimation by using maximum likelihood estimation method (MLE) and to find out the factors which affect to univariate Weibull regression in Mahakam river. The result shows that the closed form of the maximum likelihood estimator can not be found analytically, and it can be approximed by using the Newton-Raphson iterative method. Based on the result of partial hypothesis test for all the parameter regression, it was found that detergent concentration and nitrate concentration had significant influence to the DO in the water of Mahakam river.
Pengelompokkan Data Runtun Waktu menggunakan Analisis Cluster
Authors: Dani Andrea Tri Rian , Wahyuningsih Sri , Rizki Nanda Arista
Published: July 2024

The export value of East Kalimantan Province has big data conditions with time series and multivariable data types. Cluster analysis can be applied to time series data, where there are different procedures and grouping algorithms compared to grouping cross section data. Algorithms and procedures in the cluster formation process are done differently, because time series data is a series of observational data that occur based on a time index in sequence with a fixed time interval. The purpose of this research is to obtain the best similarity measurement using the cophenetic correlation coefficient and get the optimal c-value using the silhouete coefficient. In this study, the grouping algorithm used is a single linkage with four measurements of similarity, namely the Pearson correlation distance, euclidean, dynamic time warping and autocorrelation based distance. The sample in this study is the data on the export value of oil and non-oil commodities in East Kalimantan Province from January 2000 to December 2016 consisting of 10 variables. Based on the results of the analysis, the distance of the best similarity measurement in clustering the export value of oil and non-oil commodities in East Kalimantan Province is the dynamic time warping distance with the optimal c-value of 3 clusters.
Penerapan Latent Class Regression Analysis dalam Segmentasi Pasar
Authors: Musmirani Musmirani , Purnamasari Ika , Suyitno Suyitno
Published: July 2024

Cluster analysis is a method of grouping observation objects into several classes. One method of mixed-scale data grouping is Latent Class Regression Analysis (LCRA). The purpose of this research is to classify the opinion of Wardah's product consumers on marketing strategies (product aspects, price aspects, location aspects, and promotion aspects) PT. Paragon Technology and Innovation Regional Samarinda in 2017 with covariate variables arelength of subscription, type of work and age of consumers. Estimation of LCRA using the Expectation Maximization (EM) method, solved by the Newton-Raphson method. The result of LCRA analysis that based on consumer opinion on market segmentation, consumers are grouped into two classes.The first class is 31 consumers  that strongly agrees the aspects of product, price, promotion and position are appropriate market segmentation, and the second class is 69  that quite agrees product aspects, prices, promotion and position is the appropriate market segmentation.
Model Spatial Autoregressive Moving Average (SARMA) pada Data Jumlah Kejadian Demam Berdarah Dengue (DBD) di Provinsi Kalimantan Timur dan Tengah Tahun 2016
Authors: Sari Devi Nur Endah , Hayati Memi Nor , Wahyuningsih Sri
Published: July 2024

Spatial Autoregressive Moving Average (SARMA) is a spatial regression model that uses the regional approach. The weighting matrix used is an adjacency matrix which is based on the intersection between observed locations. This study was conducted to determine the SARMA model and the factors that influence the number of cases of dengue hemorrhagic fever (DHF) in the provinces of East Kalimantan and Central Kalimantan in 2016. Based on the results of the Moran's Index test, there is a spatial autocorrelation on the number of dengue events in East Kalimantan Province and Central Kalimantan in 2016. The Lagrange Multiplier (LM) test has a spatial lag on the dependent variable and the error variable, which is a parameter  and  that is significant to the significance level . Based on the results of SARMA modeling that the factors that influence the number of dengue events in the provinces of East Kalimantan and Central Kalimantan in 2016 are the percentage of population density, the percentage of healthy houses, and the percentage of puskesmas.
Analisis Distribusi Frekuensi dan Periode Ulang Hujan
Authors: Widyawati Widyawati , Yuniarti Desi , Goejantoro Rito
Published: July 2024

Increasing water demand for various needs can be a complex problem so it is necessary to manage water resources. Analysis of hydrological data is very necessary to get information about water resources where the information can be used as a benchmark for planning a water resources builder. One of hydrological analysis is the analysis of rainfall data where this analysis uses frequency distribution analysis and rain return periods. There are four types of distribution used, namely normal distribution, normal log distribution, Gumbel distribution and type III log Pearson distribution. The goodness of fit test uses the Kolmogorov-Smirnov method, Chi-Square and Anderson-Darling. Rainfall return calculation is calculated when it is known the type of distribution of the data studied. This research uses rainfall data of Long Iram Sub-Distric, West Kutai Distric in 2013 to 2017 obtained from the Meteorology, Climatology and Geophysics Agency (BMKG) of Samarinda City. The results from research showed that the Gumbel distribution was the right distribution or distribution that was the best with the results of the return period of rain for the return period of 2 years obtained by rainfall of 519 mm, 5-year return period of 796 mm, 10-year return period of 980 mm, return period 20 years of 1.154 mm, a 50 year return period of 1.348 mm and in a 100 year return period of 1.752 mm.
Analisis Diagram Kontrol Fuzzy U
Authors: Fauzia Rina , Yuniarti Desi , Hayati Memi Nor
Published: July 2024

Fuzzy in general means that an element can be classified into two sets simultaneously. Fuzzy control diagrams are very suitable to be used for observations that produce information (data) that is uncertain, unclear and based on one's subjectivity. This study was applied to data on plywood products in PT. Segara Timber, Samarinda, East Kalimantan Province in 2018. The purpose of this study is to get the results of the decision fuzzy u control diagram. Based on the results of the use of the fuzzy control diagram u produce the most found decisions are rather in control that is equal to 26 observations, while the second most is rather out of control that is equal to 22 observations, and out of control that is equal to 14 and in control of 5 out of 67 observation.
Penerapan Model Geographically Weighted Logistic Regression Pada Data Status Kesejahteraan Masyarakat di Kalimantan Tahun 2017
Authors: Pratiwi Nadya , Suyitno Suyitno , Siringoringo Meiliyani
Published: July 2024

Geographically Weighted Logistic Regression (GWLR) model is a regression model developed from logistic regression which is applied to spatial data. The aims of research is a GWLR model determination on dichotomous data of community welfare status based on the Human Development Index (HDI) and to find the factors influencing the probability of high welfare status of each Regency/City on Kalimantan Island in 2017. Parameters estimation of the GWLR model was done at each observation location using a weighted Maximum Likelihood Estimation (MLE) method and maximum likelihood estimator was obtained by Newton Raphson iterative method. Spatial weighting on parameter estimation was determined using Adaptive Gaussian weighting function and optimum bandwidth was determined using Generalized Cross-Validation (GCV) criterion. Based on the result of GWLR parameter testing, it was concluded that the factors influencing the probability of high welfare status of Regency/City on Kalimantan Island in 2017 were school enrollment rates (senior high school), the number of health workers, real per capita income and the open unemployment rate.
Penentuan Jalur Terpendek dengan Metode Heuristik Menggunakan Algoritma Sarang Semut (Ant Colony)
Authors: Hidayat Alfian , Purnamasari Ika , Siringoringo Meiliyani
Published: July 2024

Ant Colony algorithm was adopted from the behavior of ant colonies, known as the system of ants, ant colonies are naturally able to find the shortest route on their way from nest to food source places. Colony of ants can find shortest route between the nest and food sources based on the trajectory of footprints that have been passed. The density of ant footprints on the path is always updating because of the evaporation of the footprints and the determination of ant pathways using probability calculations. This study aims to determine the results of determining the shortest path using the ant colony algorithm as the best route from the Samarinda City secondary arterial road with the route starts from Slamet Riyadi road to DI Panjaitan road. Based on the results of the study using the ant colony algorithm obtained the shortest path of 8.307 kilometers with footprint density of 1.005.
Peramalan dengan Menggunakan Metode Holt-Winters Exponential Smoothing
Authors: Aryati Ayu , Purnamasari Ika , Nasution Yuki Novia
Published: July 2024

Forecasting is a technique for estimating a value in the future by looking at past and current data. Foreign tourists are everyone who visits a country outside their place of residence, driven by one or several needs without intending to earn income in the place visited and the duration of the visit is no more than twelve months. The method used in this study is the Holt-Winters smoothing smoothing method. In this study used data of foreign tourists visiting Indonesia in January 2014 - September 2018. The purpose of this study was to determine the pattern of data forecasting the number of foreign tourists, the value of the accuracy of forecasting, and the results of forecasting. Based on the Holt-Winters smoothing method, the data pattern for the number of foreign tourists is the multiplicative Holt-Winters data pattern. The value of the smoothing parameter combination with the smallest MAPE of 0,938% is α = 0,9; β = 0,1; and γ = 0,9. The results of forecasting the number of foreign tourists visiting Indonesia in October 2018 and November 2018 were 1.410.157 and 1.362.473 people respectively
Penerapan Model Mixed Geographically Weighted Regression dengan Fungsi Pembobot Adaptive Tricube pada IPM 30 Kabupaten/Kota di Provinsi Kalimantan Timur, Kalimantan Tengah dan Kalimantan Selatan Tahun 2016
Authors: Safitri Ranita Nur , Suyitno Suyitno , Hayati Memi Nor
Published: July 2024

Mixed Geographically Weighted Regression (MGWR) model is a Geographically Weighted Regression (GWR) model which has global (equal value) and local (inequal value) parameters at every different observation location. The goal of this study is to obtain MGWR model of the Human Development Index (HDI) data and find out significant factors influencing the HDI in each district (city) East Kalimantan, Central Kalimantan and South Kalimantan province in 2016. Parameter estimation method is conducted in two stages namely local parameter estimation and global parameter estimation. Local parameter estimation method is Maximum Likelihood Estimation (MLE), with spatial weighting is calculated by  adaptive tricube weighting function and optimum bandwidth determination uses the Akaike Information Criteria (AIC). Global parameter estimation method is Ordinary Least Square (OLS). Based on the result of MGWR parameter testing, it was concluded that the school enrollment rates (SMP) and poor people percentage affected the HDI of 30 districts (cities) in East Kalimantan, Central Kalimantan and South Kalimantan. Meanwhile the population density affected the HDI of two districts namely HDI of Samarinda and Bontang.
Analisis Cluster Pada Data Kategorik dan Numerik dengan Pendekatan Cluster Ensemble
Authors: Lestari Nur Aini Ayu , Hayati Memi Nor , Amijaya Fidia Deny Tisna
Published: July 2024

Cluster analysis used to process categorical and numerical data at once is Cluster Ensemble algorithm Based on Mixed Data Clustering (algCEBMDC), which is a cluster algorithm with an ensemble cluster approach. The method used for numerical data is Agglomerative Nesting (AGNES) algorithm and for categorical data is the RObust Clustering using linK (ROCK) algorithm. The best clustering method and the optimum number of clusters in the AGNES algorithm is selected based on the maximum Pseudo-F value and the minimum icdrate value. The optimum number of clusters in the ROCK algorithm is selected using the minimum value of  ratio . The purpose of this study was to make a group of 179 Puskesmas in East Kalimantan on December 2017. Based on the results of the analysis, obtained 5 optimum cluster for numerical clustering with the AGNES algorithm and 2 optimum cluster for categorical clustering data with the ROCK algorithm. Final cluster for mixed data clustering obtained 2 optimum cluster at a threshold of 0.2 and 0.3 with value of ratio  is . The first cluster consists of 83 Puskesmas and cluster two of 96 Puskesmas.
Estimasi Parameter Model Regresi Linier dengan Pendekatan Bayes
Authors: Katianda Kristin Rulin , Goejantoro Rito , Satriya Andi M Ade
Published: July 2024

Two types of viewpoints in statistics are Frequentist and Bayesian Method. In Bayesian method sees a parameter as a random variable, so the value is not single. Frequentist method that are often used in linear regression are Ordinary Least Square (OLS) and Maximum Likelihood Estimation (MLE). But along with developments, several studies show the results of modeling that are better at using Bayesian method than the Frequentist method. The data used is Poverty data in 2017 from BPS East Kalimantan. The purpose of this study is to estimate the parameters of the regression model with the Bayesian method on data on the number of poor people and regional domestic products in East Kalimantan Province in 2017. To estimate the parameters of the Bayesian linear regression model it is used by the prior conjugate distribution. Then the markov chain is designed from the posterior distribution with Gibbs Sampler as many as 50.000 iterations and the estimated parameters that are the average of the Gibbs Sampler value are = 0.9149, = 5.462, and = 0.2827. From the Gibbs Sampler values ​​that have been obtained, a density function for each parameter is generated so that the Bayesian confidence interval (credible interval) for estimation is  (0.85; 0.9836),  (4.484; 6.439) and (0.2694 ; 0,296) for parameters .
Pengelompokan Data Kategorik Dengan Algoritma Robust Clustering Using Links
Authors: Dewi Isma , Syaripuddin Syaripuddin , Hayati Memi Nor
Published: July 2024

Cluster analysis is a technique of data mining that is used to group data based on the similarity of attributes of data objects. The problem that is often encountered in cluster analysis is the data on a categorical scale. Categorical scale data grouping can be done using the ROCK (RObust Clustering using linKs) algorithm. The ROCK algorithm is included in the of agglomerative hierarchical clustering algorithms in cluster analysis. This algorithm introduces a concept called neighbors and links in grouping data. Categorical data grouping with ROCK algorithm is done in three steps. The first step is counting similarities. The second step is determining the neighbors and the last is calculating the links between the observation objects. The value of the link is affected by θ. The optimum number of clusters in the ROCK algorithm is selected using a minimum ratio value of . The purpose of this study is to group 100 data of insurance customers of PT. Prudential Life Samarinda in 2018. Based on the analysis results, obtained that the optimum group is at θ = 0.1 with a ratio value of  is 0.1371. The optimum number of groups formed is 2 clusters. The first group consisted of 42 customers and the second group consisted of 58 customers.
Perbandingan Metode Klasifikasi Naïve Bayes Dan Jaringan Saraf Tiruan
Authors: Ardyanti Hesti , Goejantoro Rito , Amijaya Fidia Deny Tisna
Published: July 2024

Classification is a technique to form a model of data that is already known to its classification group. The model that was formed will be used to classify new object. Naïve Bayes is a classification technique for predicting future probability based on past experiences with a strong assumption of independence. Artificial neural network is one of the data mining analysis tools that can be used to create data on classification. Model selection in artifial neural networks requires various factors such as the selection of optimal number of hidden neuron. This research has a goal to compare the level of classification accuracy between the Naïve Bayes method and artificial neural network on payment status of the insurance premium. The data used is insurance costumer’s data of PT AJB Bumiputera Samarinda in 2018. The result of the comparison of accuracy calculation from the two analyzes indicate that artificial neural network has a higher level of accuracy than naïve Bayes method. Classification accuracy result of Naïve Bayes is 82,76% and artificial neural network is 86,21%.
Penerapan Algoritma K-Medoids pada Pengelompokan Wilayah Desa atau Kelurahan di Kabupaten Kutai Kartanegara
Authors: Ibrahim Rizky Nur , Hayati Memi Nor , Amijaya Fidia Deny Tisna
Published: July 2024

Kutai Kartanegara Regency (Kukar) was recorded as the largest contributor to the poor population in East Kalimantan (Kaltim) Province in 2017, so that appropriate strategies are needed to solve proverty problems. The development strategy is prioritized for the regions with the largest number of poor people. Identification is conducted based on facilities, infrastructures, access, social, population and economy is provided in the Village Potential data (PODES). K-Medoids is a grouping method that uses representative objects as a central point, which can be used to find out the characteristics of a region. This research is aimed to find out the optimal cluster formed by choosing the largest value of Silhouette Coefficient (SC) from the grouping of villages / political district in Kukar Regency using PODES data in 2018. Clusters that will be formed in this research are 2 clusters, 3 clusters, 4 clusters and 5 clusters. Based on the analysis, it can be seen that the value of SC 2 cluster is 0.430, the value of SC 3 cluster is 0.174, the value of SC 4 cluster is 0.175 and the value of SC 5 cluster is 0.196. So that the largest SC or optimal cluster values ​​obtained in the grouping of 2 clusters with a SC value of 0.430. Cluster 1 consists of 186 villages / political dsitrict and cluster 2 consists of 46 villages / political district.
Perbandingan Metode Klasifikasi Naive Bayes dan K-Nearest Neighbor
Authors: Novalia Viona , Goejantoro Rito , Sifriyani Sifriyani
Published: July 2024

Classification is a technique to build a model and assess an object to put in a particular class. Naive Bayes is one of algorithm in the classification based on the Bayesian theorem, which assumes the independencies of one class with another class. K-nearest neighbor is an algorithm in the classification method for classifiying based on data that has a closest distance between one object and another object. Naive Bayes and k-nearest neighbor methods are used in classification of the employment status of citizen in Kutai Kartanegara regency because has a good accuracy and produce a small error rate when using large data sets. This research aim to compared optimal performance accuracy of  both methods on the classifiying of the employment status of  citizen. The data used are employment status of citizen in Kutai Kartanegara Regency based on SAKERNAS of East Kalimantan Province in 2018 and used 5 factors namely age, sex, status in the household, marital status, and education to predict employment status of citizen. Based on the analysis, classification the employment status of citizen with naive Bayes method has accuracy of 90,08% and in the k-nearest neighbor has accuracy of 94,66%. To evaluate the accuracy of classification used calculation of Press’s Q. Based on Press’s Q value showed that both of classification methods are accurate. From that analysis, can be concluded that the k-nearest neighbor method works better compared with the naive Bayes method for the case of the employment status of citizen in Kutai Kartanegara Regency.
Penaksiran Kandungan Klorida di Sungai Mahakam Wilayah Samarinda Tahun 2017 dengan Metode Cokriging
Authors: Putra Eko Prasatyo , Goejantoro Rito , Suyitno Suyitno
Published: July 2024

Cokriging is the interpolation method of value of an unsampled data by minimizing the variance of the estimation error by utilizing cross correlations between the main variable and the additional variable. This study aims to estimate the chloride content in the Mahakam River in Samarinda by using the cokriging method. The data of this study are spatial data that consists of the main variable data  is chloride content and additional variable data is the pH of the water, as well as the coordinates of the observation location. Semivariogram (matrix covariance) is determined based on the best model, namely theoretical semivariogram. The best theoretical semivariogram model for cross variables is the exponential model, while the best theoretical semivariogram model for the main variable and additional variables are the spherical model. The selected theoretical semivariogram model was used to determine the semivariogram matrix in estimating chloride content in IPA Bantuas and Teluk Lerong. The results of estimation of chloride content in IPA Bantuas and Teluk Lerong are 1.91 mg/l and 1.64 mg/l. Based on the estimated chloride content in IPA Bantuas and in Teluk Lerong, it shows that the chloride content is still below the maximum threshold and meets the water chloride content standard for consumption by the Ministry of Health of the Republic of Indonesia, which is a maximum of 250 mg/l.
Pemodelan Indeks Pembangunan Manusia (IPM) Menggunakan Analisis Regresi Probit
Authors: Christyadi Santo , Satriya Andi M Ade , Goejantoro Rito
Published: July 2024

Ordinal probit regression analysis is non-linear regression analysis that used to find affected independent variables for ordered categorical dependent variable and regression model in this analysis used Normal cumulative distribution function. Parameter estimation in this model used Maximum Likelihood Estimation (MLE) method. This model has been applied to Human Development Index (HDI) in Borneo Island in 2017 case study. HDI is the most important measurement in improving the human development quality in all cities/regencies in Indonesia. Some factors that affected to IPM, they are Life Expectancy (X1), School Expectancy (X2), Spending per Capita (X3), Average School Duration (X4), and Labour Force Participation Rate (X5). Based on research that was performed by researcher, resulted two factors affecting to HDI, those are Life Expetancy and Average School Duration. This model has classification accuracy of 89,29%, APER (Apparent Error Rate) value of 10,71%, and AIC (Akaike Information Criterion) value of 39,75; this model was very good because prediction value is almost approaching to observation value (actual value).
Perbandingan Diagram Kontrol Demerit dan Fuzzy u
Authors: Septilasse Rebeka Norcaline , Goejantoro Rito , Wahyuningsih Sri
Published: July 2024

Control chart is a graph that provides a picture of a running process whether under controlled conditions or not. Demerit control chart and fuzzy u control chart are very suitable for production quality control. This study was applied to the data of defects of plywood products at pt. segara timber, samarinda, east Kalimantan in 2019. The purpose of this study is to get the results of a comparison of the decision of Demerit control chart and fuzzy u control chart. The results of this study shows the demerit control chart is more thorough than the fuzzy u control chart due to the demerit control chart found 12 out of control observations and the fuzzy u control chart only found 1 out of control observations.
Analisis Spasial Persebaran Jumlah Kasus Malaria di Kalimantan Timur Menggunakan Indeks Moran dan Local Indicator Spatial of Autocorrelation
Authors: Hadisti Zahrah Dhafina , Hayati Memi Nor , Fauziyah Meirinda
Published: July 2024

Spatial analysis is an analysis that considers the location and distance of an object in the research data. Moran’s index is one of the spatial methods used to analyze spatial autocorrelation globally. Furthermore, there is the Local Indicator of Spatial Autocorrelation (LISA) method which is used to analyze spatial autocorrelation locally. This study aims to determine whether there is spatial autocorrelation and determine the distribution pattern formed in the data on the average number of malaria cases in East Kalimantan based on the regency/city during 2018-2022. The results showed that based on the Moran index globally, there was no spatial autocorrelation in the average number of malaria cases in East Kalimantan in 2018-2022. The type of spatial pattern in the distribution of malaria cases in East Kalimantan is a clustering pattern indicated by the clustering of malaria cases in each district/city in East Kalimantan. Furthermore, the results of spatial autocorrelation using LISA show that locally there is spatial autocorrelation in several districts/cities in East Kalimantan, namely Paser, Kutai Timur, Kutai Barat and Penajam Paser Utara.
Indonesia Gold Price Forecasting Using ARIMA Model (0,1,1) - GARCH (1,0)
Authors: Sari Hafivah Rosvita , Wahyuningsih Sri , Siringoringo Meiliyani
Published: July 2024

A frequently employed time series model is the Autoregressive Integrated Moving Average (ARIMA) model. In highly volatile data, ARIMA models sometimes produce residual variances that are heteroscedasticity. One method that can overcome the problem of residual variance heteroscedasticity is the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) method. The purpose of this study is to obtain the ARIMA-GARCH model for daily gold price data in Indonesia for the period 1 January 2022 to 31 December 2022, and to obtain daily gold price forecasting results in Indonesia. The daily gold price forecasting model obtained for Indonesia is ARIMA (0,1,1) - GARCH (1,0) with a MAPE value of 0.5745% which shows that the model is very good because the MAPE value is less than 10%. The results of Indonesia's daily gold price forecast from January 1st, 2023 to January 3rd, 2023 remain stable.